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Aramrattana, MaytheewatORCID iD iconorcid.org/0000-0003-4951-5315
Publikasjoner (10 av 18) Visa alla publikasjoner
Aramrattana, M., Larsson, T., Englund, C., Jansson, J. & Nåbo, A. (2022). A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations. IEEE transactions on intelligent transportation systems (Print), 23(4), 3790-3796
Åpne denne publikasjonen i ny fane eller vindu >>A Simulation Study on Effects of Platooning Gaps on Drivers of Conventional Vehicles in Highway Merging Situations
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2022 (engelsk)Inngår i: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 23, nr 4, s. 3790-3796Artikkel i tidsskrift (Fagfellevurdert) Published
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.

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE, 2022
Emneord
Merging, Vehicles, Roads, Automobiles, Vehicular ad hoc networks, Meters, Safety
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-43769 (URN)10.1109/TITS.2020.3040085 (DOI)000776187400074 ()2-s2.0-85098774184 (Scopus ID)
Forskningsfinansiär
Vinnova, 2015-04881
Merknad

Funding: Swedish Government Agency for Innovation Systems VINNOVA through the NGEA step 2; Vehicle and Traffic Safety Centre at Chalmers SAFER

Tilgjengelig fra: 2021-01-11 Laget: 2021-01-11 Sist oppdatert: 2022-05-02bibliografisk kontrollert
Amador Molina, O., Aramrattana, M. & Vinel, A. (2022). A Survey on Remote Operation of Road Vehicles. IEEE Access, 10, 130135-130154
Åpne denne publikasjonen i ny fane eller vindu >>A Survey on Remote Operation of Road Vehicles
2022 (engelsk)Inngår i: IEEE Access, E-ISSN 2169-3536, Vol. 10, s. 130135-130154Artikkel, forskningsoversikt (Fagfellevurdert) Published
Abstract [en]

In recent years, the use of remote operation has been proposed as a bridge towards driverless mobility by providing human assistance remotely when an automated driving system finds a situation that is ambiguous and requires input from a remote operator. The remote operation of road vehicles has also been proposed as a way to enable drivers to operate vehicles from safer and more comfortable locations. While commercial solutions for remote operation exist, remaining challenges are being tackled by the research community, who is continuously testing and validating the feasibility of deploying remote operation of road vehicles on public roads. These tests range from the technological scope to social aspects such as acceptability and usability that affect human performance. This survey presents a compilation of works that approach the remote operation of road vehicles. We start by describing the basic architecture of remote operation systems and classify their modes of operation depending on the level of human intervention. We use this classification to organize and present recent and relevant work on the field from industry and academia. Finally, we identify the challenges in the deployment of remote operation systems in the technological, regulatory, and commercial scopes.

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE, 2022
Emneord
5G, automated mobility, connected vehicle, remote driving, teleoperation
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-48981 (URN)10.1109/access.2022.3229168 (DOI)000902004300001 ()2-s2.0-85144797263 (Scopus ID)
Prosjekter
Safety of Connected Intelligent Vehicles in Smart Cities–SafeSmart
Forskningsfinansiär
Vinnova, 2020-02945Vinnova, 2019-03068Knowledge FoundationELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Tilgjengelig fra: 2022-12-21 Laget: 2022-12-21 Sist oppdatert: 2023-02-01bibliografisk kontrollert
Aramrattana, M., Larsson, T., Englund, C., Jansson, J. & Nåbo, A. (2020). A Novel Risk Indicator for Cut-In Situations. In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC): . Paper presented at The 23rd IEEE International Conference on Intelligent Transportation Systems, Virtual Conference, September 20 – 23, 2020. Piscataway, NJ: IEEE, Article ID 9294315.
Åpne denne publikasjonen i ny fane eller vindu >>A Novel Risk Indicator for Cut-In Situations
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2020 (engelsk)Inngår i: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), Piscataway, NJ: IEEE, 2020, artikkel-id 9294315Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE, 2020
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-43770 (URN)10.1109/ITSC45102.2020.9294315 (DOI)000682770700139 ()2-s2.0-85099646310 (Scopus ID)978-1-7281-4149-7 (ISBN)978-1-7281-4150-3 (ISBN)
Konferanse
The 23rd IEEE International Conference on Intelligent Transportation Systems, Virtual Conference, September 20 – 23, 2020
Forskningsfinansiär
Vinnova, 2015-04881
Merknad

Funding: Swedish Government Agency for Innovation Systems VINNOVA through the NGEA step 2; Vehicle and Traffic Safety Centre at Chalmers (SAFER)

Tilgjengelig fra: 2021-01-11 Laget: 2021-01-11 Sist oppdatert: 2023-10-05bibliografisk kontrollert
Aramrattana, M., Larsson, T., Jansson, J. & Nåbo, A. (2019). A simulation framework for cooperative intelligent transport systems testing and evaluation. Transportation Research Part F: Traffic Psychology and Behaviour, 61, 268-280
Åpne denne publikasjonen i ny fane eller vindu >>A simulation framework for cooperative intelligent transport systems testing and evaluation
2019 (engelsk)Inngår i: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 61, s. 268-280Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Connected and automated driving in the context of cooperative intelligent transport systems (C-ITS) is an emerging area in transport systems research. Interaction and cooperation between actors in transport systems are now enabled by the connectivity by means of vehicle-to-vehicle and vehicle-to-infrastructure (V2X) communication. To ensure the goals of C-ITS, which are safer and more efficient transport systems, testing and evaluation are required before deployment of C-ITS applications. Therefore, this paper presents a simulation framework—consisting of driving-, traffic-, and network-simulators—for testing and evaluation of C-ITS applications. Examples of cooperative adaptive cruise control (CACC) applications are presented, and are used as test cases for the simulation framework as well as to elaborate on potential use cases of it. Challenges from combining the simulators into one framework, and limitations are reported and discussed. Finally, the paper concludes with future development directions, and applications of the simulation framework in testing and evaluation of C-ITS. © 2017 Elsevier Ltd. All rights reserved.

sted, utgiver, år, opplag, sider
Kidlington: Pergamon Press, 2019
Emneord
C-ITS, driving simulator, traffic simulator, network simulator, platooning
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-34870 (URN)10.1016/j.trf.2017.08.004 (DOI)000464489700024 ()2-s2.0-85028624553 (Scopus ID)
Prosjekter
Vehicle ICT Innovation Methodology (VICTIg)
Forskningsfinansiär
Knowledge Foundation
Merknad

This work is supported by SAFER – Vehicle and Traffic Safety Centre at Chalmers, as a part of Vehicle ICT Innovation Methodology (VICTIg) project.

Tilgjengelig fra: 2017-09-04 Laget: 2017-09-04 Sist oppdatert: 2021-05-17bibliografisk kontrollert
David, J., Mostowski, W., Aramrattana, M., Fan, Y., Varshosaz, M., Karlsson, P., . . . Andersson, E. (2019). Design and Development of a Hexacopter for the Search and Rescue of a Lost Drone. In: : . Paper presented at IROS 2019 - Workshop on Challenges in Vision-based Drones Navigation, Macau, China, November 8, 2019.
Åpne denne publikasjonen i ny fane eller vindu >>Design and Development of a Hexacopter for the Search and Rescue of a Lost Drone
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2019 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Search and rescue with an autonomous robot is an attractive and challenging task within the research community. This paper presents the development of an autonomous hexacopter that is designed for retrieving a lost object, like a drone, from a vast-open space, like a desert area. Navigating its path with a proposed coverage path planning strategy, the hexacopter can efficiently search for a lost target and locate it using an image-based object detection algorithm. Moreover, after the target is located, our hexacopter can grasp it with a customised gripper and transport it back to a destined location. It is also capable of avoiding static obstacles and dynamic objects. The proposed system was realised in simulations before implementing it in a real hardware setup, i.e. assembly of the drone, crafting of the gripper, software implementation and testing under real-world scenarios. The designed hexacopter won the best UAV design award at the CPS-VO 2018 Competition held in Arizona, USA.

Emneord
drones, UAV, competition, search and rescue
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-40830 (URN)
Konferanse
IROS 2019 - Workshop on Challenges in Vision-based Drones Navigation, Macau, China, November 8, 2019
Tilgjengelig fra: 2019-11-04 Laget: 2019-11-04 Sist oppdatert: 2021-05-17bibliografisk kontrollert
Aramrattana, M. (2018). A Simulation-Based Safety Analysis of CACC-Enabled Highway Platooning. (Doctoral dissertation). Halmstad: Halmstad University Press
Åpne denne publikasjonen i ny fane eller vindu >>A Simulation-Based Safety Analysis of CACC-Enabled Highway Platooning
2018 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Cooperative Intelligent Transport Systems (C-ITS) enable actors in the transport systems to interact and collaborate by exchanging information via wireless communication networks. There are several challenges to overcome before they can be implemented and deployed on public roads. Among the most important challenges are testing and evaluation in order to ensure the safety of C-ITS applications.

This thesis focuses on testing and evaluation of C-ITS applications with regard to their safety using simulation. The main focus is on one C-ITS application, namely platooning, that is enabled by the Cooperative Adaptive Cruise Control (CACC) function. Therefore, this thesis considers two main topics: i) what should be modelled and simulated for testing and evaluation of C-ITS applications? and ii) how should CACC functions be evaluated in order to ensure safety?

When C-ITS applications are deployed, we can expect traffic situations which consist of vehicles with different capabilities, in terms of automation and connectivity. We propose that involving human drivers in testing and evaluation is important in such mixed traffic situations. Considering important aspects of C-ITS including human drivers, we propose a simulation framework, which combines driving-, network-, and traffic simulators. The simulation framework has been validated by demonstrating several use cases in the scope of platooning. In particular, it is used to demonstrate and analyse the safety of platooning applications in cut-in situations, where a vehicle driven by a human driver cuts in between vehicles in platoon. To assess the situations, time-to-collision (TTC) and its extensions are used as safety indicators in the analyses.

The simulation framework permits future C-ITS research in other fields such as human factors by involving human drivers in a C-ITS context. Results from the safety analyses show that cut-in situations are not always hazardous, and two factors that are the most highly correlated to the collisions are relative speed and distance between vehicles at the moment of cutting in. Moreover, we suggest that to solely rely on CACC functions is not sufficient to handle cut-in situations. Therefore, guidelines and standards are required to address these situations properly.

sted, utgiver, år, opplag, sider
Halmstad: Halmstad University Press, 2018. s. 103
Serie
Halmstad University Dissertations ; 51
Emneord
simulation, driving simulator, traffic simulator, network simulator, C-ITS, cooperative intelligent transport systems, platooning
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-38390 (URN)978-91-88749-07-9 (ISBN)978-91-88749-08-6 (ISBN)
Disputas
2018-12-12, Wigforssalen, Hus J (Visionen), Halmstad University, Kristian IV:s väg 3, Halmstad, 10:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2018-11-26 Laget: 2018-11-20 Sist oppdatert: 2021-05-17bibliografisk kontrollert
Aramrattana, M., Patel, R. H., Englund, C., Härri, J., Jansson, J. & Bonnet, C. (2018). Evaluating Model Mismatch Impacting CACC Controllers in Mixed. In: 2018 IEEE Intelligent Vehicles Symposium (IV): . Paper presented at 2018 IEEE Intelligent Vehicles Symposium, IV 2018, Changshu, China, 26-30 September, 2018 (pp. 1867-1872). IEEE
Åpne denne publikasjonen i ny fane eller vindu >>Evaluating Model Mismatch Impacting CACC Controllers in Mixed
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2018 (engelsk)Inngår i: 2018 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2018, s. 1867-1872Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
IEEE, 2018
Emneord
Behavioral research, Intelligent vehicle highway systems, Model predictive control, Predictive control systems, Vehicles, Automated vehicles, Control inputs, Driving simulator, Evaluating models, Human behaviors, Market penetration, Proof of concept, Transportation system, Controllers
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-38740 (URN)10.1109/IVS.2018.8500479 (DOI)2-s2.0-85056772722 (Scopus ID)978-1-5386-4452-2 (ISBN)978-1-5386-4451-5 (ISBN)978-1-5386-4453-9 (ISBN)
Konferanse
2018 IEEE Intelligent Vehicles Symposium, IV 2018, Changshu, China, 26-30 September, 2018
Merknad

Funding: Raj Haresh Patel is a recipient of a PhD Grant from the Graduate School of the University Pierre Marie Curie (UPMC), Paris. EURECOM acknowledges the support of its industrial members, namely BMW Group, IABG, Monaco Telecom, Orange, SAP and Symantec.

Tilgjengelig fra: 2019-01-10 Laget: 2019-01-10 Sist oppdatert: 2021-05-17bibliografisk kontrollert
Aramrattana, M., Patel, R. H., Englund, C., Harri, J., Jansson, J. & Bonnet, C. (2018). Evaluating Model Mismatch Impacting CACC Controllers in Mixed Traffic using a Driving Simulator. In: 2018 IEEE Intelligent Vehicles Symposium (IV): . Paper presented at IEEE Intelligent Vehicles Symposium (IV), Changshu, Suzhou, China, June 26-30, 2018 (pp. 1867-1872). New York, NY: IEEE
Åpne denne publikasjonen i ny fane eller vindu >>Evaluating Model Mismatch Impacting CACC Controllers in Mixed Traffic using a Driving Simulator
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2018 (engelsk)Inngår i: 2018 IEEE Intelligent Vehicles Symposium (IV), New York, NY: IEEE, 2018, s. 1867-1872Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
New York, NY: IEEE, 2018
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-52252 (URN)10.1109/IVS.2018.8500479 (DOI)000719424500291 ()2-s2.0-85056772722 (Scopus ID)978-1-5386-4452-2 (ISBN)978-1-5386-4451-5 (ISBN)978-1-5386-4453-9 (ISBN)
Konferanse
IEEE Intelligent Vehicles Symposium (IV), Changshu, Suzhou, China, June 26-30, 2018
Merknad

Funsing: Raj Haresh Patel is a recipient of a PhD Grant from the Graduate School of the University Pierre Marie Curie (UPMC), Paris. EURECOM acknowledges the support of its industrial members, namely BMW Group, IABG, Monaco Telecom, Orange, SAP and Symantec.

Tilgjengelig fra: 2023-12-21 Laget: 2023-12-21 Sist oppdatert: 2023-12-21bibliografisk kontrollert
Aramrattana, M., Detournay, J., Englund, C., Frimodig, V., Jansson, O. U., Larsson, T., . . . Shahanoor, G. (2018). Team Halmstad Approach to Cooperative Driving in the Grand Cooperative Driving Challenge 2016. IEEE transactions on intelligent transportation systems (Print), 19(4), 1248-1261
Åpne denne publikasjonen i ny fane eller vindu >>Team Halmstad Approach to Cooperative Driving in the Grand Cooperative Driving Challenge 2016
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2018 (engelsk)Inngår i: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 19, nr 4, s. 1248-1261Artikkel i tidsskrift (Fagfellevurdert) Published
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.

sted, utgiver, år, opplag, sider
Piscataway, N.J.: Institute of Electrical and Electronics Engineers Inc., 2018
Emneord
Adaptive cruise control, Cruise control, Decision making, Autonomous driving, Cooperative adaptive cruise control, Cooperative driving, GCDC 2016, IEEE 802.11p, platooning, Cooperative communication
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-38712 (URN)10.1109/TITS.2017.2752359 (DOI)000429017300023 ()2-s2.0-85041535321 (Scopus ID)
Tilgjengelig fra: 2019-01-08 Laget: 2019-01-08 Sist oppdatert: 2021-05-17bibliografisk kontrollert
Aramrattana, M., Englund, C., Jansson, J., Larsson, T. & Nåbo, A. (2017). Safety Analysis of Cooperative Adaptive Cruise Control in Vehicle Cut-in Situations. In: Proceedings of 2017 4th International Symposium on Future Active Safety Technology towards Zero-Traffic-Accidents (FAST-zero): . Paper presented at 4th International Symposium on Future Active Safety Technology towards Zero-Traffic-Accidents (FAST-Zero’17), Nara, Japan, 18-22 September, 2017. Society of Automotive Engineers of Japan, Article ID 20174621.
Åpne denne publikasjonen i ny fane eller vindu >>Safety Analysis of Cooperative Adaptive Cruise Control in Vehicle Cut-in Situations
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2017 (engelsk)Inngår i: Proceedings of 2017 4th International Symposium on Future Active Safety Technology towards Zero-Traffic-Accidents (FAST-zero), Society of Automotive Engineers of Japan , 2017, artikkel-id 20174621Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Society of Automotive Engineers of Japan, 2017
Emneord
cooperative adaptive cruise control, modelling and simulations
HSV kategori
Identifikatorer
urn:nbn:se:hh:diva-35681 (URN)
Konferanse
4th International Symposium on Future Active Safety Technology towards Zero-Traffic-Accidents (FAST-Zero’17), Nara, Japan, 18-22 September, 2017
Forskningsfinansiär
Knowledge Foundation
Tilgjengelig fra: 2017-12-01 Laget: 2017-12-01 Sist oppdatert: 2021-05-17bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0003-4951-5315