Combinatorial Optimization of Congested Road and Parking Charging

Abstract

Congestion charging on certain roads can get ideal work proved by practice in many places; meanwhile, the parking charging also restrains traffic demand effectively. Thus, combining these two strategies with systematical analysis is rather important. This paper develops a bi-level combination optimization model. The upper-level of this model aims at maximizing the social benefit, and the user optimization equilibrium model is used as the lower model. Moreover, generalized travel costs (including travel cost and parking fee) are considered with elastic demand based on traffic demand analysis. This model is to obtain the balance between congestion charging and parking charging. Pattern search algorithm is used to solve this problem. The numerical results show that different initial step length and iteration accuracy lead to different results, and combination charging can get equilibrium traffic flow assignment in the whole network. It also alleviates road-charged congestion to some extent with traffic demand reduction. The numerical example proves the rationality and efficiency of the bi-level combination optimization model and algorithm.