Clustering Strategies of Cooperative Adaptive Cruise Control: Impacts on Human-driven Vehicles

TL;DR

This study compares two clustering strategies for cooperative adaptive cruise control (CACC) and their effects on human-driven vehicles, revealing that local coordination improves network performance but may impact safety and driving behavior.

Contribution

It provides a comparative analysis of ad hoc and local clustering strategies for CACC and their impacts on human-driven vehicles using microscopic simulation data.

Findings

Local coordination outperforms ad hoc in throughput and productivity.

Safety impacts vary with clustering strategy, affecting hard braking distributions.

CAVs increase lane change frequency in human-driven vehicles.

Abstract

As a promising application of connected and automated vehicles (CAVs), Cooperative Adaptive Cruise Control (CACC) is expected to be deployed on the public road in the near term. Thus far the majority of the CACC studies have been focusing on the overall network performance with limited insight on the potential impact of CAVs on human-driven vehicles (HVs). This paper aims to quantify the influence of CAVs on HVs by studying the high-resolution vehicle trajectory data that is obtained from microscopic simulation. Two clustering strategies for CACC are implemented: an ad hoc coordination one and a local coordination one. Results show that the local coordination outperforms the ad hoc coordination across all tested market penetration rates (MPRs) in terms of network throughput and productivity. The greatest performance difference between the two strategies is observed at 30% and 40% MPR for throughput and productivity, respectively. However, the distributions of the hard braking observations (as a potential safety impact) for HVs change significantly under local coordination strategy. Regardless of the clustering strategy, CAVs increase the average lane change frequency for HVs. 30% MPR is the break-even point for local coordination, after which the average lane change frequency decreases from the peak 5.42 to 5.38. Such inverse relationship to MPR is not found in the ah hoc case and the average lane change frequency reaches the highest 5.48 at 40% MPR.