Multiple Time Periods And With Fair Factors, Many Ways To Support The Pricing Model

Rapid developments in urbanization and growth of economy in China enable more and more people to own a car, which has led to serious urban traffic congestion. Conventional supply-side strategies such as road construction or capacity expansion have been less effective in reducing traffic congestion. More and more transportation policy-makers are now realizing the importance of transportation demand management (TDM). Congestion pricing as a TDM strategy has received increasing attention. This paper proposes a congestion pricing model with multi-period and multi-mode and then incorporates the multi-user dimension, in order to study the equity problem. Besides, by incorporating user and mode dimension together with the spatial and temporal dimension, the above model becomes a congestion pricing model with multi-period, multi-mode and multi-user, which focuses the interaction of the four dimensions above. After giving reasonable parameters to the function used in the model, a first partial derivative method is applied for the optimal model upon a simple network. The simulation example is conducted by software MATLAB and the results show that the model is effective.Generally speaking, when ignoring the equity problem, major impacts of congestion pricing policy on traffic volume allocations include: diversion of traffic from the tolled links to the free links; shift of the peak period traffic to the off-peak period; shift of the tolled mode to the non-toll mode; reduction in total traffic volumes and increase in total people's volumes. Congestion tolls which are endogenously determined by the equilibrium traffic volume allocations can actually be regarded as results of the game between the government and users. Congestion tolls as well as the social welfare are closely related to the network toll design, such as the tolled link, period and mode etc. It is true that social welfare gains through congestion pricing, however, the traffic congestion may not be alleviated. Tolling in peak period or encourage more users choosing public transportation mode to travel are more effective to prompt the social welfare. After considering the heterogeneity of users, major impacts of congestion pricing policy on traffic and people's volume allocations, congestion toll and social welfare do not change fundamentally. Meanwhile, this paper studies the impacts of enlarging the difference of users gradually on the traffic and people's volume, congestion toll and social welfare, and gets some meaningful conclusions, which would contribute positive effects to the equity study of congestion pricing.