Signal Timing Optimization for Isolated Intersections under Mixed Traffic Environment

The development of connected vehicle technology is beneficial to traffic operations at intersections. Automated vehicles are expected to emerge in the urban network gradually. The mixed traffic environment will exist for a long period. This paper presents a signal optimization model for an isolated intersection under the mixed traffic environment including connected and human-driven vehicles (CHVs) and connected and automated vehicles (CAVs). The problem is formulated as a mixed integer linear programming (MILP) model. Phase sequence and phase duration are optimized without the concept of cycle length for total vehicle delay minimization. Vehicle motion is analyzed and the passing states of CHVs and CAVs at stop bars are predicted to avoid the prior information of specific trajectory planning strategies of CAVs. A rolling horizon procedure is designed for the dynamic implementation of the proposed model with varying traffic conditions. The simulation results show that the proposed signal timing model can reduce average vehicle delay significantly compared to vehicle-actuated and fixed time control, especially with under-saturated traffic demand and more conflicting traffic streams. The sensitive analysis further shows that average vehicle delay decreases notably when the penetration rate of CAVs increases from 0% to 30%.