Abstract
This paper proposed a multi-objective guaranteed feasible connected and autonomous vehicle (CAV) platoon control method for signalized isolated intersections with priorities. Specifically, we prioritized the intersection throughput and traffic efficiency under a pre-defined signal cycle, based on which we minimized fuel consumption and emissions for CAV platoons. Longitudinal safety was also considered as a necessary condition. To handle the aforementioned targets, we firstly designed a vehicular sub-platoon splitting algorithm based on Farkas lemma to accommodate a maximum number of vehicles for each signal green time phase. Secondly, the CAV optimal trajectories control algorithm was designed as a centralized cooperative model predictive control (MPC). Moreover, the optimal control problem was formulated as discrete linear quadratic control problems with constraints with receding predictive horizons, which can be efficiently solved by quadratic programming after reformulation. For rigor, the proofs of the recursive feasibility and asymptotic stability of our proposed predictive control model were provided. For evaluation, the performance of the control algorithm was compared against a non-cooperative distributed CAV control through simulation. It was found that the proposed method can significantly enhance both traffic efficiency and energy efficiency with ensured safety for CAV platoons at urban signalized intersections.
Highlights
Connected and autonomous vehicles (CAVs) are expected to improve traffic efficiency, safety, and reduce fuel consumption and emissions
We present formulations for both single CAV and CAV platoons to reflect the difference between their control objectives
Note that the decentralized method was developed based on the same concept of the proposed method, while it optimized each CAV instead
Summary
Connected and autonomous vehicles (CAVs) are expected to improve traffic efficiency, safety, and reduce fuel consumption and emissions. Various CAV trajectory control strategies had been proposed, with multiple objectives of maximizing traffic throughput, minimizing fuel consumption and emission, and ensuring driving safety. The studies on freeway focused on optimizing vehicle trajectories [4,5,6,7,8] to deal with speed oscillation in stop-and-go conditions [9,10,11,12,13,14,15] and dangerous situations caused by lane change and merges [16,17,18,19,20]. Research on Energies 2020, 13, 625; doi:10.3390/en13030625 www.mdpi.com/journal/energies
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