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This manuscript investigated coordinated intersection signal design problem for mixed traffic flow of Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs). Two main macroscopic impact of the mixed flow on signal setting are considered: saturation flow rate and the platoon dispersion. In order to capture the traffic flow operational characteristics on coordinated intersections, three locations, namely entrance location where the loop detector was located at, and upstream intersection and downstream intersection were defined. Two types of vehicle cumulative curves, namely cumulative arrival profile and cumulative departure profile were constructed. The mixed-flow traffic dynamics were analyzed, and the arrival-departure curves relationship was derived using a combination of Newell car-following and Ak&#x00E7;elik acceleration model. A mixed-flow platoon dispersion model was proposed to describe the vehicle's progression between two locations. Due to the nonlinear nature of the problem, a particle swarm optimization (PSO) method was employed to obtain the optimal signal parameters, including the cycle length, green duration, and optimal offset. The algorithm was implemented and validated in a case study involving two intersections, with the demand formulated and simulated by the Markov chain. The results showed that the proposed model could effectively decrease delays when compared with current signal control methods.

Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles