Distributed traffic control for reduced fuel consumption and travel time in transportation networks

This paper proposes a distributed framework for optimal control of vehicles in transportation networks. The objective is to reduce the balanced fuel consumption and travel time through hybrid control on speed limit and ramp metering rate. The dual decomposition theory associated with the subgradient method is then applied in order to decompose the optimal control problem into a series of suboptimal problems and then solve them individually via networked road infrastructures (RIs). Coordination among connected RIs is followed in each iteration to update the individual controls. An example is demonstrated to verify the reduction in terms of fuel consumption and travel time using the proposed approach.

I. Introduction

Today's transportation system is experiencing a revolution that significantly impacts people's lives. The increasing demands of safety, traffic capacity and energy efficiency impelled the emergence of new technologies. Examples of such technologies include vehicle sensing, hybrid drive systems, communication networks, etc., all aimed at enhancing the public desired performance in terms of efficiency and safety. It can be envisioned that the effectiveness of vehicle guidance and traffic management strategies will be amplified through Dedicated Short Range Communication wireless networks. These networks will operate among vehicles and between vehicles and roadway infrastructure (RI), named vehicular networks [1], [2]. In this venue, not only the drivers in vehicles have direct access to dynamic traveling related information, but also RI has more accurate situational awareness.