Game theoretic approach for predictive lane-changing and car-following control

Wang, Meng; Hoogendoorn, Serge P.; Daamen, Winnie; Arem, Bart van; Happee, Riender

doi:10.1016/j.trc.2015.07.009

Cited by 281 publications

(121 citation statements)

References 37 publications

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“…Several other studies suggested that greater levels of safety could be secured by advanced longitudinal or lateral multiobjective optimization controllers (see e.g. Gong, Shen, & Du, 2016;Khondaker & Kattan, 2015;Wang, Hoogendoorn, Daamen, van Arem, & Happee, 2015), intersection controllers (see e.g. Dresner & Stone, 2008) and path planning algorithms (see e.g.…”

Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

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725

383

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KEYWORDSautomated driving; first, second, and third order impacts; policy and societal implications; ripple effect ABSTRACTIn this paper, the potential effects of automated driving that are relevant to policy and society are explored, findings discussed in literature about those effects are reviewed and areas for future research are identified. The structure of our review is based on the ripple effect concept, which represents the implications of automated vehicles at three different stages: first-order (traffic, travel cost, and travel choices), second-order (vehicle ownership and sharing, location choices and land use, and transport infrastructure), and third-order (energy consumption, air pollution, safety, social equity, economy, and public health). Our review shows that first-order impacts on road capacity, fuel efficiency, emissions, and accidents risk are expected to be beneficial. The magnitude of these benefits will likely increase with the level of automation and cooperation and with the penetration rate of these systems. The synergistic effects between vehicle automation, sharing, and electrification can multiply these benefits. However, studies confirm that automated vehicles can induce additional travel demand because of more and longer vehicle trips. Potential land use changes have not been included in these estimations about excessive travel demand. Other third-order benefits on safety, economy, public health and social equity still remain unclear. Therefore, the balance between the short-term benefits and long-term impacts of vehicle automation remains an open question.

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Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

Self Cite

725

383

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“…A majority of existing studies have focused on designing AVs' driving algorithms in various scenarios to ensure traffic efficiency, safety, or ethics (Reece and Shafer, 1993;Yoo and Langari, 2013;Kim and Langari, 2014;Yu et al, 2018;Wang et al, 2015;Talebpour et al, 2015;Wang et al, 2016;Gong et al, 2016;Gong and Du, 2018;Li et al, 2018;Huang et al, 2019a,c,b;Smith, 2019), but ignoring human drivers' behavioral adaptation to AVs as humans are exposed to more and more traffic encounters with AVs. Human drivers may have a weaker incentive to exercise "due care" when faced with AVs.…”

Section: Literature Reviewmentioning

confidence: 99%

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach

Talley

2019

SSRN Journal

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Autonomous vehicles (AVs) are inevitably entering our lives with potential benefits for improved traffic safety, mobility, and accessibility. However, AVs' benefits also introduce a serious potential challenge, in the form of complex interactions with human-driven vehicles (HVs). The emergence of AVs introduces uncertainty in the behavior of human actors and in the impact of the AV manufacturer on autonomous driving design. This paper thus aims to investigate how AVs affect road safety and to design socially optimal liability rules in comparative negligence for AVs and human drivers. A unified game is developed, including a Nash game between human drivers, a Stackelberg game between the AV manufacturer and HVs, and a Stackelberg game between the law maker and other users. We also establish the existence and uniqueness of the equilibrium of the game. The game is then simulated with numerical examples to investigate the emergence of human drivers' moral hazard, the AV manufacturer's role in traffic safety, and the law maker's role in liability design. Our findings demonstrate that human drivers could develop moral hazard if they perceive their road environment has become safer and an optimal liability rule design is crucial to improve social welfare with advanced transportation technologies. More generally, the game-theoretic model developed in this paper provides an analytical tool to assist policy-makers in AV policymaking and hopefully mitigate uncertainty in the existing regulation landscape about AV technologies.

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“…Advances in next generation transportation system technologies and the emergence of Connected and Automated Vehicles (CAVs), also known as "autonomous vehicles", have the potential to drastically improve a transportation network's performance in terms of safety, comfort, congestion reduction and energy efficiency. In highway driving, an overview of automated intelligent vehicle-highway systems was provided in [1] with more recent developments mostly focusing on autonomous car-following control [2], [3], [4]. Automating a lane change maneuver remains a challenging problem which has attracted increasing attention in recent years [5], [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Time and Energy-Optimal Lane Change Maneuvers for Cooperating Connected and Automated Vehicles^⋆

Chen

Cassandras

Tahmasbi-Sarvestani

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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We derive optimal control policies for a Connected and Automated Vehicle (CAV) cooperating with neighboring CAVs to implement a highway lane change maneuver. We optimize the maneuver time and subsequently minimize the associated energy consumption of all cooperating vehicles in this maneuver. We prove structural properties of the optimal policies which simplify the solution derivations and lead to analytical optimal control expressions. The solutions, when they exist, are guaranteed to satisfy safety constraints for all vehicles involved in the maneuver. Simulation results show the effectiveness of the proposed solution and significant performance improvements compared to maneuvers performed by human-driven vehicles.

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Game theoretic approach for predictive lane-changing and car-following control

Cited by 281 publications

References 37 publications

Policy and society related implications of automated driving: A review of literature and directions for future research

Policy and society related implications of automated driving: A review of literature and directions for future research

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach

Time and Energy-Optimal Lane Change Maneuvers for Cooperating Connected and Automated Vehicles^⋆

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Game theoretic approach for predictive lane-changing and car-following control

Cited by 281 publications

References 37 publications

Policy and society related implications of automated driving: A review of literature and directions for future research

Policy and society related implications of automated driving: A review of literature and directions for future research

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach

Time and Energy-Optimal Lane Change Maneuvers for Cooperating Connected and Automated Vehicles⋆

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Time and Energy-Optimal Lane Change Maneuvers for Cooperating Connected and Automated Vehicles^⋆