Towards a Complete Safety Framework for Longitudinal Driving

Сидоренко, Г. А.; Fedorov, Aleksei; Thunberg, Johan; Vinel, Alexey

doi:10.1109/tiv.2022.3209910

Cited by 14 publications

(6 citation statements)

References 15 publications

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“…These principles offer more granular details about the underlying movement processes of the involved vehicles [39]. In these safety principles, regulations regarding the inter-vehicle distance [40] or gaps have been introduced. In recent years, the formulation of safety rules for autonomous vehicles has been formalized as a verification problem, following standard practices in the realm of software engineering [41].…”

Section: Notations Listmentioning

confidence: 99%

Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy

2024

IEEE Open J. Intell. Transp. Syst.

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The safety of autonomous vehicles (AVs) is a critical consideration for their widespread adoption. Responsibility sensitive safety (RSS) is proposed to serve as a model checking tool for AV safety. However, RSS alone cannot guarantee safety when they are mixed with human-driven vehicles (HDVs). These HDVs may disregard safety rules, creating dilemmas for AVs where they must choose between crashing into their leader or crashing into their follower. This manuscript defines this dilemma regarding the longitudinal driving and extends it to platooning scenarios with an arbitrary number of vehicles, referred to as polylemma. In polylemma, a violation of safety rules by one vehicle inevitably results in at least one crash between neighboring vehicles. To avoid the polylemmascenario, the manuscript proposes a human error-tolerant (HET) driving strategy, wherein AVs maintain an additional gap and prepare for moderate deceleration to account for potential errors by human drivers. The manuscript derives the risk reduction and capacity variation resulting from the implementation of this strategy at a given market penetration rate (MPR) using real world trajectory data. The analysis indicates that a 50% MPR would reduce risks due to human error by 80%, with a decrease in capacity which vary different for background traffic flow speed.

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Section: Notations Listmentioning

confidence: 99%

Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy

2024

IEEE Open J. Intell. Transp. Syst.

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“…Automatic Preventive Braking (APB) has been developed for collision avoidance in car-following [9], [10]. In the APB system, constraints on the jerk profile define a safe longitudinal distance, making the braking mild and comfortable [19], [20]. However, real data-based testing shows that APB might have fluctuations in the braking process frequently, which will corrupt the braking distance and increase the risk of collisions [8].…”

Section: B Related Workmentioning

confidence: 99%

Robust Optimal Braking Policy for Avoiding Collision With Front Bicycle

Shen,

Zhang,

Zhang

et al. 2023

IEEE Open J. Intell. Transp. Syst.

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Bicycles are frequently involved in traffic collisions with vehicles, particularly when sudden changes in direction occur. This paper presents a robust risk-predictive braking policy to ensure collision avoidance in all possible crossing behaviors of a bicycle. The policy controls the vehicle to follow an upper limit of the safe speed before the bicycle changes direction, ensuring that the vehicle can stop in time by the advanced emergency braking system before a collision occurs in any situation. The upper limit of the safe speed is the solution of an intractable robust optimization problem. Therefore, a scenario approach is adapted to develop a tractable approximate problem for the original robust optimization problem. The feasibility and optimality of the problem reduction are theoretically proved. A bisection method-based fast algorithm is designed to solve the approximate problem of the original robust optimization problem, making it applicable in practical scenarios. The convergence of the algorithm is also proven. The effectiveness of the proposed method is validated through hardware-in-the-loop simulations using CarMaker.

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“…The multi-vehicle scenario of longitudinal driving [15] in a string formation, referred to as platooning [16,17], has been thoroughly investigated from a control-theoretic perspective in terms of concepts such as string stability [18], model predictive control (MPC) [11], and spacing policy [19,20].…”

Section: Related Workmentioning

confidence: 99%

“…Similar to human-driven vehicles, it is natural for a CAV to experience temporary braking and stopping for various reasons including, but not limited to, emergency braking [15,[21][22][23], passing through signalized and nonsignalized intersections [24], stop-and-go waves [25] and pedestrian crossings.…”

Section: Related Workmentioning

confidence: 99%

Cooperative Vehicles versus Non-Cooperative Traffic Light: Safe and Efficient Passing

Thunberg,

Saeed,

Sidorenko

et al. 2023

Computers

Self Cite

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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.

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Towards a Complete Safety Framework for Longitudinal Driving

Cited by 14 publications

References 15 publications

Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy

Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy

Robust Optimal Braking Policy for Avoiding Collision With Front Bicycle

Cooperative Vehicles versus Non-Cooperative Traffic Light: Safe and Efficient Passing

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