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Study on Urban Traffic Network Optimization Based on the Link Capacity

Author: CuiZuo
Tutor: SunHuiJun
School: Beijing Jiaotong University
Course: System Analysis and Integration
Keywords: Link Capacity Random Variation Risk Aversion Congestion Pricing Bi-level Programming
CLC: U491
Type: Master's thesis
Year: 2011
Downloads: 104
Quote: 0
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Abstract


Imbalance of supply and demand is the basic reason of urban traffic congestion. In reality the contradiction of imbalance is often difficult to reconcile. There are many reasons. In addition to the inherent deficiency of network design supply capacity, stochastic link capacity plays an important role in the contradiction. Link capacity is part of network design supply capacity, it is influenced by traffic accidents, road construction, vehicle breakdowns, weather variations and so on, stochastic link capacity leads to the degradation of network supply capacity. At the same time, link capacity is also the critical decision factor of Continuous Network Design Problem. At the present time, link capacity planning has been studied extensively by the transportation researchers. In order to utilize the supply resources more efficiently, the link capacity planning which thinks about the choice behaviors of travelers and management strategies is more meaningful. The paper study as follows:Firstly, consider the choice behaviors of risk aversion travelers under uncertain network. The risk aversion is closely related to stochastic link capacities, which represents sensitive degree of the capacity changes. Both sensitivity and awareness effect the travelers’behaviors. Put forward a travelers’risk aversion assignment model according to Logit model. Simulation results show that the affects of sensitivity differ with the changes of awareness. The combination of sensitivity and awareness brings the best results, and excessive sensitivity is detrimental to the travelers.Secondly, adopt the network with stochastic link capacity and consider congestion pricing. Put forward a congestion pricing bi-level programming model. The upper objective is to minimize the total travel time changes thinking about congestion pricing, the lower model is habitual travel time budget equilibrium model. The computation results show that the time unpredictability caused by stochastic link capacity effect the behaviors of travelers, the habitual travel time budget equilibrium model is more truthfulness; congestion pricing reduces the total travel time changes and eases the traffic congestion, but the efficacy of congestion pricing will be falling off if the road condition is better.Finally, introduce the pricing subsidy to the Continuous Network Design Problem:add the congestion pricing to road construction and embody it in the investment function. Put forward Continuous Network Design model under pricing subsidy. The upper objective is to minimize the total travel time changes thinking about congestion pricing, the lower model is stochastic equilibrium model. The computation results show that calculating the estimated value accurately can minimize the total travel time and avoid extravagance; congestion pricing and pricing subsidy both can reduce the total travel time changes, and pricing subsidy’s effectiveness is better.

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CLC: > Transportation > Road transport > Technical management of traffic engineering and road transport > Traffic engineering and traffic management
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