This article considers the energy optimization problem with multiple time window constraints, which is motivated by the eco-driving of connected and automated vehicles (CAVs) in urban traffic. Timely crossing of signalized intersections defines complex spatio-temporal constraints, and multiple available open time windows introduce the discontinuous feasible domains of crossing times. The CAVs should select an open time window for each intersection, determine the crossing times, and optimize the speed profiles accordingly, which turns out to be a hard-to-solve optimization problem. To address this challenge, this article proposes a unifying approach that transforms the energy optimization problem into a novel mixed-integer optimal control problem with characteristic time (MIOCP-CT) constraints. This approach facilitates the simultaneous optimization of open time windows, crossing times, and speed profiles within a single optimization problem, which can be solved by our proposed novel numerical solution procedure. The application of the proposed method in the eco-driving of CAVs approaching multiple signalized intersections demonstrates its performance within real-world urban driving cycles. The experimental results of the hardware-in-the-loop (HiL) demonstrate a superior energy-saving performance of 5.83% compared to existing methods, while also achieving real-time feasibility within 100 ms.
Mixed-Integer Optimal Control With Disjunctive Characteristic Time Constraints for Energy-Optimal Speed Planning
IEEE Transactions on Transportation Electrification ; 11 , 4 ; 9532-9543
01.08.2025
2006945 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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BASE | 2013
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