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  • 1.
    Sidorenko, Galina
    Halmstad University, School of Information Technology.
    Safety of Cooperative Automated Driving: Analysis and Optimization2022Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    New cooperative intelligent transportation system (C-ITS) applications become enabled thanks to advances in communication technologies between vehicles(V2V) and with the infrastructure (V2I). Communicating vehicles share information with each other and cooperate, which results in improved safety, fuel economy, and traffic efficiency. An example of a C-ITS application is platooning, which comprises a string of vehicles that travel together with short inter-vehicle distances (IVDs).

    Any solution related to C-ITS must comply with high safety requirements in order to pass standardization and be commercially deployed. Furthermore, trusted safety levels should be assured even for critical scenarios.

    This thesis studies the conditions that guarantee safety in emergency braking scenarios for heterogeneous platooning, or string-like, formations of vehicles. In such scenarios, the vehicle at the head of the string emergency brakes and all following vehicles have to automatically react in time to avoid rear-end collisions. The reaction time can be significantly decreased with vehicle-to-vehicle (V2V) communication usage since the leader can explicitly inform other platooning members about the critical braking.

    The safety analysis conducted in the thesis yields computationally efficient methods and algorithms for calculating minimum inter-vehicle distances that allow avoiding rear-end collisions with a predefined high guarantee. These IVDs are theoretically obtained for an open-loop and a closed-loop configurations. The former implies that follower drives with a constant velocity until braking starts, whereas in the latter, an adaptive cruise control (ACC) with a constant-distance policy serves as a controller. In addition, further optimization of inter-vehicle distances in the platoon is carried out under an assumption of centralized control. Such an approach allows achieving better fuel consumption and road utilization.

    The performed analytical comparison suggests that our proposed V2V communication based solution is superior to classical automated systems, such as automatic emergency braking system (AEBS), which utilizes only onboard sensors and no communication. Wireless communication, enabling to know the intentions of other vehicles almost immediately, allows for smaller IVDs whilst guaranteeing the same level of safety.

    Overall, the presented thesis highlights the importance of C-ITS and, specifically, V2V in the prevention of rear-end collisions in emergency scenarios. Future work directions include an extension of the obtained results by considering more advanced models of vehicles, environment, and communication settings; and applying the proposed algorithms of safety guaranteeing to other controllers, such as ACC with a constant time headway policy.

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  • 2.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology.
    Fedorov, Aleksei
    Lund University, Lund, Sweden.
    Thunberg, Johan
    Halmstad University, School of Information Technology.
    Vinel, Alexey
    Halmstad University, School of Information Technology. University of Passau, Passau, Germany.
    Towards a Complete Safety Framework for Longitudinal Driving2022In: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, Vol. 7, no 4, p. 809-814Article in journal (Refereed)
    Abstract [en]

    Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework allows calculating minimum safe inter-vehicular distances for arbitrary ego vehicle control policies. We use this framework to enhance the Responsibility-Sensitive Safety (RSS) model and models based on it, which fail to cover situations where the ego vehicle has a higher decelerating capacity than its preceding vehicle. For arbitrary ego vehicle control policies, we show how our framework can be applied by substituting real (possibly computationally intractable) controllers with upper bounding functions. This comprises a general approach for longitudinal safety, where safety guarantees for the upper-bounded system are equivalent to those for the original system but come at the expense of larger inter-vehicular distances. 

  • 3.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Mostowski, Wojciech
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Sjöberg, Jeanette
    Halmstad University, School of Education, Humanities and Social Science, Centrum för lärande, kultur och samhälle (CLKS).
    Cooney, Martin
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    The CAR Approach: Creative Applied Research Experiences for Master’s Students in Autonomous Platooning2021In: 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021, IEEE, 2021, p. 214-221Conference paper (Refereed)
    Abstract [en]

    Autonomous vehicles (AVs) are crucial robotic systems that promise to improve our lives via safe, efficient, and inclusive transport-while posing some new challenges for the education of future researchers in the area, that our current research and education might not be ready to deal with: In particular, we don't know what the AVs of the future will look like, practical learning is restricted due to cost and safety concerns, and a high degree of multidisciplinary knowledge is required. Here, following the broad outline of Active Student Participation theory, we propose a pedagogical approach targeted toward AVs called CAR that combines Creativity theory, Applied demo-oriented learning, and Real world research context. Furthermore, we report on applying the approach to stimulate learning and engagement in a master's course, in which students freely created a demo with 10 small robots running ROS2 and Ubuntu on Raspberry Pis, in connection to an ongoing research project and a real current problem (SafeSmart and COVID-19). The results suggested the feasibility of the CAR approach for enabling learning, as well as mutual benefits for both the students and researchers involved, and indicated some possibilities for future improvement, toward more effective integration of research experiences into second cycle courses. © 2021 IEEE.

  • 4.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology.
    Plöger, Daniel
    Institute of Communication Networks, Hamburg University of Technology, Hamburg, Germany.
    Thunberg, Johan
    Halmstad University, School of Information Technology.
    Vinel, Alexey
    Halmstad University, School of Information Technology.
    Emergency braking with ACC: how much does V2V communication help2022In: IEEE Networking Letters, E-ISSN 2576-3156, Vol. 4, no 3, p. 157-161Article in journal (Refereed)
    Abstract [en]

    This paper provides a safety analysis for emergency braking scenarios involving consecutive vehicles which utilize adaptive cruise control (ACC) with a constant-distance policy together with vehicle-to-vehicle (V2V) communication. We identify analytically, how the minimum safe inter-vehicle distance(IVD) that allows avoiding rear-end collision can be shortened with the use of electronic emergency brake lights and derive the explicit dependency of such IVDs on V2V communication time delay. We further show how these results can be used to compute probabilities of safe braking in the presence of packet losses.

  • 5.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology.
    Thunberg, Johan
    Halmstad University, School of Information Technology.
    Sjöberg, Katrin
    Volvo Autonomous Solutions, Göteborg, Sweden.
    Fedorov, Aleksei
    Lund University, Lund, Sweden.
    Vinel, Alexey
    Safety of Automatic Emergency Braking in Platooning2022In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 71, no 3, p. 2319-2332Article in journal (Refereed)
    Abstract [en]

    A platoon comprises a string of consecutive highly automated vehicles traveling together. Platooning allows for increased road utilization and reduced fuel consumption due to short inter-vehicular distances. Safety in terms of guaranteeing no rear-end collisions is of utmost importance for platooning systems to be deployed in practice. We compare how safely emergency braking can be handled by emerging V2V communications on the one hand and by radar-based measurements of existing AEBS on the other. We show that even under conservative assumptions on the V2V communications, such an approach significantly outperforms AEBS with an ideal radar sensor in terms of allowed inter-vehicle distances and response times. Furthermore, we design two emergency braking strategies for platooning based on V2V communications. The first braking strategy assumes centralized coordination by the leading vehicle and exploits necessary optimal conditions of a constrained optimization problem, whereas the second -- the more conservative solution -- assumes only local information and is distributed in nature. Both strategies are also compared with the AEBS.

  • 6.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Thunberg, Johan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Sjöberg, Katrin
    Scania CV AB, Södertälje, Sweden.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Vehicle-to-Vehicle Communication for Safe and Fuel-Efficient Platooning2020In: 2020 IEEE Intelligent Vehicles Symposium (IV), Piscataway: Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 795-802, article id 9304719Conference paper (Refereed)
    Abstract [en]

    A platoon consists of a string of vehicles traveling close together. Such tight formation allows for increased road throughput and reduced fuel consumption due to decreased air resistance. Furthermore, sensors and control algorithms can be used to provide a high level of automation. In this context, safety – in terms of no rear-end collisions – is a key property that needs to be assured. We investigate how vehicle-to-vehicle communication can be used to reduce inter-vehicle distances while guaranteeing safety in emergency braking scenarios. An optimization-based modeling scheme is presented that, under certain restrictions, provides an analytical calculation of inter-vehicle distances for safe braking. In contrast to earlier simulation-based approaches, the framework allows for computationally efficient solutions with explicit guarantees. Two approaches for computing braking strategies in emergency scenarios are proposed. The first assumes centralized coordination by the leading vehicle and exploits necessary optimal conditions of a constrained optimization problem, whereas the second – the more conservative solution – assumes only local information and is distributed in nature. We illustrate the usefulness of the approaches through several computational simulations. © 2020 IEEE.

  • 7.
    Sidorenko, Galina
    et al.
    Halmstad University, School of Information Technology.
    Thunberg, Johan
    Halmstad University, School of Information Technology.
    Vinel, Alexey
    Halmstad University, School of Information Technology. Karlsruhe Institute of Technology, Karlsruhe, Germany.
    Ethical V2X: Cooperative Driving as the only Ethical Path to Multi-Vehicle Safety2023In: 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall), IEEE, 2023Conference paper (Refereed)
    Abstract [en]

    We argue that an information exchange between vehicles via the vehicular communications is the foundation for ethical driving. In other words - autonomous vehicles must be cooperative to be able to resolve ethical dilemmas in a multi-vehicle scenario. We show this by exploring the minimal setting of a longitudinal driving in a formation of three vehicles. © 2023 IEEE.

  • 8.
    Thunberg, Johan
    et al.
    Halmstad University, School of Information Technology.
    Saeed, Taqwa
    Lund University, Lund, Sweden.
    Sidorenko, Galina
    Halmstad University, School of Information Technology.
    Valle, Felipe
    Halmstad University, School of Information Technology.
    Vinel, Alexey
    Halmstad University, School of Information Technology. Karlsruhe Institute Of Technology, Karlsruhe, Germany.
    Cooperative Vehicles versus Non-Cooperative Traffic Light: Safe and Efficient Passing2023In: Computers, E-ISSN 2073-431X, Vol. 12, no 8, article id 154Article in journal (Refereed)
    Abstract [en]

    Connected and automated vehicles (CAVs) will be a key component of future cooperative intelligent transportation systems (C-ITS). Since the adoption of C-ITS is not foreseen to happen instantly, not all of its elements are going to be connected at the early deployment stages. We consider a scenario where vehicles approaching a traffic light are connected to each other, but the traffic light itself is not cooperative. Information about indented trajectories such as decisions on how and when to accelerate, decelerate and stop, is communicated among the vehicles involved. We provide an optimization-based procedure for efficient and safe passing of traffic lights (or other temporary road blockage) using vehicle-to-vehicle communication (V2V). We locally optimize objectives that promote efficiency such as less deceleration and larger minimum velocity, while maintaining safety in terms of no collisions. The procedure is computationally efficient as it mainly involves a gradient decent algorithm for one single parameter. © 2023 by the authors.

  • 9.
    Thunberg, Johan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Sidorenko, Galina
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Sjöberg, Katrin
    Scania CV AB, Södertälje, Sweden.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). Western Norway University of Applied Sciences, Bergen, Norway.
    Efficiently Bounding the Probabilities of Vehicle Collision at Intelligent Intersections2021In: IEEE Open Journal of Intelligent Transportation Systems, E-ISSN 2687-7813, Vol. 2, p. 47-59Article in journal (Refereed)
    Abstract [en]

    Intelligent intersections have the potential to serve as an integral part of tomorrow’s traffic infrastructure. Wireless communication is key to enabling such technology. We consider a scenario where two flows of vehicles are to traverse an intelligent intersection. We investigate safety in emergency braking scenarios, where one of the vehicles in a flow suddenly decides to emergency brake and emergency braking messages are broadcast to affected vehicles. We provide a framework for computing lower bounds on probabilities for safe braking – collisions between vehicles are to be avoided. If we require that a crash or collision, for example, occurs at most once in a million scenarios, our approach allows for computation of lower bounds on the time-varying (or distance-varying) packet loss probabilities to ensure this. One of the benefits of the proposed framework is that the computational time is reduced; eliminating, for example, the need for time-consuming Monte Carlo simulations.

  • 10.
    Winikoff, Michael
    et al.
    Victoria University of Wellington, Wellington, New Zealand.
    Sidorenko, Galina
    Halmstad University, School of Information Technology.
    Evaluating a Mechanism for Explaining BDI Agent Behaviour2023In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Richland, SC: The International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2023, Vol. 2023-May, p. 2283-2285Conference paper (Refereed)
    Abstract [en]

    We conducted a survey to evaluate a previously proposed mechanism for explaining Belief-Desire-Intention (BDI) agents using folk psychological concepts (belief, desires, and valuings). We also consider the relationship between trust in the specific autonomous system, and general trust in technology. We find that explanations that include valuings are particularly likely to be preferred by the study participants. We also found evidence that single-factor explanations, as used in some previous work, are too short. © 2023 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

  • 11.
    Winikoff, Michael
    et al.
    Victoria University of Wellington, Wellington, New Zealand.
    Sidorenko, Galina
    Halmstad University, School of Information Technology.
    Evaluating a Mechanism for Explaining BDI Agent Behaviour2023In: Proceedings of the 5th International Workshop on EXTRAAMAS 2023 / [ed] Davide Calvaresi; Amro Najjar; Andrea Omicini; Reyhan Aydoğan; Rachele Carli; Giovanni Ciatto; Yazan Mualla; Kary Främling, Heidelberg: Springer, 2023, Vol. 14127, p. 18-37Conference paper (Refereed)
    Abstract [en]

    Explainability of autonomous systems is important to supporting the development of appropriate levels of trust in the system, as well as supporting system predictability. Previous work has proposed an explanation mechanism for Belief-Desire-Intention (BDI) agents that uses folk psychological concepts, specifically beliefs, desires, and valuings. In this paper we evaluate this mechanism by conducting a survey. We consider a number of explanations, and assess to what extent they are considered believable, acceptable, and comprehensible, and which explanations are preferred. We also consider the relationship between trust in the specific autonomous system, and general trust in technology. We find that explanations that include valuings are particularly likely to be preferred by the study participants, whereas those explanations that include links are least likely to be preferred. We also found evidence that single-factor explanations, as used in some previous work, are too short. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

  • 12.
    Winikoff, Michael
    et al.
    Victoria University of Wellington, Wellington, New Zealand; University of Otago, Dunedin, New Zealand.
    Sidorenko, Galina
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS). University of Otago, Dunedin, New Zealand.
    Dignum, Virginia
    Umeå University, Umeå, Sweden.
    Dignum, Frank
    Umeå University, Umeå, Sweden; Utrecht University, Utrecht, Netherlands.
    Why bad coffee? Explaining BDI agent behaviour with valuings2021In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 300, article id 103554Article in journal (Refereed)
    Abstract [en]

    An important issue in deploying an autonomous system is how to enable human users and stakeholders to develop an appropriate level of trust in the system. It has been argued that a crucial mechanism to enable appropriate trust is the ability of a system to explain its behaviour. Obviously, such explanations need to be comprehensible to humans. Due to the perceived similarity in functioning between humans and autonomous systems, we argue that it makes sense to build on the results of extensive research in social sciences that explores how humans explain their behaviour. Using similar concepts for explanation is argued to help with comprehensibility, since the concepts are familiar. Following work in the social sciences, we propose the use of a folk-psychological model that utilises beliefs, desires, and “valuings”. We propose a formal framework for constructing explanations of the behaviour of an autonomous system, present an (implemented) algorithm for giving explanations, and present evaluation results. © 2021 Elsevier B.V.

  • 13.
    Winikoff, Michael
    et al.
    Victoria University Of Wellington, Wellington, New Zealand.
    Sidorenko, Galina
    Halmstad University, School of Information Technology.
    Dignum, Virginia
    Umeå University, Umea, Sweden.
    Dignum, Frank
    Umeå University, Umea, Sweden.
    Why Bad Coffee? Explaining BDI Agent Behaviour with Valuings (Extended Abstract)2022In: IJCAI International Joint Conference on Artificial Intelligence, Palo Alto, CA: AAAI Press, 2022, p. 5782-5786Conference paper (Refereed)
    Abstract [en]

    An important issue in deploying an autonomous system is how to enable human users and stakeholders to develop an appropriate level of trust in the system. It has been argued that a crucial mechanism to enable appropriate trust is the ability of a system to explain its behaviour. Obviously, such explanations need to be comprehensible to humans. Due to the perceived similarity in functioning between humans and autonomous systems, we argue that it makes sense to build on the results of extensive research in social sciences that explores how humans explain their behaviour. Using similar concepts for explanation is argued to help with comprehensibility, since the concepts are familiar. Following work in the social sciences, we propose the use of a folk-psychological model that utilises beliefs, desires, and “valuings”. We propose a formal framework for constructing explanations of the behaviour of an autonomous system, present an (implemented) algorithm for giving explanations, and present evaluation results. © 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.

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