Optimal Control for Speed Harmonization of Automated Vehicles

TL;DR

This paper develops an optimal control method for automated vehicle speed harmonization that minimizes fuel consumption and travel time while ensuring safety, validated through microscopic simulations showing significant improvements over existing methods.

Contribution

It provides a closed-form, real-time implementable control solution for automated vehicle speed regulation with safety guarantees, outperforming baseline and existing algorithms.

Findings

Fuel consumption reduced by up to 22% compared to baseline.

Travel time improved by up to 39% over existing algorithms.

Method effectively ensures safety and efficiency in simulated freeway scenarios.

Abstract

This article addresses the problem of controlling the speed of a number of automated vehicles before they enter a speed reduction zone on a freeway. We formulate the control problem and provide an analytical, closed-form solution that can be implemented in real time. The solution yields the optimal acceleration/deceleration of each vehicle under the hard safety constraint of rear-end collision avoidance. The effectiveness of the solution is evaluated through a microscopic simulation testbed and it is shown that the proposed approach reduces significantly both fuel consumption and travel time. In particular, for three different traffic volume levels, fuel consumption for each vehicle is reduced by 19-22% compared to the baseline scenario, where human-driven vehicles are considered, by 12-17% compared to the variable speed limit (VSL) algorithm, and by 18-34% compared to the vehicular-based speed harmonization (SPD-HARM) algorithm. Similarly, travel time is improved by 26-30% compared to the baseline scenario, by 3-19% compared to the VSL algorithm, and by 31-39% compared to the vehicular-based SPD-HARM algorithm.