SYROSep 21, 2018

Decentralized Optimal Merging Control for Connected and Automated Vehicles

arXiv:1809.07916v237 citations
Originality Incremental advance
AI Analysis

This work addresses merging efficiency and safety for CAVs, but it is incremental as it builds on existing decentralized control methods.

This paper tackles the optimal control problem for Connected and Automated Vehicles (CAVs) at merging points to minimize travel time and energy consumption while ensuring safety constraints, with simulation results showing improvements in both metrics compared to a baseline with human-driven vehicles.

This paper addresses the optimal control of Connected and Automated Vehicles (CAVs) arriving from two roads at a merging point where the objective is to jointly minimize the travel time and energy consumption of each CAV. The solution guarantees that a speed-dependent safety constraint is always satisfied, both at the merging point and everywhere within a control zone which precedes it. We first analyze the case of no active constraints and prove that under certain conditions the safety constraint remains inactive, thus significantly simplifying the determination of an explicit decentralized solution. When these conditions do not apply, an explicit solution is still obtained that includes intervals over which the safety constraint is active. Our analysis allows us to study the tradeoff between the two objective function components (travel time and energy within the control zone). Simulation examples are included to compare the performance of the optimal controller to a baseline with human-driven vehicles with results showing improvements in both metrics.

Foundations

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