Abstract
Plug-in hybrid electric vehicles (PHEVs) are a promising step toward reaching a fully green passenger vehicle with large pre-chargeable batteries which offer a very good fuel economy. Many researchers are now focussing on making vehicles safer and more efficient by improving vehicles' interaction with their environment and assisting drivers to make better decisions with less errors. Adaptive Cruise Control (ACC) systems are a way to connect vehicles to the most important part of their environment which is the surrounding traffic. It has been shown that using the data from preceding traffic by ACC systems can significantly improve the driving performance. This study presents an ecological ACC (Eco-ACC) system that takes advantage of a radar and traffic light-to-vehicle communications (TL2VC) to predict the future trajectory of its preceding vehicle and employs this information to drive the vehicle with an ecological driving pattern. The problem is formulated as an optimal control problem and the model predictive control (MPC) method is used to solve it. The proposed Eco-ACC is evaluated using a high-fidelity Toyota Prius PHEV model, which shows about 17% improvement in the energy cost compared to a regular car-following ACC.
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