Leading Cruise Control in Mixed Traffic Flow

TL;DR

This paper introduces Leading Cruise Control (LCC), a novel approach for CAVs that considers their influence on upstream traffic, demonstrating its potential to improve traffic stability and flow through modeling, analysis, and simulations.

Contribution

The paper proposes LCC, a new control strategy for CAVs that explicitly accounts for upstream traffic influence, supported by controllability analysis and transfer function derivation.

Findings

LCC can effectively suppress traffic instabilities.

LCC enables CAVs to lead and influence upstream vehicles.

Numerical results show improved traffic flow smoothness.

Abstract

Vehicle-to-vehicle (V2V) communications have a great potential to improve traffic system performance. Most existing work of connected and autonomous vehicles (CAVs) focused on adaptation to downstream traffic conditions, neglecting the impact of CAVs' behaviors on upstream traffic flow. In this paper, we introduce a notion of Leading Cruise Control (LCC) that retains the basic car-following operation and explicitly considers the influence of the CAV's actions on the vehicles behind. We first present a detailed modeling process for LCC. Then, rigorous controllability analysis verifies the feasibility of exploiting the CAV as a leader to actively lead the motion of its following vehicles. Besides, the head-to-tail transfer function is derived for LCC under adequate employment of V2V connectivity. Numerical studies confirm the potential of LCC to strengthen the capability of CAVs in suppressing traffic instabilities and smoothing traffic flow.