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  • 1.
    Abella, Jaume
    et al.
    Barcelona Supercomputing Center, Barcelona, Spain.
    Perez, Jon
    Ikerlan Technology Research Centre, Arrasate, Spain.
    Englund, Cristofer
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Zonooz, Bahram
    Navinfo Europe, Eindhoven, Netherlands.
    Giordana, Gabriele
    AIKO S.r.l., Torino, Italy.
    Donzella, Carlo
    Exida Development s.r.l.,Colleretto Giacosa, Italy.
    Cazorla, Francisco J.
    Barcelona Supercomputing Center, Barcelona, Spain.
    Mezzetti, Enrico
    Barcelona Supercomputing Center, Barcelona, Spain.
    Serra, Isabel
    Barcelona Supercomputing Center, Barcelona, Spain.
    Brando, Axel
    Barcelona Supercomputing Center, Barcelona, Spain.
    Agirre, Irune
    Ikerlan Technology Research Centre, Arrasate, Spain.
    Eizaguirre, Fernando
    Ikerlan Technology Research Centre, Arrasate, Spain.
    Bui, Thanh Hai
    RISE Research Institutes of Sweden, Lund, Sweden.
    Arani, Elahe
    Navinfo Europe, Eindhoven, Netherlands.
    Sarfraz, Fahad
    Navinfo Europe, Eindhoven, Netherlands.
    Balasubramaniam, Ajay
    Navinfo Europe, Eindhoven, Netherlands.
    Badar, Ahmed
    Navinfo Europe, Eindhoven, Netherlands.
    Bloise, Ilaria
    AIKO S.r.l., Torino, Italy.
    Feruglio, Lorenzo
    AIKO S.r.l., Torino, Italy.
    Cinelli, Ilaria
    AIKO S.r.l., Torino, Italy.
    Brighenti, Davide
    Exida Engineering S.r.l., Rovereto, Italy.
    Cunial, Davide
    Exida Engineering S.r.l., Rovereto, Italy.
    SAFEXPLAIN: Safe and Explainable Critical Embedded Systems Based on AI2023In: DATE 23: Design, Automation And Test In Europe: The European Event For Electronic System Design & Test, 2023, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Deep Learning (DL) techniques are at the heart of most future advanced software functions in Critical Autonomous AI-based Systems (CAIS), where they also represent a major competitive factor. Hence, the economic success of CAIS industries (e.g., automotive, space, railway) depends on their ability to design, implement, qualify, and certify DL-based software products under bounded effort/cost. However, there is a fundamental gap between Functional Safety (FUSA) requirements on CAIS and the nature of DL solutions. This gap stems from the development process of DL libraries and affects high-level safety concepts such as (1) explainability and traceability, (2) suitability for varying safety requirements, (3) FUSA-compliant implementations, and (4) real-time constraints. As a matter of fact, the data-dependent and stochastic nature of DL algorithms clashes with current FUSA practice, which instead builds on deterministic, verifiable, and pass/fail test-based software. The SAFEXPLAIN project tackles these challenges and targets by providing a flexible approach to allow the certification - hence adoption - of DL-based solutions in CAIS building on: (1) DL solutions that provide end-to-end traceability, with specific approaches to explain whether predictions can be trusted and strategies to reach (and prove) correct operation, in accordance to certification standards; (2) alternative and increasingly sophisticated design safety patterns for DL with varying criticality and fault tolerance requirements; (3) DL library implementations that adhere to safety requirements; and (4) computing platform configurations, to regain determinism, and probabilistic timing analyses, to handle the remaining non-determinism. © 2023 EDAA.

  • 2.
    Alonso-Fernandez, Fernando
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bigun, Josef
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    Expression Recognition Using the Periocular Region: A Feasibility Study2018In: 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) / [ed] Gabriella Sanniti di Baja, Luigi Gallo, Kokou Yetongnon, Albert Dipanda, Modesto Castrillón-Santana & Richard Chbeir, Los Alamitos: IEEE, 2018, p. 536-541Conference paper (Refereed)
    Abstract [en]

    This paper investigates the feasibility of using the periocular region for expression recognition. Most works have tried to solve this by analyzing the whole face. Periocular is the facial region in the immediate vicinity of the eye. It has the advantage of being available over a wide range of distances and under partial face occlusion, thus making it suitable for unconstrained or uncooperative scenarios. We evaluate five different image descriptors on a dataset of 1,574 images from 118 subjects. The experimental results show an average/overall accuracy of 67.0%/78.0% by fusion of several descriptors. While this accuracy is still behind that attained with full-face methods, it is noteworthy to mention that our initial approach employs only one frame to predict the expression, in contraposition to state of the art, exploiting several order more data comprising spatial-temporal data which is often not available.

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  • 3.
    Andersson, Jonas
    et al.
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Habibovic, Azra
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Klingegård, Maria
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Englund, Cristofer
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Malmsten-Lundgren, Victor
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Hello human, can you read my mind?2017In: ERCIM News, ISSN 0926-4981, E-ISSN 1564-0094, no 109, p. 36-37Article, review/survey (Refereed)
    Abstract [en]

    For safety reasons, autonomous vehicles should communicate their intent rather than explicitly invite people to act. At RISE Viktoria in Sweden, we believe this simple design principle will impact how autonomous vehicles are experienced in the future.

  • 4.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Detournay, J.
    Swedish National Transport Research Institute, Gothenburg, SE-402 78, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Frimodig, Viktor
    Halmstad University, School of Information Technology.
    Jansson, Oscar Uddman
    Swedish National Transport Research Institute, Gothenburg, SE-402 78, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Mostowski, Wojciech
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Díez Rodríguez, Víctor
    Halmstad University, School of Information Technology.
    Rosenstatter, Thomas
    Halmstad University, School of Information Technology.
    Shahanoor, Golam
    Halmstad University, School of Information Technology.
    Team Halmstad Approach to Cooperative Driving in the Grand Cooperative Driving Challenge 20162018In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 19, no 4, p. 1248-1261Article in journal (Refereed)
    Abstract [en]

    This paper is an experience report of team Halmstad from the participation in a competition organised by the i-GAME project, the Grand Cooperative Driving Challenge 2016. The competition was held in Helmond, The Netherlands, during the last weekend of May 2016. We give an overview of our car’s control and communication system that was developed for the competition following the requirements and specifications of the i-GAME project. In particular, we describe our implementation of cooperative adaptive cruise control, our solution to the communication and logging requirements, as well as the high level decision making support. For the actual competition we did not manage to completely reach all of the goals set out by the organizers as well as ourselves. However, this did not prevent us from outperforming the competition. Moreover, the competition allowed us to collect data for further evaluation of our solutions to cooperative driving. Thus, we discuss what we believe were the strong points of our system, and discuss post-competition evaluation of the developments that were not fully integrated into our system during competition time. © 2000-2011 IEEE.

  • 5.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Göteborg, Sweden.
    Jansson, Jonas
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Nåbo, Arne
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Safety Analysis of Cooperative Adaptive Cruise Control in Vehicle Cut-in Situations2017In: Proceedings of 2017 4th International Symposium on Future Active Safety Technology towards Zero-Traffic-Accidents (FAST-zero), Society of Automotive Engineers of Japan , 2017, article id 20174621Conference paper (Refereed)
    Abstract [en]

    Cooperative adaptive cruise control (CACC) is a cooperative intelligent transport systems (C-ITS) function, which especially when used in platooning applications, possess many expected benefits including efficient road space utilization and reduced fuel consumption. Cut-in manoeuvres in platoons can potentially reduce those benefits, and are not desired from a safety point of view. Unfortunately, in realistic traffic scenarios, cut-in manoeuvres can be expected, especially from non-connected vehicles. In this paper two different controllers for platooning are explored, aiming at maintaining the safety of the platoon while a vehicle is cutting in from the adjacent lane. A realistic scenario, where a human driver performs the cut-in manoeuvre is used to demonstrate the effectiveness of the controllers. Safety analysis of CACC controllers using time to collision (TTC) under such situation is presented. The analysis using TTC indicate that, although potential risks are always high in CACC applications such as platooning due to the small inter-vehicular distances, dangerous TTC (TTC < 6 seconds) is not frequent. Future research directions are also discussed along with the results.

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  • 6.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). The Swedish National Road and Transport Research Institute (VTI), Göteborg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Göteborg, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Jansson, Jonas
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Nåbo, Arne
    The Swedish National Road and Transport Research Institute (VTI), Göteborg, Sweden.
    Safety Evaluation of Highway Platooning Under a Cut-In Situation Using SimulationManuscript (preprint) (Other (popular science, discussion, etc.))
    Abstract [en]

    Platooning refers to an application, where a group of connected and automated vehicles follow a lead vehicle autonomously, with short inter-vehicular distances. At merging points on highways such as on-ramp, platoons could encounter manually driven vehicles, which are merging on to the highways. In some situations, the manually driven vehicles could end up between the platooning vehicles. Such situations are expected and known as “cut-in” situations. This paper presents a simulation study of a cut-in situation, where a platoon of five vehicles encounter a manually driven vehicle at a merging point of a highway. The manually driven vehicle is driven by 37 test persons using a driving simulator. For the platooning vehicles, two longitudinal controllers with four gap settings between the platooning vehicles, i.e. 15 meters, 22.5 meters, 30 meters, and 42.5 meters, are evaluated. Results summarizing cut-in behaviours and how the participants perceived the situation are presented. Furthermore, the situation is assessed using safety indicators based on time-to-collision.

  • 7.
    Aramrattana, Maytheewat
    et al.
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Habibovic, Azra
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Safety and experience of other drivers while interacting with automated vehicle platoons2021In: Transportation Research Interdisciplinary Perspectives, ISSN 2590-1982, Vol. 10, article id 100381Article in journal (Refereed)
    Abstract [en]

    It is currently unknown how automated vehicle platoons will be perceived by other road users in their vicinity. This study explores how drivers of manually operated passenger cars interact with automated passenger car platoons while merging onto a highway, and how different inter-vehicular gaps between the platooning vehicles affect their experience and safety. The study was conducted in a driving simulator and involved 16 drivers of manually operated cars. Our results show that the drivers found the interactions mentally demanding, unsafe, and uncomfortable. They commonly expected that the platoon would adapt its behavior to accommodate a smooth merge. They also expressed a need for additional information about the platoon to easier anticipate its behavior and avoid cutting-in. This was, however, affected by the gap size; larger gaps (30 and 42.5 m) yielded better experience, more frequent cut-ins, and less crashes than the shorter gaps (15 and 22.5 m). A conclusion is that a short gap as well as external human–machine interfaces (eHMI) might be used to communicate the platoon's intent to “stay together”, which in turn might prevent drivers from cutting-in. On the contrary, if the goal is to facilitate frequent, safe, and pleasant cut-ins, gaps larger than 22.5 m may be suitable. To thoroughly inform such design trade-offs, we urge for more research on this topic. © 2021 The Author(s)

  • 8.
    Aramrattana, Maytheewat
    et al.
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Gothenburg, Sweden.
    Jansson, Jonas
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Nåbo, Arne
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    A Novel Risk Indicator for Cut-In Situations2020In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Piscataway, NJ: IEEE, 2020, article id 9294315Conference paper (Refereed)
    Abstract [en]

    Cut-in situations occurs when a vehicle intention- ally changes lane and ends up in front of another vehicle or in-between two vehicles. In such situations, having a method to indicate the collision risk prior to making the cut-in maneuver could potentially reduce the number of sideswipe and rear end collisions caused by the cut-in maneuvers. This paper propose a new risk indicator, namely cut-in risk indicator (CRI), as a way to indicate and potentially foresee collision risks in cut-in situations. As an example use case, we applied CRI on data from a driving simulation experiment involving a manually driven vehicle and an automated platoon in a highway merging situation. We then compared the results with time-to-collision (TTC), and suggest that CRI could correctly indicate collision risks in a more effective way. CRI can be computed on all vehicles involved in the cut-in situations, not only for the vehicle that is cutting in. Making it possible for other vehicles to estimate the collision risk, for example if a cut-in from another vehicle occurs, the surrounding vehicles could be warned and have the possibility to react in order to potentially avoid or mitigate accidents. © 2020 IEEE.

  • 9.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology.
    Larsson, Tony
    Halmstad University, School of Information Technology.
    Englund, Cristofer
    Halmstad University, School of Information Technology. RISE Viktoria, Gothenburg, Sweden.
    Jansson, Jonas
    Swedish National Road and Transport Research Institute (VTI), Sweden.
    Nåbo, Arne
    Swedish National Road and Transport Research Institute (VTI), Sweden.
    A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations2022In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, no 4, p. 3790-3796Article in journal (Refereed)
    Abstract [en]

    Platooning refers to a group of vehicles that--enabled by wireless vehicle-to-vehicle (V2V) communication and vehicle automation--drives with short inter-vehicular distances. Before its deployment on public roads, several challenging traffic situations need to be handled. Among the challenges are cut-in situations, where a conventional vehicle--a vehicle that has no automation or V2V communication--changes lane and ends up between vehicles in a platoon. This paper presents results from a simulation study of a scenario, where a conventional vehicle, approaching from an on-ramp, merges into a platoon of five cars on a highway. We created the scenario with four platooning gaps: 15, 22.5, 30, and 42.5 meters. During the study, the conventional vehicle was driven by 37 test persons, who experienced all the platooning gaps using a driving simulator. The participants' opinions towards safety, comfort, and ease of driving between the platoon in each gap setting were also collected through a questionnaire. The results suggest that a 15-meter gap prevents most participants from cutting in, while causing potentially dangerous maneuvers and collisions when cut-in occurs. A platooning gap of at least 30 meters yield positive opinions from the participants, and facilitating more smooth cut-in maneuvers while less collisions were observed.

  • 10.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Gothenburg, Sweden.
    Jansson, Jonas
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Nåbo, Arne
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Simulation of Cut-In by Manually Driven Vehicles in Platooning Scenarios2017In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), Piscataway, NJ: IEEE, 2017, p. 1-6Conference paper (Refereed)
    Abstract [en]

    In the near future, Cooperative Intelligent Transport System (C-ITS) applications are expected to be deployed. To support this, simulation is often used to design and evaluate the applications during the early development phases. Simulations of C-ITS scenarios often assume a fleet of homogeneous vehicles within the transportation system. In contrast, once C-ITS is deployed, the traffic scenarios will consist of a mixture of connected and non-connected vehicles, which, in addition, can be driven manually or automatically. Such mixed cases are rarely analysed, especially those where manually driven vehicles are involved. Therefore, this paper presents a C-ITS simulation framework, which incorporates a manually driven car through a driving simulator interacting with a traffic simulator, and a communication simulator, which together enable modelling and analysis of C-ITS applications and scenarios. Furthermore, example usages in the scenarios, where a manually driven vehicle cut-in to a platoon of Cooperative Adaptive Cruise Control (CACC) equipped vehicles are presented. © 2017 IEEE.

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  • 11.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Larsson, Tony
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Jansson, Jonas
    The Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden.
    Dimensions of Cooperative Driving, ITS and Automation2015In: 2015 IEEE Intelligent Vehicles Symposium (IV), Piscataway, NJ: IEEE Press, 2015, p. 144-149Conference paper (Refereed)
    Abstract [en]

    Wireless technology supporting vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communication, allow vehicles and infrastructures to exchange information, and cooperate. Cooperation among the actors in an intelligent transport system (ITS) can introduce several benefits, for instance, increase safety, comfort, efficiency. Automation has also evolved in vehicle control and active safety functions. Combining cooperation and automation would enable more advanced functions such as automated highway merge and negotiating right-of-way in a cooperative intersection. However, the combination have influences on the structure of the overall transport systems as well as on its behaviour. In order to provide a common understanding of such systems, this paper presents an analysis of cooperative ITS (C-ITS) with regard to dimensions of cooperation. It also presents possible influence on driving behaviour and challenges in deployment and automation of C-ITS.

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  • 12.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology. Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Patel, Raj Haresh
    Communication Systems Department, EURECOM, Sophia-Antipolis, France.
    Englund, Cristofer
    Halmstad University, School of Information Technology. RISE Viktoria, Gothenburg, Sweden.
    Harri, Jerome
    Communication Systems Department, EURECOM, Sophia-Antipolis, France.
    Jansson, Jonas
    Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Bonnet, Christian
    Communication Systems Department, EURECOM, Sophia-Antipolis, France.
    Evaluating Model Mismatch Impacting CACC Controllers in Mixed Traffic using a Driving Simulator2018In: 2018 IEEE Intelligent Vehicles Symposium (IV), New York, NY: IEEE, 2018, p. 1867-1872Conference paper (Refereed)
    Abstract [en]

    At early market penetration, automated vehicles will share the road with legacy vehicles. For a safe transportation system, automated vehicle controllers therefore need to estimate the behavior of the legacy vehicles. However, mismatches between the estimated and real human behaviors can lead to inefficient control inputs, and even collisions in the worst case. In this paper, we propose a framework for evaluating the impact of model mismatch by interfacing a controller under test with a driving simulator. As a proof-of-concept, an algorithm based on Model Predictive Control (MPC) is evaluated in a braking scenario. We show how model mismatch between estimated and real human behavior can lead to a decrease in avoided collisions by almost 46%, and an increase in discomfort by almost 91%. Model mismatch is therefore non-negligible and the proposed framework is a unique method to evaluate them. © 2018 IEEE.

  • 13.
    Aramrattana, Maytheewat
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Patel, Raj Haresh
    Communication Systems Department, EURECOM, Sophia-Antipolis, France.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). RISE Viktoria, Gothenburg, Sweden.
    Härri, Jérôme
    Communication Systems Department, EURECOM, Sophia-Antipolis, France.
    Jansson, Jonas
    Swedish National Road and Transport Research Institute (VTI), Linköping, Sweden.
    Bonnet, Christian
    Communication Systems Department, EURECOM, Sophia-Antipolis, France.
    Evaluating Model Mismatch Impacting CACC Controllers in Mixed2018In: 2018 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2018, p. 1867-1872Conference paper (Refereed)
    Abstract [en]

    At early market penetration, automated vehicles will share the road with legacy vehicles. For a safe transportation system, automated vehicle controllers therefore need to estimate the behavior of the legacy vehicles. However, mismatches between the estimated and real human behaviors can lead to inefficient control inputs, and even collisions in the worst case. In this paper, we propose a framework for evaluating the impact of model mismatch by interfacing a controller under test with a driving simulator. As a proof- of-concept, an algorithm based on Model Predictive Control (MPC) is evaluated in a braking scenario. We show how model mismatch between estimated and real human behavior can lead to a decrease in avoided collisions by almost 46%, and an increase in discomfort by almost 91%. Model mismatch is therefore non-negligible and the proposed framework is a unique method to evaluate them. © 2018 IEEE.

  • 14.
    Arvidsson, Moa
    et al.
    Halmstad University, School of Information Technology, Center for Applied Intelligent Systems Research (CAISR).
    Sawirot, Sithichot
    Halmstad University, School of Information Technology, Center for Applied Intelligent Systems Research (CAISR).
    Englund, Cristofer
    Halmstad University, School of Information Technology, Center for Applied Intelligent Systems Research (CAISR).
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Center for Applied Intelligent Systems Research (CAISR).
    Torstensson, Martin
    RISE Viktoria, Gothenburg, Sweden.
    Duran, Boris
    RISE Viktoria, Gothenburg, Sweden.
    Drone navigation and license place detection for vehicle location in indoor spaces2023In: Progress in Artificial Intelligence and Pattern Recognition / [ed] Yanio Hernández Heredia; Vladimir Milián Núñez; José Ruiz Shulcloper, Heidelberg: Springer, 2023, p. 362-374Conference paper (Refereed)
    Abstract [en]

    Millions of vehicles are transported every year, tightly parked in vessels or boats. To reduce the risks of associated safety issues like fires, knowing the location of vehicles is essential, since different vehicles may need different mitigation measures, e.g. electric cars. This work is aimed at creating a solution based on a nano-drone that navigates across rows of parked vehicles and detects their license plates. We do so via a wall-following algorithm, and a CNN trained to detect license plates. All computations are done in real-time on the drone, which just sends position and detected images that allow the creation of a 2D map with the position of the plates. Our solution is capable of reading all plates across eight test cases (with several rows of plates, different drone speeds, or low light) by aggregation of measurements across several drone journeys. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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  • 15.
    Bengtsson, Hoai
    et al.
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Chen, Lei
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Voronov, Alexey
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden.
    Interaction Protocol for Highway Platoon Merge2015In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems / [ed] Lisa O’Conner, Los Alamitos: IEEE, 2015, p. 1971-1976, article id 7313411Conference paper (Refereed)
    Abstract [en]

    An interaction protocol for cooperative platoon merge on highways is proposed. The interaction protocol facilitates a challenge scenario for the Grand Cooperative Driving Challenge (GCDC) 2016, where two platoons running on separate lanes merge into one platoon due to a roadwork in one of the lanes. Detailed interaction procedures, described with state machines of each vehicle are presented. A communication message set is designed to support platoon controllers to perform safe and efficient manoeuvres. © 2015 IEEE.

  • 16.
    Bergman, Lars
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kindberg, J.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Olsson, J.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Sjögren, B.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Modelling and Control of the Web-Fed Offset Newspaper Printing Press2003In: Proceedings of the Technical Association of the Graphic Arts, TAGA, Technical Association of the Graphic (TAGA) , 2003, p. 27-29Conference paper (Refereed)
    Abstract [en]

    We present an approach to modelling and controlling the web-fed offset printing process. An image processing and artificial neural networks based device is used to measure the printing process output - the observable variables. The observable variables are measured on halftone areas and integrate information about both ink densities and dot sizes. From only one measurement the device is capable of estimating the actual relative amount of each cyan, magenta, yellow, and black ink dispersed on paper in the measuring area. We build and test linear and non-linear printing press models using the measured variables andother parameters characterising the press. The observable variables measured and the press model developed are then further used by a control unit for generating control signals - signals for controlling the ink keys - to compensate for colour deviation. The experimental investigations performed have shown that the non-linear model developed is accurate enough to be used in a control loop for controlling the printing process. The control accuracy - the tracking accuracy of the desired ink level - obtained from the controller was higher than that observed when controlling the press by the operator.

  • 17.
    Borg, Markus
    et al.
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Englund, Cristofer
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Durann, Boris
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Lewandowski, Christoffer
    QRTECH AB, Mölndal, Sweden.
    Gao, Shenjian
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Tan, Yanwen
    Blekinge Institute of Technology, Karlskrona, Sweden.
    Kaijser, Henrik
    AB Volvo, Volvo Group Trucks Technology, Gothenburg, Sweden.
    Lönn, Henrik
    AB Volvo, Volvo Group Trucks Technology, Gothenburg, Sweden.
    Törnqvist, Jonnas
    QRTECH AB, Mölndal, Sweden.
    Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industry2019In: Journal of Automotive Software Engineering, ISSN 2589-2258, Vol. 1, no 1, p. 1-19Article in journal (Refereed)
    Abstract [en]

    Deep neural networks (DNNs) will emerge as a cornerstone in automotive software engineering. However, developing systems with DNNs introduces novel challenges for safety assessments. This paper reviews the state-of-the-art in verification and validation of safety-critical systems that rely on machine learning. Furthermore, we report from a workshop series on DNNs for perception with automotive experts in Sweden, confirming that ISO 26262 largely contravenes the nature of DNNs. We recommend aerospace-to-automotive knowledge transfer and systems-based safety approaches, for example, safety cage architectures and simulated system test cases.© 2019 The Authors.

  • 18.
    Chen, Lei
    et al.
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Englund, Cristofer
    Research Institutes of Sweden, RISE Viktoria, Gothenburg, Sweden.
    Choreographing services for smart cities: smart traffic demonstration2017In: Vehicular Technology Conference (VTC Spring), 2017 IEEE 85th, Sydney, Australia: IEEE, 2017Conference paper (Refereed)
    Abstract [en]

    With the fifth generation (5G) communication technologies on the horizon, the society is rapidly transformed into a fully connected world. The Future Internet (FI) is foreseeable to consist of an infinite number of software components and things that coordinate with each other to enable different applications. Transport systems, as one of the most important systems in future smart cities, will embrace the connectivity, together with the fast development of cooperative and automated vehicles to enable smart traffic. To facilitate this transformation, a service choreography composition platform is under development to enable fast innovation and prototyping of choreography-based Internet of Things (IoT) applications by automatically synthesizing choreographies. Based on the method, a smart traffic application is developed and demonstrated.

  • 19.
    Chen, Lei
    et al.
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden & SAFER Vehicle and Traffic Safety Centre, Chalmers University of Technology, Gothenburg.
    Cooperative Intersection Management: A Survey2016In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 17, no 2, p. 570-586Article, review/survey (Refereed)
    Abstract [en]

    Intersection management is one of the most challenging problems within the transport system. Traffic light-based methods have been efficient but are not able to deal with the growing mobility and social challenges. On the other hand, the advancements of automation and communications have enabled cooperative intersection management, where road users, infrastructure, and traffic control centers are able to communicate and coordinate the traffic safely and efficiently. Major techniques and solutions for cooperative intersections are surveyed in this paper for both signalized and nonsignalized intersections, whereas focuses are put on the latter. Cooperative methods, including time slots and space reservation, trajectory planning, and virtual traffic lights, are discussed in detail. Vehicle collision warning and avoidance methods are discussed to deal with uncertainties. Concerning vulnerable road users, pedestrian collision avoidance methods are discussed. In addition, an introduction to major projects related to cooperative intersection management is presented. A further discussion of the presented works is given with highlights of future research topics. This paper serves as a comprehensive survey of the field, aiming at stimulating new methods and accelerating the advancement of automated and cooperative intersections. © 2015 IEEE.

  • 20.
    Chen, Lei
    et al.
    Research Institutes of Sweden, RISE Viktoria, Lindholmspiren 3A, Gothenburg, 417 56, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Every Second Counts: Integrating Edge Computing and Service Oriented Architecture for Automatic Emergency Management2018In: Journal of Advanced Transportation, ISSN 0197-6729, E-ISSN 2042-3195, p. 13-, article id 7592926Article in journal (Refereed)
    Abstract [en]

    Emergency management has long been recognized as a social challenge due to the criticality of the response time. In emergency situations such as severe traffic accidents, minimizing the response time, which requires close collaborations between all stakeholders involved and distributed intelligence support, leads to greater survival chance of the injured. However, the current response system is far from efficient, despite the rapid development of information and communication technologies. This paper presents an automated collaboration framework for emergency management that coordinates all stakeholders within the emergency response system and fully automates the rescue process. Applying the concept of multiaccess edge computing architecture, as well as choreography of the service oriented architecture, the system allows seamless coordination between multiple organizations in a distributed way through standard web services. A service choreography is designed to globally model the emergency management process from the time an accident occurs until the rescue is finished. The choreography can be synthesized to generate detailed specification on peer-to-peer interaction logic, and then the specification can be enacted and deployed on cloud infrastructures. © 2018 Lei Chen and Cristofer Englund.

  • 21.
    Chen, Lei
    et al.
    Viktoria Swedish ICT, Göteborg, Sweden.
    Habibovic, Azra
    Viktoria Swedish ICT, Göteborg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Göteborg, Sweden.
    Voronov, Alexey
    Viktoria Swedish ICT, Göteborg, Sweden.
    Walter, Anders Lindgren
    MTO Säkerhet, Swedish Road Administration, Stockholm Bypass Project, Stockholm, Sweden.
    Coordinating dangerous goods vehicles: C-ITS applications for safe road tunnels2015In: 2015 IEEE Intelligent Vehicles Symposium (IV), Piscataway, NJ: IEEE, 2015, p. 156-161, article id 7225679Conference paper (Refereed)
    Abstract [en]

    Despite the existing regulation efforts and measures, vehicles with dangerous goods still pose significant risks on public safety, especially in road tunnels. Solutions based on cooperative intelligent transportation system (C-ITS) are promising measures, however, they have received limited attention. We propose C-ITS applications that coordinate dangerous goods vehicles to minimize the risk by maintaining safe distances between them in road tunnels. Different mechanisms, including global centralized coordination, global distributed coordination, and local coordination, are proposed and investigated. A preliminary simulation is performed and demonstrates their effectiveness. © 2015 IEEE.

  • 22.
    Chen, Lei
    et al.
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Torstensson, Martin
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Research Institutes of Sweden, Gothenburg, Sweden.
    Federated learning to enable automotive collaborative ecosystem: opportunities and challenges2020Conference paper (Refereed)
    Abstract [en]

    Despite the strong interests in creating data economy, automotive industries are creating data silos with each stakeholder maintaining its own data cloud. Federated learning (FL), designed for privacy-preserving collaborative Machine Learning (ML), offers a promising method that allows multiple stakeholders to share information through ML models without the exposure of raw data, thus natively protecting privacy. Motivated by the strong need for automotive collaboration and the advancement of FL, this paper investigates how FL could enable privacy-preserving information sharing for automotive industries. We first introduce the statuses and challenges for automotive data sharing, followed by a brief introduction to FL. We then present a comprehensive discussion on potential applications of federated learning to enable an automotive collaborative ecosystem. To illustrate the benefits, we apply FL for driver action classification and demonstrate the potential for collaborative machine learning without data sharing. 

  • 23.
    Cristofer, Englund
    et al.
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Chen, Lei
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Lin, Shih-Yang
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Future Applications of VANETs2015In: Vehicular Ad Hoc Networks: Standards, Solutions, and Research / [ed] Claudia Campolo, Antonella Molinaro & Riccardo Scopigno, Cham: Springer Publishing Company, 2015, p. 525-544Chapter in book (Refereed)
    Abstract [en]

    Current transportation systems face great challenges due to the increasing mobility. Traffic accidents, congestion, air pollution, etc., are all calling for new methods to improve the transportation system. With the US legislation in progress over vehicle communications and EU’s finalization of the basic set of standards over cooperative intelligent transportation systems (C-ITS), vehicular ad hoc network (VANET) based applications are expected to address those challenges and provide solutions for a safer, more efficient and sustainable future intelligent transportation systems (ITS). In this chapter, transportation challenges are firstly summarized in respect of safety, efficiency, environmental threat, etc. A brief introduction of the VANET is discussed along with state of the art of VANET-based applications. Based on the current progress and the development trend of VANET, a number of new features of future VANET are identified, together with a set of potential future ITS applications. The on-going research and field operational test projects, which are the major enabling efforts for the future VANET-based C-ITS, are presented. The chapter is of great interest to readers working within ITS for current development status and future trend within the C-ITS area. It is also of interest to general public for an overview of the VANET enabled future transportation system. © Springer International Publishing Switzerland 2015.

  • 24.
    Durán, Boris
    et al.
    RISE Viktoria, Gothenburg, Sweden.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Gothenburg, Sweden.
    Habobovic, Azra
    RISE Viktoria, Gothenburg, Sweden.
    Andersson, Jonas
    RISE Viktoria, Gothenburg, Sweden.
    Modeling vehicle behavior with neural dynamics2017In: Future Active Safety Technology - Towards zero traffic accidents, Nara, Japan, 2017Conference paper (Refereed)
    Abstract [en]

    Modeling the interaction of vehicles during certain traffic situations is the starting point for creating autonomous driving. Data collected from field trials where test subjects drive through a single-vehicle intersection was used to create behavioral models. The present work describes two implementations of models based on the dynamical systems approach and compares similarities and differences between them. The proposed models are designed to closely replicate the behavior selection in the intersection crossing experiment.

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  • 25.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Action intention recognition of cars and bicycles in intersections2020In: International Journal of Vehicle Design, ISSN 0143-3369, E-ISSN 1741-5314, Vol. 83, no 2-4, p. 103-121Article in journal (Refereed)
    Abstract [en]

    Copyright © 2020 Inderscience Enterprises Ltd.Action intention recognition is becoming increasingly important in the road vehicle automation domain. Autonomous vehicles must be aware of their surroundings if we are to build safe and efficient transport systems. This paper presents a method for predicting the action intentions of road users based on sensors in the road infrastructure. The scenarios used for demonstration are recorded on two different public road sections. The first scenario includes bicyclists and the second includes cars that are driving in a road approaching an intersection where they are either leaving or continuing straight. A 3D camera-based data acquisition system is used to collect trajectories of the road users that are used as input for models trained to predict the action intention of the road users. The proposed system enables future connected and automated vehicles to receive collision warnings from an infrastructure-based sensor system well in advance to enable better planning.

  • 26.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Aware and intelligent infrastructure for action intention recognition of cars and bicycles2020In: Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS / [ed] Berns K.,Helfert M.,Gusikhin O., SciTePress, 2020, p. 281-288Conference paper (Refereed)
    Abstract [en]

    Action intention recognition is becoming increasingly important in the road vehicle automation domain. Autonomous vehicles must be aware of their surroundings if we are to build safe and efficient transport systems. This paper explores methods for predicting the action intentions of road users based on an aware and intelligent 3D camera-based sensor system. The collected data contains trajectories of two different scenarios. The first one includes bicyclists and the second cars that are driving in a road approaching an intersection where they are either turning or continuing straight. The data acquisition system is used to collect trajectories of the road users that are used as input for models trained to predict the action intention of the road users. © 2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

  • 27.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Modelling and controlling an offset lithographic printing process2007Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The objective of this thesis is to provide methods for print quality enhancements in an offset lithographic printing proess. Various parameters characterising the print quality are recognised, however, in this work print quality is defined as the deviation of the amount of ink in a sample image from the reference print.

    The methods developed are model-based and historical data collected at the printing press are used to build the models. Inherent in the historical process data are outliers owing to sensor faults, measurement errors and impurity of the material used. It is essential to detect and remove these outliers to avoid using them to update the process models. A process modelbased outlieer detection tool has been proposed. Several diagnostic measures are ombined via a neural network to achieve robust data categorisation into inlier and outlier classes.

    To cope with the slow variation in printing process data, a SOM-based data mining and adaptive modelling technique has been proposed. The technique continously updates the data set characterising the process and the process models if they become out-of-date. A SOM-based approach to model ombination has been proposed to permit the cration of adaptive - data dependet - committees.

    A multiple models-based controller, which employs the process models developed, is combined with an integrating controller to achieve robust ink feed control. Results have shown that the robust ink feed controller is capable of controlling the ink feed in the newspaper printing press according to the desired process output. Based on the process modelling, techniques have also been developed for initialising the printing press in order to reduce the time needed to achieve the desired print quality. The use of the developed methods and tools at a print shop in Halmstad, Sweden, resulted in higher print quality and lower ink and paper waste.

  • 28.
    Englund, Cristofer
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Modelling the offset lithographic printing process2006Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    A concept for data management and adaptive modelling of the offset lithographic printing process is proposed. Artificial neural networks built from historical process data are used to model the offset printing process aiming to develop tools for online ink flow control.

    Inherent in the historical data are outliers owing to sensor faults, measurement errors and impurity of the materials used. It is fundamental to identify outliers in process data in order to avoid using these data points for updating the model. In this work, a hybrid the process-model-network-based technique for outlier detection is proposed. Several diagnosti measures are aggregated via a neural network to categorize the data points into the oulier or inlier classes. Experimentally it was demonstrated that a fuzzy expert can be configured to label data for training the categorization neural network.

    A SOM based model combination strategy, allowing to create adaptive - data dependent - committees, is proposed to build models used for printing press initialization. Both, the number of models included into a committee and aggregation weights are specific for each input data point analyzed.

    The printing process is constantly changing due to wear, seasonal changes, duration of print jobs etc. Consequently, models trained on historical data become out of date with time and need to be updated. Therefore, a data mining and adaptive modelling approach has been propsed. The experimental investigations performed have shown that the tools developed can follow the process changes and make appropriate adaptations of the ata set and the process models. A low process modelling error has been obtained by employing data dependent committees.

  • 29.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden.
    Chen, Lei
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Ploeg, Jeroen
    Netherlands Organization for Applied Scientific Research TNO, Hague, Netherlands.
    Semsar-Kazerooni, Elham
    Netherlands Organization for Applied Scientific Research TNO, Hague, Netherlands.
    Voronov, Alexey
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Hoang Bengtsson, Hoai
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Didoff, Jonas
    Viktoria Swedish ICT, Gothenburg, Sweden.
    The Grand Cooperative Driving Challenge 2016: Boosting the Introduction of Cooperative Automated Vehicles2016In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 23, no 4, p. 146-152Article in journal (Refereed)
    Abstract [en]

    The Grand Cooperative Driving Challenge (GCDC), with the aim to boost the introduction of cooperative automated vehicles by means of wireless communication, is presented. Experiences from the previous edition of GCDC, which was held in Helmond in the Netherlands in 2011, are summarized, and an overview and expectations of the challenges in the 2016 edition are discussed. Two challenge scenarios, cooperative platoon merge and cooperative intersection passing, are specified and presented. One demonstration scenario for emergency vehicles is designed to showcase the benefits of cooperative driving. Communications closely follow the newly published cooperative intelligent transport system standards, while interaction protocols are designed for each of the scenarios. For the purpose of interoperability testing, an interactive testing tool is designed and presented. A general summary of the requirements on teams for participating in the challenge is also presented.

  • 30.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Viktoria, Gothenburg, Sweden.
    Didoff, Jonas
    RISE Viktoria, Gothenburg, Sweden.
    Wahlström, Björn
    Swedish Aviation Services, Norrköping, Sweden.
    A new method for ground vehicle access control and situation awareness: experiences from a real-life implementation at an airport2017Conference paper (Refereed)
    Abstract [en]

    To improve safety in complex traffic situations, access control can be applied. This paper presents a generic vehicle access control method for improved situation awareness. The method concerns three main steps (i) zones definition (ii) rules to manage access and (iii) situation awareness based on realtime position monitoring. The proposed system consists of a server where the access zones and rules are stored and mobile units providing position data to the server and information to the driver. At the control center a client control unit is used to provide improved situation awareness by monitoring and visualizing the positions of the clients in the vehicles. The client in the control center is also utilized to give access to the clients in the vehicles that request access. The system has been demonstrated at an airport to grant access for ground vehicles to enter the runway and has since been developed into a commercial product by an industrial supplier. It was introduced at the World ATM Congress in Madrid in March of 2017. The server system is implemented as a cloud service in Microsoft Azure, the control client uses a WACOM CINTIQ touch screen computer for interaction and the vehicle clients are off-the-shelf Samsung Android units paired with Trimble R1GNSS receiver and 4G mobile communication between the server and the clients.

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  • 31.
    Englund, Cristofer
    et al.
    RISE Viktoria, Gothenburg, Sweden.
    Engdahl, Henrik
    Nimling AB, Askim, Sweden.
    Habibi, Shiva
    Chalmers University of Technology, Gothenburg, Sweden.
    Pettersson, Stefan
    RISE Viktoria, Gothenburg, Sweden.
    Sprei, Frances
    Chalmers University of Technology, Gothenburg, Sweden.
    Voronov, Alexey
    RISE Viktoria, Gothenburg, Sweden.
    Wedlin, Johan
    RISE Viktoria, Gothenburg, Sweden.
    Method for prediction of Utilization Rate of Electric Vehicle Free-Floating Car Sharing Services using Data Mining2018In: 31st International Electric Vehicles Symposium & Exhibition (EVS 31) & International Electric Vehicle Technology Conference 2018 (EVTeC 2018), 2018Conference paper (Refereed)
    Abstract [en]

    Free-floating car sharing is a form of car rental used by people for short periods of time where the cars can be picked up and returned anywhere within a given area. In this paper, we have collected free-floating car sharing data, for electric as well as fossil fueled cars, and data regarding e.g. size of the city, number of cars in the service, etc. The utilization rates of the free-floating car sharing services vary much between the cities, greatly influencing the success of the services. This paper presents the most important factors influencing the utilization rate, and also a methodology to predict the utilization rate for new cities, using data mining based on Random Forests.© EVS 31 & EVTeC 2018.

  • 32.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Research Institutes of Sweden, Göteborg, Sweden.
    Erdal Aksoy, Eren
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Cooney, Martin Daniel
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Pashami, Sepideh
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. RISE Research Institutes of Sweden, Göteborg, Sweden.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    AI Perspectives in Smart Cities and Communities to Enable Road Vehicle Automation and Smart Traffic Control2021In: Smart Cities, E-ISSN 2624-6511, Vol. 4, no 2, p. 783-802Article in journal (Refereed)
    Abstract [en]

    Smart Cities and Communities (SCC) constitute a new paradigm in urban development. SCC ideates on a data-centered society aiming at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with internet of things enables data collection and with the help of artificial intelligence (AI) situation awareness can be obtained to feed the SCC actors with enriched knowledge. This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control. Perception, Smart Traffic Control and Driver Modelling are described along with open research challenges and standardization to help introduce advanced driver assistance systems and automated vehicle functionality in traffic. To fully realize the potential of SCC, to create a holistic view on a city level, the availability of data from different stakeholders is need. Further, though AI technologies provide accurate predictions and classifications there is an ambiguity regarding the correctness of their outputs. This can make it difficult for the human operator to trust the system. Today there are no methods that can be used to match function requirements with the level of detail in data annotation in order to train an accurate model. Another challenge related to trust is explainability, while the models have difficulties explaining how they come to a certain conclusions it is difficult for humans to trust it. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

  • 33.
    Englund, Cristofer
    et al.
    RISE Viktoria, Göteborg, Sweden.
    Estrada, John
    eTrans Systems, Fairfax, USA.
    Jaaskelainen, Juhani
    MH Roine Consulting, Helsinki, Finland.
    Meisner, Jim
    Qualcomm Technologies Inc., San Diego, USA.
    Satyavolu, Surya
    Sirab Technologies Inc., Novato, USA.
    Serna, Frank
    Draper Laboratory, 555 Technology Square, Cambridge, USA.
    Sundararajan, Sudharson
    Booz Allen Hamilton Inc., Washington, USA.
    Enabling Technologies for Road Vehicle Automation2017In: Road Vehicle Automation 4 / [ed] Meyer G. & Beiker S., Leiden: VSP , 2017, p. 177-185Chapter in book (Refereed)
    Abstract [en]

    Technology is to a large extent driving the development of road vehicle automation. This Chapter summarizes the general overall trends in the enabling technologies within this field that were discussed during the Enabling technologies for road vehicle automation breakout session at the Automated Vehicle Symposium 2016. With a starting point in six scenarios that have the potential to be deployed at an early stage, five different categories of emerging technologies are described: (a) positioning, localization and mapping (b) algorithms, deep learning techniques, sensor fusion guidance and control (c) hybrid communication (d) sensing and perception and (e) technologies for data ownership and privacy. It is found that reliability and extensive computational power are the two most common challenges within the emerging technologies. Furthermore, cybersecurity binds all technologies together as vehicles will be constantly connected. Connectivity allows both improved local awareness through vehicle-to-vehicle communication and it allows continuous deployment of new software and algorithms that constantly learns new unforeseen objects or scenarios. Finally, while five categories were individually considered, further holistic work to combine them in a systems concept would be the important next step toward implementation. © Springer International Publishing AG 2018

  • 34.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    A hybrid approach to outlier detection in the offset lithographic printing process2005In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 18, no 6, p. 759-768Article in journal (Refereed)
    Abstract [en]

    Artificial neural networks are used to model the offset printing process aiming to develop tools for on-line ink feed control. Inherent in the modelling data are outliers owing to sensor faults, measurement errors and impurity of materials used. It is fundamental to identify outliers in process data in order to avoid using these data points for updating the model. We present a hybrid, the process-model-network-based technique for outlier detection. The outliers can then be removed to improve the process model. Several diagnostic measures are aggregated via a neural network to categorize data points into the outlier and inlier classes. We demonstrate experimentally that a soft fuzzy expert can be configured to label data for training the categorization of neural network.

  • 35.
    Englund, Cristofer
    et al.
    Viktoria Institute, Göteborg, Sweden.
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab). Department of Electrical & Control Equipment, Kaunas University of Technology, Kaunas, Lithuania.
    A novel approach to estimate proximity in a random forest: An exploratory study2012In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 39, no 17, p. 13046-13050Article in journal (Refereed)
    Abstract [en]

    A data proximity matrix is an important information source in random forests (RF) based data mining, including data clustering, visualization, outlier detection, substitution of missing values, and finding mislabeled data samples. A novel approach to estimate proximity is proposed in this work. The approach is based on measuring distance between two terminal nodes in a decision tree. To assess the consistency (quality) of data proximity estimate, we suggest using the proximity matrix as a kernel matrix in a support vector machine (SVM), under the assumption that a matrix of higher quality leads to higher classification accuracy. It is experimentally shown that the proposed approach improves the proximity estimate, especially when RF is made of a small number of trees. It is also demonstrated that, for some tasks, an SVM exploiting the suggested proximity matrix based kernel, outperforms an SVM based on a standard radial basis function kernel and the standard proximity matrix based kernel. © 2012 Elsevier Ltd. All rights reserved.

  • 36.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    A SOM based model combination strategy2005In: Advances in Neural Networks – ISNN 2005 Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part I / [ed] Jun Wang, Xiaofeng Liao and Zhang Yi, Berlin: Springer Berlin/Heidelberg, 2005, p. 461-466Conference paper (Refereed)
    Abstract [en]

    A SOM based model combination strategy, allowing to create adaptive – data dependent – committees, is proposed. Both, models included into a committee and aggregation weights are specific for each input data point analyzed. The possibility to detect outliers is one more characteristic feature of the strategy.

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    FULLTEXT01
  • 37.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    A SOM-based data mining strategy for adaptive modelling of an offset lithographic printing process2007In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 20, no 3, p. 391-400Article in journal (Refereed)
    Abstract [en]

    This paper is concerned with a SOM-based data mining strategy for adaptive modelling of a slowly varying process. The aim is to follow the process in a way that makes a representative up-to-date data set of a reasonable size available at any time. The technique developed allows analysis and filtering of redundant data, detection of the need to update the process models and the core-module of the system itself and creation of process models of adaptive, data-dependent complexity. Experimental investigations performed using data from a slowly varying offset lithographic printing process have shown that the tools developed can follow the process and make the necessary adaptations of the data set and the process models. A low-process modelling error has been obtained by employing data-dependent committees for modelling the process.

  • 38.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Combining traditional and neural-based techniques for ink feed control in a newspaper printing press2007In: Advances in Data Mining: Theoretical Aspects and Applications, Proceedings / [ed] Perner, P., Berlin / Heidelberg: Springer Berlin/Heidelberg, 2007, p. 214-227Conference paper (Refereed)
    Abstract [en]

    A SOM based model combination strategy, allowing to create adaptive – data dependent – committees, is proposed. Both, models included into a committee and aggregation weights are specific for each input data point analyzed. The possibility to detect outliers is one more characteristic feature of the strategy.

  • 39.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Ink feed control in a web-fed offset printing press2008In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 39, no 9-10, p. 919-930Article in journal (Refereed)
    Abstract [en]

    Automatic and robust ink feed control in a web- fed offset printing press is the objective of this work. To achieve this goal an integrating controller and a multiple neural models-based controller are combined. The neural networks-based printing process models are built and updated automatically without any interaction from the user. The multiple models-based controller is superior to the integrating controller as the process is running in the training region of the models. However, the multiple models-based controller may run into generalisation prob- lems if the process starts operating in a new part of the input space. Such situations are automatically detected and the integrating controller temporary takes over the process control. The developed control configuration has success- fully been used to automatically control the ink feed in the web-fed offset printing press according to the target amount of ink. Use of the developed tools led to higher print quality and lower ink and paper waste.

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    fulltext
  • 40.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
    Ink flow control by multiple models in an offset lithographic printing process2008In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, Vol. 55, no 3, p. 592-605Article in journal (Refereed)
    Abstract [en]

    A multiple model-based controller has been developed aiming at controlling the ink flow in the offset lithographic printing process. The control system consists of a model pool of four couples of inverse and direct models. Each couple evaluates a number of probable control signals and the couple, generating the most suitable control signal is used to control the printing press, at that moment. The developed system has been tested at a newspaper printing shop during normal production. The results show that the developed modelling and control system is able to drive the output of the printing press to the desired target levels.

  • 41.
    Habibi, Shiva
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Sprei, Frances
    Chalmers University of Technology, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    Pettersson, Stefan
    RISE Viktoria, Gothenburg, Sweden.
    Voronov, Alexey
    RISE Viktoria, Gothenburg, Sweden.
    Wedlin, Johan
    RISE Viktoria, Gothenburg, Sweden.
    Engdahl, Henrik
    Nimling AB, Askim, Sweden.
    Comparison of free-floating car-sharing services in cities2017Conference paper (Refereed)
    Abstract [en]

    In recent years, free-floating car sharing services (FFCS) have been offered by many organizations as a more flexible option compared to traditional car sharing. FFCS allows users to pick up and return cars anywhere within a specified area of a city. FFCS can provide a high degree of utilization of vehicles and less usage of infrastructure in the form of parking lots and roads and thus has the potential to increase the efficiency of the transport sector. However, there is also a concern that these compete with other efficient modes of transport such as biking and public transport. The aim of this paper is to better understand how, when and where the vehicles are utilized through logged data of the vehicles movements. We have access to data collected on FFCS services in 22 cities in Europe and North America which allows us to compare the usage pattern in different cities and examine whether or not there are similar trends. In this paper, we use the collected data to compare the different cities based on utilization rate, length of trip and time of day that the trip is made. We find that the vehicle utilization rates differ between cities with Madrid and Hamburg having some of the highest utilization levels for the FFCS vehicles. The result form a first step of a better understanding on how these services are being used and can provide valuable input to local policy makers as well as future studies such as simulation models.

  • 42.
    Habibi, Shiva
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Sprei, Frances
    Chalmers University of Technology, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    Voronov, Alex
    RISE Viktoria, Gothenburg, Sweden.
    Pettersson, Stefan
    RISE Viktoria, Gothenburg, Sweden.
    Wedlin, Johan
    RISE Viktoria, Gothenburg, Sweden.
    Engdahl, Henrik
    Nimling, Gothenburg, Sweden.
    Success and usage pattern of free-floating car sharing services in cities2018In: Transportation Research Board (TRB) Meeting 2018, 2018Conference paper (Refereed)
    Abstract [en]

    Free-floating car sharing services (FFCS) have been offered as a more flexible mobility solution than other car sharing services. FFCS users can pick up and return cars anywhere within a specified area in a city.The objective of this paper is to identify similar usage patterns of FFCS in different cities as well as city characteristics that make these services a viable option. The authors have access to real booking data for 32 cities in Europe and North America. Their study shows the share of daily car trips is negatively correlated to the utilization rate of these services. Also, the higher the congestion and the harder finding a parking lot, the lower the utilization rate of these services is in the cities. Moreover, our results suggest that FFCS services do not compete with public transport but are rather used in combination to it. These services are mainly used during midday and evening peak and the trips taken by these services are mainly chained trips.The clustering analysis shows that the trips are grouped into two or three clusters in different cities. The majority of clusters are the inner city clusters which contain a significantly higher number of trips than the clusters around other points of interest such as airports. © Conference Compass and Transportation Research Board

  • 43.
    Habibovic, Azra
    et al.
    Research Institutes of Sweden, RISE, Gothenburg, Sweden.
    Andersson, Jonas
    Research Institutes of Sweden, RISE, Gothenburg, Sweden.
    Malmsten Lundgren, Victor
    Research Institutes of Sweden, RISE, Gothenburg, Sweden.
    Klingegård, Maria
    Research Institutes of Sweden, RISE, Gothenburg, Sweden.
    Englund, Cristofer
    Research Institutes of Sweden, RISE, Gothenburg, Sweden.
    Larsson, Sofia
    Research Institutes of Sweden, RISE, Piteå, Sweden.
    External Vehicle Interfaces for Communication with Other Road Users?2019In: Road Vehicle Automation 5 / [ed] Gereon Meyer & Sven Beiker, Cham: Springer, 2019, p. 91-102Chapter in book (Refereed)
    Abstract [en]

    How to ensure trust and societal acceptance of automated vehicles (AVs) is a widely-discussed topic today. While trust and acceptance could be influenced by a range of factors, one thing is sure: the ability of AVs to safely and smoothly interact with other road users will play a key role. Based on our experiences from a series of studies, this paper elaborates on issues that AVs may face in interactions with other road users and whether external vehicle interfaces could support these interactions. Our overall conclusion is that such interfaces may be beneficial in situations where negotiation is needed. However, these benefits, and potential drawbacks, need to be further explored to create a common language, or standard, for how AVs should communicate with other road users.

  • 44.
    Habibovic, Azra
    et al.
    RISE Viktoria, Gothenburg, Sweden.
    Andersson, Jonas
    RISE Viktoria, Gothenburg, Sweden.
    Malmsten-Lundgren, Victor
    RISE Viktoria, Gothenburg, Sweden.
    Klingegård, Maria
    RISE Viktoria, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    External vehicle interfaces for communication with other road users2017In: Automated Vehicle Symposium, 2017Conference paper (Other academic)
  • 45.
    Henriksson, Jens
    et al.
    Semcon AB, Gothenburg, Sweden.
    Berger, Christian
    University of Gothenburg, Chalmers Institute of Technology, Gothenburg, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden AB, Lund and Gothenburg, Sweden.
    Tornberg, Lars
    Machine Learning and AI Center of Excellence, Volvo Cars, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Research Institutes of Sweden AB, Lund and Gothenburg, Sweden.
    Sathyamoorthy, Sankar
    QRTech AB, Gothenburg, Sweden.
    Ursing, Stig
    Semcon AB, Gothenburg, Sweden.
    Towards Structured Evaluation of Deep Neural Network Supervisors2019In: 2019 IEEE International Conference On Artificial Intelligence Testing (AITest), New York: IEEE, 2019, p. 27-34Conference paper (Refereed)
    Abstract [en]

    Deep Neural Networks (DNN) have improved the quality of several non-safety related products in the past years. However, before DNNs should be deployed to safety-critical applications, their robustness needs to be systematically analyzed. A common challenge for DNNs occurs when input is dissimilar to the training set, which might lead to high confidence predictions despite proper knowledge of the input. Several previous studies have proposed to complement DNNs with a supervisor that detects when inputs are outside the scope of the network. Most of these supervisors, however, are developed and tested for a selected scenario using a specific performance metric. In this work, we emphasize the need to assess and compare the performance of supervisors in a structured way. We present a framework constituted by four datasets organized in six test cases combined with seven evaluation metrics. The test cases provide varying complexity and include data from publicly available sources as well as a novel dataset consisting of images from simulated driving scenarios. The latter we plan to make publicly available. Our framework can be used to support DNN supervisor evaluation, which in turn could be used to motive development, validation, and deployment of DNNs in safety-critical applications. © 2019 IEEE.

  • 46.
    Henriksson, Jens
    et al.
    Semcon AB, Gothenburg, Sweden.
    Berger, Christian
    University of Gothenburg, Gothenburg, Sweden & Chalmers Institute of Technology, Gothenburg, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden AB, Lund and Gothenburg, Sweden.
    Tornberg, Lars
    Machine Learning and AI Center of Excellence, Volvo Cars, Gothenburg, Sweden.
    Sathyamoorthy, Sankar
    QRTech AB, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Research Institutes of Sweden AB, Lund and Gothenburg, Sweden.
    Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks2019In: Proceedings. 45th Euromicro Conference on Software Engineering and Advanced Applications. SEAA 2019: 28 - 30 August 2019 Kallithea, Chalkidiki, Greece / [ed] Staron, M., Capilla, R. & Skavhaug, A., Piscataway: IEEE, 2019Conference paper (Refereed)
    Abstract [en]

    Several areas have been improved with Deep Learning during the past years. For non-safety related products adoption of AI and ML is not an issue, whereas in safety critical applications, robustness of such approaches is still an issue. A common challenge for Deep Neural Networks (DNN) occur when exposed to out-of-distribution samples that are previously unseen, where DNNs can yield high confidence predictions despite no prior knowledge of the input. In this paper we analyse two supervisors on two well-known DNNs with varied setups of training and find that the outlier detection performance improves with the quality of the training procedure. We analyse the performance of the supervisor after each epoch during the training cycle, to investigate supervisor performance as the accuracy converges. Understanding the relationship between training results and supervisor performance is valuable to improve robustness of the model and indicates where more work has to be done to create generalized models for safety critical applications. © 2019 IEEE

  • 47.
    Henriksson, Jens
    et al.
    Semcon Sweden AB, Gothenburg, Sweden.
    Borg, Markus
    RISE SICS, Lund, Sweden.
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    Automotive safety and machine learning: Initial results from a study on how to adapt the ISO 26262 safety standard2018In: 2018 IEEE/ACM 1st International Workshop on Software Engineering for AI in Autonomous Systems (SEFAIAS), New York, NY: ACM Publications, 2018, p. 47-49Conference paper (Refereed)
    Abstract [en]

    Machine learning (ML) applications generate a continuous stream of success stories from various domains. ML enables many novel applications, also in safety-critical contexts. However, the functional safety standards such as ISO 26262 did not evolve to cover ML. We conduct an exploratory study on which parts of ISO 26262 represent the most critical gaps between safety engineering and ML development. While this paper only reports the first steps toward a larger research endeavor, we report three adaptations that are critically needed to allow ISO 26262 compliant engineering, and related suggestions on how to evolve the standard. © 2018 ACM.

  • 48.
    Larsson, Tony
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Jansson, Jonas
    VTI - Swedish National Road and Transport Research Institute, Linköping, Sweden.
    Grante, Christian
    Volvo AB, Göteborg, Sweden.
    Englund, Cristofer
    Viktoria Swedish ICT, Göteborg, Sweden.
    Cooperative partly automated and coordinated vehicles and transports2014Conference paper (Refereed)
    Abstract [en]

    Automation of vehicles and transports is rapidly evolving from a vision to reality due to systems for local situation awareness relying on advanced on-board vehicle sensors and software implemented intelligence. This evolution will be further supported by the capability to communicate and cooperate between vehicles and with important infrastructure to coordinate the traffic for both safe and environmentally efficient transports. To become accepted among vehicle drivers and other citizens this will require understanding of the problems involved and suitable methods to cope with these problems. This paper identifies some of the problems seen and methods needed.

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    fulltext
  • 49.
    Perez-Cerrolaza, Jon
    et al.
    Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), Spain.
    Abella, Jaume
    Barcelona Supercomputing Center (BSC), Spain.
    Borg, Markus
    RISE Research Institutes of Sweden AB, Lund, Sweden.
    Donzella, Carlo
    Exida, Italy.
    Cerquides, Jesús
    Artificial Intelligence Research Institute (IIIA-CSIC), Spain.
    Cazorla, Francisco J.
    BSC and Maspatechnologies S.L., Spain.
    Englund, Cristofer
    RISE Research Institutes of Sweden AB, Gothenburg, Sweden.
    Tauber, Markus
    Research Studios Austria, Austria.
    Nikolakopoulos, George
    Luleå University of Technology, Sweden.
    Flores, Jose Luis
    Ikerlan Technology Research Centre, BRTA, Spain.
    Artificial Intelligence for Safety-Critical Systems in Industrial and Transportation Domains: A Survey2024In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 56, no 7, article id 176Article in journal (Refereed)
  • 50.
    Pettersson, Stefan
    et al.
    RISE Viktoria, Gothenburg, Sweden.
    Bjärsvik, Susanne
    Volvo Car Corporation, Gothenburg, Sweden.
    Englund, Cristofer
    RISE Viktoria, Gothenburg, Sweden.
    Eriksson, Robert
    Volvo Car Corporation, Gothenburg, Sweden.
    Koponen, Veikko
    Volvo Car Corporation, Gothenburg, Sweden.
    Kristiansson, Urban
    RISE Viktoria, Gothenburg, Sweden.
    Milding, Hans-Göran
    Volvo Car Corporation, Gothenburg, Sweden.
    Sundström, Christofer
    RISE Viktoria, Gothenburg, Sweden.
    Wedlin, Johan
    RISE Viktoria, Gothenburg, Sweden.
    Driving style comparison of plug-in hybrids and fossil fueled vehicles based on data collection of fast sampled signals2018Conference paper (Refereed)
12 1 - 50 of 69
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