Eco-Trajectory Planning with Consideration of Queue along Congested Corridor for Hybrid Electric Vehicles

At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.

[1]  Zoran Filipi,et al.  Modeling and Analysis of the Toyota Hybrid System , 2005 .

[2]  Yiheng Feng,et al.  Intelligent Traffic Control in a Connected Vehicle Environment , 2015 .

[3]  Ardalan Vahidi,et al.  Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time , 2011, IEEE Transactions on Control Systems Technology.

[4]  Guoyuan Wu,et al.  Development and evaluation of an enhanced eco-approach traffic signal application for Connected Vehicles , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[5]  Kanok Boriboonsomsin,et al.  Dynamic ECO-driving for arterial corridors , 2011, 2011 IEEE Forum on Integrated and Sustainable Transportation Systems.

[6]  Hesham A. Rakha,et al.  Eco-driving at signalized intersections using V2I communication , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[7]  Henry X. Liu,et al.  Optimal vehicle speed trajectory on a signalized arterial with consideration of queue , 2015 .

[8]  Kanok Boriboonsomsin,et al.  Energy and emissions impacts of a freeway-based dynamic eco-driving system , 2009 .

[9]  Carlos Canudas de Wit,et al.  Eco-driving in urban traffic networks using traffic signal information , 2013, 52nd IEEE Conference on Decision and Control.

[10]  Wei Yuan,et al.  Predictive intelligent driver model for eco-driving using upcoming traffic signal information , 2018, Physica A: Statistical Mechanics and its Applications.

[11]  Xinkai Wu,et al.  A shockwave profile model for traffic flow on congested urban arterials , 2011 .

[12]  Masafumi Miyatake,et al.  Theoretical study on eco-driving technique for an Electric Vehicle considering traffic signals , 2011, 2011 IEEE Ninth International Conference on Power Electronics and Drive Systems.

[13]  Meng Wang,et al.  Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment , 2017 .

[14]  Namwook Kim,et al.  Autonomie model validation with test data for 2010 Toyota Prius , 2012 .

[15]  黒田 孝次,et al.  Highway Capacity Manual改訂の動向--テイラ-教授の講演より , 1984 .

[16]  Junichi Murata,et al.  Model Predictive Control of Vehicles on Urban Roads for Improved Fuel Economy , 2013, IEEE Transactions on Control Systems Technology.

[17]  Huei Peng,et al.  Modeling and Control of a Power-Split Hybrid Vehicle , 2008, IEEE Transactions on Control Systems Technology.

[18]  O. Singh,et al.  Global Trends of Fossil Fuel Reserves and Climate Change in the 21st Century , 2012 .

[19]  Henry X. Liu,et al.  A calibration procedure for microscopic traffic simulation , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[20]  Dimitar Filev,et al.  Analytical and numerical solutions for energy minimization of road vehicles with the existence of multiple traffic lights , 2013, 52nd IEEE Conference on Decision and Control.