Development and Evaluation of an Adaptive Traffic Signal Control Scheme Under a Mixed-Automated Traffic Scenario

Abstract

This paper presents a novel adaptive traffic signal control scheme that addresses a mixed manual-automated traffic scenario in a typically isolated intersection. The traffic signals are optimized in a receding horizon control framework that aims at minimizing the total crossing time of all vehicles, considering their dynamical states. The control scheme ensures comfortable crossing of manually driven vehicles by retaining the basic features of the traditional signal management systems. The optimal signal changing times are broadcasted one cycle ahead, which enables the automated vehicles to tune their speed in order to cross the intersection with minimum stop-delay. More specifically, the framework optimizes the green time of each signal without considering the existing cycle-split concept explicitly. The proposed signal control scheme is evaluated in microscopic traffic simulation considering the different proportion of turning traffic at the intersection and various penetration rates of the automated vehicles. It is observed that the optimization process usually results in the shortest possible green period of each signal that can be realized without reducing the capacity of the intersection at any traffic volumes. Consequently, the resulting short signal cycle which is adaptive to the traffic around the intersection improves the average speed and reduces both the traffic density and the number of idling vehicles. As a consequence, the fuel consumption efficiency and the rate of CO2 emission around the intersection are also reduced. These results are compared with both the traditional fixed time and the actuated signal control schemes. As the portion of the automated vehicles increases in the case of the proposed scheme, the overall traffic flow performance further improves.