Leveraging Connected Vehicle Technology and Telematics to Enhance Vehicle Fuel Efficiency in the Vicinity of Signalized Intersections

• Published in: Journal of intelligent transportation systems Vol. 20; no. 1; pp. 33 - 44
• Main Authors: Kamalanathsharma, Raj Kishore, Rakha, Hesham A.
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 02.01.2016; Taylor & Francis Ltd
• Subjects: Algorithms; Eco-Cruise Control; Eco-Drive Systems; Energy efficiency; Fuel consumption; Fuel economy; Fuels; Intelligent transportation systems; Intelligent vehicle highway systems; Intersections; Roads & highways; Telematics; Traffic accidents & safety; Traffic Signals; Trajectories; Vehicle Control; Vehicle Fuel Optimization; Vehicles
• ISSN: 1547-2450; 1547-2442
• DOI: 10.1080/15472450.2014.889916

Driving on highways and arterial roadways involves vehicle acceleration, braking, cruising, coasting, and idling episodes. As the vehicle speed deviates from its "fuel optimum speed," additional fuel is consumed, thus reducing the vehicle fuel efficiency. The research presented in this article develops a connected vehicle application entitled Eco-Cooperative Adaptive Cruise Control (ECACC) that uses infrastructure-to-vehicle (I2V) communication to receive signal phasing and timing (SPaT) data, predict future constraints on a vehicle's trajectory, and optimize its trajectory to minimize the vehicle's fuel consumption level. The trajectory optimization is made using a moving horizon dynamic programming (DP) approach. A modified A-star algorithm is developed to enhance the computational efficiency of the DP for use in real-time implementations. The model is calibrated and tested on 30 top-sold vehicles in the United States and is demonstrated to provide fuel savings within the vicinity of signalized intersections in the range of 5 to 30%.