MAXIMIZING CAR OWNERSHIP UNDER CONSTRAINTS OF ENVIRONMENT SUSTAINABILITY IN A CITY

This study aims to optimize road traffic flow and forecast the maximum car ownership accommodated in a city to satisfy environmental requirement and quantify road traffic capacity. A bi-level optimization model is established, where upper level is a maximum car ownership model, whose objective function is the total zonal car ownerships and the constraint is that traffic environment load on a link should not exceed the transportation environmental capacity, while lower level is a fixed demand user equilibrium assignment model, which simulates travelers' path choice behavior. To realize the feedback between the two levels and solve the optimization problems simultaneously, an optimal algorithm based on sensitivity analysis was developed, namely acquire derivative function of link volume and traffic demand with respect to zonal car ownership, and feedback the function into upper level program. Finally, we verify the bi-level model and the algorithm with a case study.