Eco-Driving of Autonomous Vehicles for Nonstop Crossing of Signalized Intersections

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This article is devoted to the development of an optimal speed profile for autonomous vehicles in order to cross a signalized intersection without stopping. The design objective is to achieve both a short travel time and low energy consumption by taking full advantage of the traffic light information based on vehicle-to-infrastructure communication. The eco-driving problem is formulated as an optimal control problem. For the case where the vehicles are in free-flow mode, we derive a real-time on-line analytical solution, distinguishing our method from most existing approaches based on numerical calculations. Under mild assumptions, the optimal eco-driving algorithm is readily extended to cases where the free-flow mode does not apply due to the presence of interfering traffic. Extensive simulations are provided to compare the performance of autonomous vehicles under the proposed speed profile and human-driven vehicles. The results show quantitatively the advantages of the proposed algorithm in terms of energy consumption and travel time. Note to Practitioners - This article is motivated by the requirements for increased safety, increased efficiency in energy consumption, and lower congestion in signalized intersections. We take advantage of the traffic signal phase and timing information based on vehicle to infrastructure communication, and use the information to plan the vehicle's trajectory to avoid the red traffic signal. An optimal speed profile is developed to achieve a trade-off between minimizing trip time and avoiding unnecessary braking and acceleration which corresponds to minimizing energy consumption. We then show how such a speed profile can be efficiently computed and control the motion of an autonomous vehicle (or serve as an intelligent speed advisory system for human-driven vehicles) leading to a safe, time-efficient, and energy-efficient trip. A video of a real autonomous vehicle test implementing our control algorithm can be found at https://www.youtube.com/watch?v=x-ao4szeLYo.

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IEEE Transactions on Automation Science and Engineering

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