Connected and autonomous vehicle
Road vehicles are becoming increasingly automated. Sensors and Advanced Driver Assistance Systems (ADAS), such as Adaptive Cruise Control (ACC) and Automatic Lane Keeping and Changing (ALK), are common features of modern cars, while Connected and Automated Vehicles (CAV) are currently being actively developed by automotive companies and suppliers, research centres, universities and standardisation organisations. One of the main arguments for driving automation is safety. Indeed, most accidents are due to human error, which could be avoided with safe automated systems. However, automated systems can also lead to new types of accidents.
The architecture of automated driving systems is multidisciplinary and mission-based. It consists of three main components:
1. The perception phase, when the system measures the surrounding thanks to sensors and cameras and interpret the driving situation.
2. The motion planning phase, when the system determines for the driving situation a safe, comfortable, and performant reference trajectory to follow.
3. The actuation phase for the longitudinal and lateral control of the vehicle to the reference trajectory.
A quantitative functional safety analysis of the automated driving systems is necessary to evaluate and demonstrate their reliability and safety. However, automated driving is a dynamic process with complex functional architecture, and the driving situations are extremely diverse. Classical static approaches from ISO Norm 26262 consist of exhaustive analysis of all driving situations and vehicle items with corresponding risk assessment. Such a task is not feasible for automated driving, especially for urban traffic at levels 3, 4, or 5 of automation without supervision. Important work is currently underway to develop specific tools and methods for the safety of automated vehicles, capable of taking into account the various dynamic aspects of driving situations as in ISO norm 21448.
- 2023
- B. Khelfa, I. Ba and A. Tordeux, "Predicting highway lane-changing maneuvers: A benchmark analysis of machine and ensemble learning algorithms", Physica A: Statistical Mechanics and its Applications, vol. 612, pp. 128471, 2023.
- P. Khound, P. Will, A. Tordeux and F. Gronwald, "The Over-Damped String Stability Condition for a Platooning System", System Theory, Control and Computing Journal, vol. 3, no. 1, pp. 12-19, 2023.
- P. Khound, P. Will, A. Tordeux and F. Gronwald, "Unified framework for over-damped string stable adaptive cruise control systems", Transportation Research Part C: Emerging Technologies, vol. 148, pp. 104039, 2023. Elsevier.
- 2022
- B. Khelfa, R. Korbmacher, A. Schadschneider and A. Tordeux, "Heterogeneity-induced lane and band formation in self-driven particle systems", Scientific Reports, vol. 12, no. 1, pp. 1-11, 2022. Nature Publishing Group.
- P. Khound, P. Will, A. Tordeux and F. Gronwald, "The importance of the over-damped string stability criterion for a platooning control system" in 2022 26th IEEE International Conference on System Theory, Control and Computing (ICSTCC), 2022, pp. 1-6.
- 2021
- I. Ba and A. Tordeux, "Comparing Macroscopic First Order Models of Regulated and Unregulated Road Traffic Intersections" in Proceeding of 30th European Safety and Reliability (ESREL) Conference, 2021.
- B. Khelfa and A. Tordeux, "Comparing rule-based and data-based approaches for lane-change prediction" in Proceeding of 30th European Safety and Reliability (ESREL) Conference, 2021.
- P. Khound, P. Will, A. Tordeux and F. Gronwald, "Extending the adaptive time gap car-following model to enhance local and string stability for adaptive cruise control systems", Journal of Intelligent Transportation Systems, vol. 27, pp. 36-56, 2021. Taylor & Francis.
- B. Khelfa and A. Tordeux, "Lane-changing prediction in highway: Comparing empirically rule-based model MOBIL and a naive Bayes algorithm" in 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, pp. 1598-1603.
- B. Khelfa and A. Tordeux, "Understanding and Predicting Overtaking and Fold-Down Lane-Changing Maneuvers on European Highways Using Naturalistic Road User Data" in 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 2021, pp. 168-173.
- 2020
- A. Tordeux and B. Khelfa, "Dynamic Safety Analysis of Longitudinal Motion Planning for Autonomous Vehicles" in Proceeding of 29th European Safety and Reliability (ESREL) Conference, 2020.
- B. Khelfa and A. Tordeux, "Extended Longitudinal Motion Planning for Autonomous Vehicles on Highways Including Lane Changing Prediction" in Traffic and Granular Flow 2019, Springer, 2020, pp. 495-503.
- A. Tordeux, J. Lebacque and S. Lassarre, "Robustness analysis of car-following models for full speed range ACC systems" in Traffic and Granular Flow 2019, Springer, 2020, pp. 571-581.
