A Study on Economical Vehicle Platooning Strategy in Urban Driving Scenarios

Abstract

This paper presents a qualitatively study of driver’s behavior impacts on the fuel consumption and travel time of vehicle platooning system under urban driving scenarios. Vehicle platooning is proven advantageous in improving traffic flow, safety, energy efficiency and emission performance. To design effective platooning strategy, a better understanding of how each driver’s behavior influences the overall platoon fuel and time cost will be helpful. An integrated microscopic traffic model with fuel consumption estimation is developed to simulate urban traffic. Each driver’s behavior is categorically depicted by personalized parameters in the model. Through extensive Monte Carlo simulations, a strong correlation result is found between maximum acceleration of leading car and travel time, fuel consumption, monetized cost of the platoon, respectively. The relationship is further described by a first-order rational model with reasonably well goodness of fit.

Yao Ma

Assistant Professor

My research interests focus on control and modeling of intelligent vehicle systems for improvement of efficiency, mobility, and safety.