A Smart City Signalized ECO-Cooperative Adaptive Cruise Control and Multi- objective Dynamic Routing System
Authors: Hao Chen and Hesham A Rakha

Abstract: The paper integrates and tests an Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I) system with a multi-objective dynamic router on a large-scale metropolitan network to quantify the system-level performance considering different vehicle powertrains, connected automated vehicle (CAV) market penetration rates, and congestion levels. Specifically, three vehicle powertrains are considered in this study, including internal combustion engine vehicles (ICEVs), battery electric vehicles (BEVs) and hybrid electric vehicles (HEVs). Since the fuel/energy consumption patterns for ICEVs, BEVs and HEVs differ significantly with respect to driving cycles, this study selects appropriate fuel/energy consumption models for different vehicle powertrains. The integrated controller provides optimal routing solutions to save energy and travel time, and also computes energy-optimized trajectories to assist vehicles traverse signalized intersections. A simulated traffic network in the Greater Los Angeles Area including the downtown LA and the immediate vicinity is used to implement and test the integrated controller. The test results demonstrate that the integrated controller produces positive impacts in saving fuel/energy consumption, reducing travel time and delays on urban networks for different combinations of CAV market penetration and congestion levels. We also conducted tests to compare the integrated controller and the multi-objective eco-routing. The test results for BEVs indicate that the integrated controller effectively reduces energy consumption by up to 8.8% and stopped delay by up to 50%, but increases travel time by up to 28% and total delay by up to 43.8%, compared to the multi-objective eco-routing. The comparison results for ICEV and HEV indicate that the integrated controller can effectively reduce stopped delay by up to 72.0% for ICEVs and 72.4% for HEVs under various congestion levels.