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 Signal Design for Mixed Equilibrium Networks with Autonomous and Regular Vehicles

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Nan Jiang
Keyword(s):  
Autonomous Vehicles ◽  
Design Problem ◽  
Control Strategies ◽  
Transportation Network ◽  
Bilevel Optimization ◽  
User Equilibrium ◽  
Signal Design ◽  
Level Model ◽  
Mixed Equilibrium ◽  
Mixed Networks

A signal design problem is studied for efficiently managing autonomous vehicles (AVs) and regular vehicles (RVs) simultaneously in transportation networks. AVs and RVs move on separate lanes and two types of vehicles share the green times at the same intersections. The signal design problem is formulated as a bilevel program. The lower-level model describes a mixed equilibrium where autonomous vehicles follow the Cournot-Nash (CN) principle and RVs follow the user equilibrium (UE) principle. In the upper-level model, signal timings are optimized at signalized intersections to allocate appropriate green times to both autonomous and RVs to minimize system travel cost. The sensitivity analysis based method is used to solve the bilevel optimization model. Various signal control strategies are evaluated through numerical examples and some insightful findings are obtained. It was found that the number of phases at intersections should be reduced for the optimal control of the AVs and RVs in the mixed networks. More importantly, incorporating AVs into the transportation network would improve the system performance due to the value of AV technologies in reducing random delays at intersections. Meanwhile, travelers prefer to choose AVs when the networks turn to be congested.

Time-Dependent Discrete Transportation Network Design

2014 ◽  
Vol 505-506 ◽  
pp. 533-536
Author(s):  
Yang Wang ◽  
Jin Xin Cao ◽  
Xia Xi Li ◽  
Ri Dong Wang
Keyword(s):  
Network Design ◽  
Transportation Network ◽  
Optimal Solution ◽  
User Equilibrium ◽  
Static Model ◽  
Time Dependent ◽  
Actual Situation ◽  
Long Time ◽  
Level Model ◽  
Dependent Transport

The transportation network construction takes place over a quite long time span and need enough budget. The budget is from the allocation of funds in phases and the construction cost change in the process of the construction. The general static transportation network design problems ignores the problems above. So the optimal solution obtained by the static model is best in short time, and it is may be unfeasible in the actual situation. Based on the actual situation and the shortage of the static model, the time-dependent transport network design is proposed in this study. The plan horizon is divided into N intervals and a bi-level model is built to describe the problem. The objective of the upper-level is to minimize the total cost of the whole stages. the lower-level model is a user equilibrium model. Then the branch and bound (B-B) algorithm is designed to solve the model. It is obvious that the solution of the time-dependent simulation model is more feasible than the solution of the static sequential design.

Research on Uncertain Network Design Problem

2014 ◽  
Vol 505-506 ◽  
pp. 613-618
Author(s):  
Yang Wang ◽  
Jin Xin Cao ◽  
Ri Dong Wang ◽  
Xia Xi Li
Keyword(s):  
Stochastic Model ◽  
Network Design ◽  
Design Problem ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Construction Costs ◽  
Travel Costs ◽  
Uncertain Network ◽  
Level Model ◽  
Discrete Network Design Problem

In this study, a kind of uncertain network design problem, network design problem under uncertain construction cost, is researched.The discrete network design problem under uncertain construction costs deals with the selection of links to be added to the existing network, so as to minimize the total travel costs in the network. It is assumed that the value of the demand between each pair of origin and destination is a constant and the construction costs of each potential link addition follow a certain stochastic distribution. In this paper, a bi-level and stochastic programming model for the discrete network design problem is proposed. The construction costs of potential links are assumed as random variables and mutually independent with each other in this model. The upper-level model is a chance constrain model with the objective function of minimizing the total travel costs in the network, and the lower-level model is a user equilibrium model. The stochastic model is then transformed into a deterministic one. A branch-and-bound solution algorithm is designed to solve the deterministic model in an efficient way. At last, a computational experiment is conducted to illustrate the effectiveness and efficiency of the approach proposed in this paper. The results show that the stochastic model is more flexible and practical compared with the deterministic one.

scholarly journals Bi-Level Model for Public Rail Transportation under Incomplete Data

2017 ◽  
Vol 17 (3) ◽  
pp. 75-91 ◽  
Author(s):  
Kristina Pavlova ◽  
Todor Stoilov ◽  
Krasimira Stoilova
Keyword(s):  
Incomplete Data ◽  
Optimization Problem ◽  
Transportation Network ◽  
Flow Distribution ◽  
Rail Transport ◽  
Rail Transportation ◽  
Maximal Flow ◽  
Level Model ◽  
Upper Level ◽  
Transportation Flows

Abstract The increase of the utilization of public rail transportations is searched in directions for redistribution of the passenger travels between rail and bus transportation. The rail transport benefits by redistribution of the transportation flows on paths, predominantly supported by rails. The redistribution of the transportation is formalized by bi-level optimization problem. The upper level optimization estimates the maximal flow, which can be transported through a transportation network, supported both by bus and rail transports. The lower level optimization gives priority to the rail transport by decreasing the costs of flow distribution, using rail transport. This bi-level optimization problem was applied for the case of optimization of the rail exploitation in Bulgaria, defining priorities in transportation of the National transport scheme.

scholarly journals The Shrinking of Beijing and the Rising of Xiong’an: Optimize Population Migration in terms of Transport Service

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Hongzhi Lin
Keyword(s):  
Bilevel Programming ◽  
Central Government ◽  
Programming Model ◽  
Service Level ◽  
User Equilibrium ◽  
Population Migration ◽  
Transport Service ◽  
Level Model ◽  
Upper Level ◽  
Bilevel Programming Model

The population of Beijing has already come to its loading capacity. The China central government plans to build an ideal city named Xiong’an nearby Beijing. The city is expected to work as a carrying hub for noncapital functions of Beijing. The central government does not rush to build before a deliberated urban planning is accomplished. For sustainable development, a difficulty faced by urban planners is that the maximum number of people can be migrated from Beijing to Xiong’an with constraint on level of transport service. This paper developed a specialized bilevel programming model where the upper level is to ensure a predetermined transport service level regarding to population migration, while the lower level is feedback equilibrium between trip generation and traffic assignment. To be more specific, trip is generated by the gravity model, and traffic is assigned by the user equilibrium model. It is well known that the bilevel programming problem is tough and challenging. A try-and-error algorithm is designed for the upper-level model, and a method of successive average (MSA) is developed for the lower-level model. The effectiveness of the model and algorithm is validated by an experimental study using the current transport network between Beijing and Xiong’an. It shows that the methods can be very useful to identify the maximum population migration subject to level of transport service.

scholarly journals Continuous Network Design Based on the Paired Combinatorial Logit Stochastic User Equilibrium Model

2014 ◽  
Vol 8 (1) ◽  
pp. 316-322
Author(s):  
Xuefei Li ◽  
Maoxiang Lang
Keyword(s):  
Network Design ◽  
Objective Function ◽  
Equilibrium Model ◽  
Design Problem ◽  
Programming Model ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Stochastic User Equilibrium ◽  
Level Model ◽  
The Impact

In order to design the traffic network more accurately, the bi-level programming model for the continuous network design problem based on the paired combinatorial Logit stochastic user equilibrium model is proposed in this study. In the model, the paired combinatorial Logit stochastic user equilibrium model which is used to characterize the route choice behaviors of the users is adopted in the lower level model, and the minimum summation of the system total costs and investment amounts is used in the upper objective function. The route-based self-regulated averaging (SRA) algorithm is designed to solve the stochastic user equilibrium model and the genetic algorithm (GA) is designed to get the optimal solution of the upper objective function. The effectiveness of the proposed combining algorithm which contains GA and SRA is verified by using a simple numerical example. The solutions of the bi-level models which use the paired combinatorial Logit stochastic user equilibrium model in the lower level model with different demand levels are compared. Finally, the impact of the dispersion coefficient parameter which influences the decision results of the network design problem is analyzed.

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.

Bus Priority Network Design Based on Bi-Level Programming

2015 ◽  
Vol 744-746 ◽  
pp. 1782-1785 ◽  
Author(s):  
Yi Kui Mo ◽  
Kai Wang ◽  
Shen Lv
Keyword(s):  
Network Design ◽  
Solution Algorithm ◽  
Bus Priority ◽  
Level Model ◽  
Upper Level ◽  
Bus Transportation

This paper analyzes the steps and difficulties of bus priority network design, including the bi-level characteristics of problems related to bus priority network design. Based on that, a bi-level model with the maximization of the overall bus transportation efficiency as the upper level and the minimization of bus passengers’ cost as the lower level is established and the solution algorithm of the model is studied.

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