TY - GEN ID - discovery10118036 AV - public KW - Mechanical power transmission KW - Energy consumption KW - Batteries KW - Vehicle dynamics KW - Trajectory KW - Torque KW - Safety EP - 2836 N1 - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions. PB - IEEE SN - 2576-2370 N2 - Traffic congestion is one of the major issues for urban traffic networks. The connected and autonomous vehicles (CAV) is an emerging technology that has the potential to address this issue by improving safety, efficiency, and capacity of the transportation system. In this paper, the problem of optimal trajectory planning of battery-electric CAVs in the context of cooperative crossing of an unsignalized intersection is addressed. An optimization-based centralized intersection controller is proposed to find the optimal velocity trajectory of each vehicle so as to minimize electric energy consumption and traffic throughput. Solving the underlying optimization problem for a group of CAVs is not straightforward because of the nonlinear and nonconvex dynamics, especially when the powertrain model is explicitly modelled. In order to ensure a rapid solution search and a unique global optimum, the optimal control problem (OCP) is reformulated via convex modeling techniques. Several simulation case studies show the effectiveness of the proposed approach and the trade-off between energy consumption and traffic throughput is illustrated. SP - 2831 Y1 - 2021/01/11/ A1 - Pan, X A1 - Chen, B A1 - Evangelou, S A1 - Timotheou, S UR - https://doi.org/10.1109/CDC42340.2020.9304392 CY - Jeju Island, South Korea TI - Optimal Motion Control for Connected and Automated Electric Vehicles at Signal-Free Intersections T3 - IEEE Conference on Decision and Control (CDC) ER -