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Preceding vehicles typically dominate the movement of following vehicles intraffic systems, thereby significantly influencing the efficacy of eco-drivingcontrol that concentrates on vehicle speed optimization. To potentiallymitigate the negative effect of preceding vehicles on eco-driving control atthe signalized intersection, this paper proposes an overtakingenabledeco-approach control (OEAC) strategy. It combines driving lane planning andspeed optimization for connected and automated vehicles to relax thefirst-in-first-out queuing policy at the signalized intersection, minimizingthe target vehicle's energy consumption and travel delay. The OEAC adopts areceding horizon two-stage control framework to derive optimal drivingtrajectories for adapting to dynamic traffic conditions. In the first stage,the driving lane optimization problem is formulated as a Markov decisionprocess and solved using dynamic programming, which takes into account theuncertain disturbance from preceding vehicles. In the second stage, thevehicle's speed trajectory with the minimal driving cost is optimized rapidlyusing Pontryagin's minimum principle to obtain the closed-form analyticaloptimal solution. Extensive simulations are conducted to evaluate theeffectiveness of the OEAC. The results show that the OEAC is excellent indriving cost reduction over constant speed and regular eco-approach anddeparture strategies in various traffic scenarios, with an average improvementof 20.91% and 5.62%, respectively.

Overtaking-enabled Eco-approach Control at Signalized Intersections for Connected and Automated Vehicles