A Smart City Signalized ECO-Cooperative Adaptive Cruise Control and Multi-objective Dynamic Routing System

The paper integrates an Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I) controller with a multi-objective dynamic router and tests it 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). The integrated controller simultaneously computes energy-optimal routings and energy-optimized trajectories in the vicinity of signalized intersections. A simulated traffic network in the Greater Los Angeles Area is used to implement and test the integrated controller. The test results demonstrate that the integrated controller produces fuel/energy consumption savings, reduces vehicle travel time and delays in urban networks. We also conducted tests to compare the integrated controller to 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 base case. The comparison results for ICEVs and HEVs indicate that the integrated controller can effectively reduce stopped delay by up to 72.0% for ICEVs and 72.4% for HEVs.