Traffic light scheduling for pedestrian-vehicle mixed-flow networks - Zhang, Yi (2021)
This paper presents a macroscopic model for pedestrian-vehicle mixed-flow network and a traffic signal scheduling strategy for both pedestrians and vehicles. We first propose a novel mathematical model of pedestrians crossing a junction. By combining a link-based vehicle network model, a traffic light scheduling problem is formulated with the aim to strike a good balance between pedestrians' needs and vehicle drivers' needs. The problem is first converted into a mixed-integer linear programming (MILP) problem via a novel transformation procedure, which is solvable by several existing solvers, e.g., GUROBI. Then a meta-heuristic method called discrete harmony search (DHS) algorithm is also adopted to reduce the computational complexity in MILP. Numerical simulation results are provided to illustrate the effectiveness of our real-time traffic light scheduling strategy for pedestrians and vehicles, and the potential impact of the pedestrian movement to the vehicle traffic flows.