scholarly journals Joint Implementation of Signal Control and Congestion Pricing in Transportation Network

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Mao ◽  
Feifei Qin ◽  
Yihong Hu ◽  
Zhijia Tan
Keyword(s):  
Transportation Network ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Joint Implementation ◽  
Simultaneous Optimization ◽  
Signal Control ◽  
Solution Methods ◽  
Total Travel Time ◽  
Upper Level ◽  
Bilevel Programs

The policy of jointly implementing signal control and congestion pricing in the transportation network is investigated. Bilevel programs are developed to model the simultaneous optimization of signal setting and congestion toll. The upper level aims to maximize the network reserve capacity or minimize the total travel time, subject to signal setting and toll constraints. The lower level is a deterministic user equilibrium problem given a plan of signal setting and congestion charge. Then the bilevel programs are transferred into the equivalent single level programs, and the solution methods are discussed. Finally, a numerical example is presented to illustrate the concepts and methods, and it is shown that the joint implementation policy can achieve promising results.

Optimal congestion pricing toll design for revenue maximization: comprehensive numerical results and implications

2015 ◽  
Vol 42 (8) ◽  
pp. 544-551 ◽  
Author(s):  
Wei Fan
Keyword(s):  
Operating Cost ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Numerical Results ◽  
Revenue Maximization ◽  
Value Of Time ◽  
Elastic Demand ◽  
Upper Level ◽  
Demand Sensitivity ◽  
The Impact

The purpose of this paper is to present bi-level optimization models and develop a genetic algorithm (GA) based method to solve the optimal congestion pricing toll design problem and to determine the second-best link-based optimal toll locations and toll levels simultaneously. The upper-level subprogram is to maximize the toll revenue collected while explicitly accounting for the toll booth setting up and operating cost, given certain toll level constraints. The lower-level subprogram is a traditional user equilibrium problem with elastic demand. The proposed GA model is applied to the Sioux Falls network, which has 76 links and 24 origin–destination pairs, assuming homogeneous users. Comprehensive numerical results including solutions achieved under continuous tolling and discrete tolling schemes, tolling on optimized links and tolling on heuristically selected most congested links are carefully presented and compared. The impact of value of time and the elastic demand sensitivity are also comprehensively investigated.

scholarly journals Flexible Emergency Vehicle Network Design considering Stochastic Demands and Inverse-Direction Lanes

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Hua Wang ◽  
Ling Xiao ◽  
Zhang Chen
Keyword(s):  
Network Design ◽  
Transportation Network ◽  
Bilevel Optimization ◽  
User Equilibrium ◽  
Emergency Vehicle ◽  
Stochastic Demands ◽  
Road Users ◽  
Level Model ◽  
Access Rights ◽  
Upper Level

We study transportation network design with stochastic demands and emergency vehicle (EV) lanes. Different from previous studies, this paper considers two groups of users, auto and EV travelers, whose road access rights are differentiated in the network, and addresses the value of incorporating inverse-direction lanes in network design. We formulate the problem as a bilevel optimization model, where the upper-level model aims to determine the optimal design of EV lanes and the lower-level model uses the user equilibrium principle to forecast the route choice of road users. A simulation-based genetic algorithm is proposed to solve the model. With numerical experiments, we demonstrate the value of deploying inverse-direction EV lanes and the computational efficiency of the proposed algorithm. We reach an intriguing finding that both regular and EV lane users can benefit from building EV lanes.

scholarly journals Topological Effects and Performance Optimization in Transportation Continuous Network Design

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jianjun Wu ◽  
Xin Guo ◽  
Huijun Sun ◽  
Bo Wang
Keyword(s):  
Network Design ◽  
Performance Optimization ◽  
Transportation Network ◽  
Small World ◽  
User Equilibrium ◽  
Solution Approach ◽  
Proposed Model ◽  
Upper Level ◽  
And Performance ◽  
Bilevel Transportation

Because of the limitation of budget, in the planning of road works, increased efforts should be made on links that are more critical to the whole traffic system. Therefore, it would be helpful to model and evaluate the vulnerability and reliability of the transportation network when the network design is processing. This paper proposes a bilevel transportation network design model, in which the upper level is to minimize the performance of the network under the given budgets, while the lower level is a typical user equilibrium assignment problem. A new solution approach based on particle swarm optimization (PSO) method is presented. The topological effects on the performance of transportation networks are studied with the consideration of three typical networks, regular lattice, random graph, and small-world network. Numerical examples and simulations are presented to demonstrate the proposed model.

scholarly journals Optimal Design of Transportation Networks with Automated Vehicle Links and Congestion Pricing

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yipeng Ye ◽  
Hua Wang
Keyword(s):  
Network Design ◽  
Traffic Congestion ◽  
Solution Method ◽  
Congestion Pricing ◽  
Market Penetration ◽  
Travel Costs ◽  
Automated Vehicle ◽  
Proposed Model ◽  
Total Travel Time ◽  
Upper Level

We propose a bi-level network design model comprising automated vehicle (AV) links and congestion pricing to improve traffic congestion. As upper-level road planners strive to minimize total travel-time costs by optimizing both the network design and the congestion pricing, lower-level travelers make choices about their routes to minimize their individual travel costs. Our proposed model integrates a network design and congestion pricing to improve traffic congestion and we use a relaxation-based method to solve the model. We conducted a series of numerical tests to analyze the proposed model and solution method. Our results indicate that network design is more effective than congestion pricing when the AV market penetration is high and the opposite is true when AV penetration is low. More importantly, we find that a network design of automated vehicle links with congestion pricing is superior to a single network design or congestion pricing, especially when both AVs and conventional vehicles have a relatively large market penetration.

Incorporating Travel Time Reliability in Equitable Congestion Pricing Schemes for Heterogeneous Users and Bimodal Networks

2021 ◽  
pp. 036119812110197
Author(s):  
Fatemeh Fakhrmoosavi ◽  
Ali Zockaie ◽  
Khaled Abdelghany
Keyword(s):  
Travel Time ◽  
Optimization Algorithm ◽  
Travel Demand ◽  
Demand Management ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Travel Demand Management ◽  
Equity Issues ◽  
Total Travel Time

Congestion pricing is proposed as an effective travel demand management strategy to circumvent the problem of congestion and generate revenue to finance developmental projects. There are several studies focusing on optimal pricing strategies to minimize the congestion level or maximize the revenue of the system. However, with regard to equity issues, benefiting only users with higher value of time is claimed to be the main factor that prevents implementation of such policies in practice. While many studies aimed to tackle the equity issues by certain welfare analyses, most of these studies fail to fully consider realistic features of users’ behavior and the uncertainty in link travel times. Given the variability of travel time in real-world networks and the impacts of pricing policies on path travel time distributions, it is important to consider the users’ reliability valuations, in addition to their travel time valuations. Thus, the goal in this study is to find an equitable pricing scheme that minimizes the total travel time of auto users in a general bimodal network considering heterogeneous users with different values of time and reliability. A particle swarm optimization algorithm is proposed to find self-funded and Pareto-improving optimal toll values. A reliability-based user equilibrium algorithm is embedded into this optimization algorithm to assign travelers to the equilibrated paths for different user classes given toll values. The proposed approach is successfully applied to a modified Sioux Falls network to explore impacts of subsidization, congestion level, and considering travel time reliability on the pricing strategy and its effectiveness.

scholarly journals Stochastic Congestion Pricing among Multiple Regions: Competition and Cooperation

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Hua Wang ◽  
Wei Mao ◽  
Hu Shao
Keyword(s):  
Social Welfare ◽  
Travel Time ◽  
Demand Uncertainty ◽  
Transportation Network ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Stochastic User Equilibrium ◽  
Multiple Regions ◽  
The Impact

Previous studies of road congestion pricing problem assume that transportation networks are managed by a central administrative authority with an objective of improving the performance of the whole network. In practice, a transportation network may be comprised of multiple independent local regions with relative independent objectives. In this paper, we investigate the cooperative and competitive behaviors among multiple regions in congestion pricing considering stochastic conditions; especially demand uncertainty is taken into account in transportation modelling. The corresponding congestion pricing models are formulated as a bilevel programming problem. In the upper level, congestion pricing model either aims to maximize the regional social welfare in competitive schemes or attempts to maximize the total social welfare of multiple regions in cooperative schemes. In the lower level, travellers are assumed to follow a reliability-based stochastic user equilibrium principle considering risks of late arrival under uncertain conditions. Numerical examples are carried out to compare the effects of different pricing schemes and to analyze the impact of travel time reliability. It is found that cooperative pricing strategy performs better than competitive strategy in improving network performance, and the pricing effects of both schemes are quite sensitive to travel time reliability.

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