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Journal of Advanced Transportation
Volume 2017 (2017), Article ID 1023654, 16 pages
https://doi.org/10.1155/2017/1023654
Research Article

Developing a Distributed Consensus-Based Cooperative Adaptive Cruise Control System for Heterogeneous Vehicles with Predecessor Following Topology

Center for Environmental Research and Technology, University of California, Riverside, Riverside, CA, USA

Correspondence should be addressed to Ziran Wang

Received 27 February 2017; Revised 13 May 2017; Accepted 19 June 2017; Published 6 August 2017

Academic Editor: Meng Wang

Copyright © 2017 Ziran Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Connected and automated vehicle (CAV) has become an increasingly popular topic recently. As an application, Cooperative Adaptive Cruise Control (CACC) systems are of high interest, allowing CAVs to communicate with each other and coordinating their maneuvers to form platoons, where one vehicle follows another with a constant velocity and/or time headway. In this study, we propose a novel CACC system, where distributed consensus algorithm and protocol are designed for platoon formation, merging maneuvers, and splitting maneuvers. Predecessor following information flow topology is adopted for the system, where each vehicle only communicates with its following vehicle to reach consensus of the whole platoon, making the vehicle-to-vehicle (V2V) communication fast and accurate. Moreover, different from most studies assuming the type and dynamics of all the vehicles in a platoon to be homogenous, we take into account the length, location of GPS antenna on vehicle, and braking performance of different vehicles. A simulation study has been conducted under scenarios including normal platoon formation, platoon restoration from disturbances, and merging and splitting maneuvers. We have also carried out a sensitivity analysis on the distributed consensus algorithm, investigating the effect of the damping gain on convergence rate, driving comfort, and driving safety of the system.