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.

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.

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 Commute Equilibrium for Mixed Networks with Autonomous Vehicles and Traditional Vehicles

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Yangbeibei Ji ◽  
Mingwei Xu ◽  
Hua Wang ◽  
Chaowu Tan
Keyword(s):  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
User Equilibrium ◽  
Analytical Models ◽  
Sensitivity Analyses ◽  
Queuing Delay ◽  
Travel Costs ◽  
Traffic Pattern ◽  
Schedule Delay ◽  
Mixed Networks

Recent development of autonomous vehicle (AV) provides new travel opportunities for citizens, and traditional vehicles (TVs) will still be used for a long time. Therefore, it is highly possible that both AVs and TVs will be used as travel modes in a city. In a transportation system with both AVs and TVs, the traffic pattern is worthy of studying. This paper investigates user equilibrium traffic pattern based on the traditional bottleneck model considering AVs and TVs. For both TVs and AVs, travel costs include queuing delay and schedule delay. However, they also have different components of travel costs; more specifically, for AVs, passengers have to pay a riding fare, and, for TVs, travelers encounter a walking time cost after parking their cars. For different combinations of travel demands and riding fare of AVs, analytical solutions of three different user equilibrium traffic patterns are obtained. Finally, numerical examples are provided to demonstrate the usefulness of the analytical models. Sensitivity analyses are examined to show the impacts of AV’s time-dependent fee and trip-based fixed fee on the traffic pattern and travel costs.

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.

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.

scholarly journals An MPCC Formulation and Its Smooth Solution Algorithm for Continuous Network Design Problem

2017 ◽  
Vol 29 (6) ◽  
pp. 569-580
Author(s):  
Guangmin Wang ◽  
Junwei Yu ◽  
Shubin Li
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Transportation Network ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Total System ◽  
Complementarity Constraints ◽  
Mathematical Programs ◽  
Investment Cost ◽  
Non Linear

Continuous network design problem (CNDP) is searching for a transportation network configuration to minimize the sum of the total system travel time and the investment cost of link capacity expansions by considering that the travellers follow a traditional Wardrop user equilibrium (UE) to choose their routes. In this paper, the CNDP model can be formulated as mathematical programs with complementarity constraints (MPCC) by describing UE as a non-linear complementarity problem (NCP). To address the difficulty resulting from complementarity constraints in MPCC, they are substituted by the Fischer-Burmeister (FB) function, which can be smoothed by the introduction of the smoothing parameter. Therefore, the MPCC can be transformed into a well-behaved non-linear program (NLP) by replacing the complementarity constraints with a smooth equation. Consequently, the solver such as LINDOGLOBAL in GAMS can be used to solve the smooth approximate NLP to obtain the solution to MPCC for modelling CNDP. The numerical experiments on the example from the literature demonstrate that the proposed algorithm is feasible.

scholarly journals Optimum Location of Autonomous Vehicle Lanes: A Model Considering Capacity Variation

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Sara Movaghar ◽  
Mahmoud Mesbah ◽  
Meeghat Habibian
Keyword(s):  
Travel Time ◽  
Autonomous Vehicles ◽  
Transition Period ◽  
Transportation Network ◽  
Autonomous Vehicle ◽  
Planning Horizon ◽  
Bilevel Optimization ◽  
Network Design Problem ◽  
Variable Capacity ◽  
Total Travel Time

This paper proposes a model to find the optimal location of autonomous vehicle lanes in a transportation network consisting of both Autonomous Vehicles (AVs) and Human-Driven Vehicles (HDVs) while accounting for the roadway capacity variation. The main contribution of the model is considering a generalized definition of capacity as a function of AV proportion on a link and incorporating it into the network design problem. A bilevel optimization model is proposed with total travel time as the objective function to be minimized. At the upper-level problem, the optimal locations of AV lanes are determined, and at the lower level which is a multiclass equilibrium assignment, road users including both AVs and HDVs seek to minimize their individual travel times. It is shown that if capacity variation is ignored, the effect of AV lane deployment can be misleading. Since there will be a long transition period during which both AVs and HDVs will coexist in the network, this model can help the network managers to optimally reallocate the valuable road space and better understand the effects of AV lane deployment at the planning horizon as well as during the transition period. Employing this model as a planning tool presents how the proposed AV lane deployment plan could consider the AV market penetration growth during the transition period. Numerical analysis based on the Sioux Falls network is presented in two cases with and without variable capacity to illustrate the application of this model. At the 60% penetration rate of AVs, the improvement in total travel time was 3.85% with a fix capacity while this improvement was 9.88% with a variable capacity.

scholarly journals Designing Vehicle Turning Restrictions Based on the Dual Graph Technique

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Lihui Zhang ◽  
Hongsheng Qi ◽  
Dianhai Wang ◽  
Zhong Wang ◽  
Jian Yang
Keyword(s):  
Travel Time ◽  
Heuristic Algorithm ◽  
Design Problem ◽  
Transportation Network ◽  
Dual Graph ◽  
User Equilibrium ◽  
Total System ◽  
Nonlinear Constraints ◽  
Dual Transformation

This paper investigates the turning restriction design problem that optimizes the turning restriction locations so as to minimize the total system travel time under the assumption of asymmetric user equilibrium. We first transform a transportation network into a dual graph, where traffic turning movements are explicitly modeled as dual links. The dual transformation allows us to derive a link-based formulation for the turning restriction design problem. Asymmetric user equilibrium is incorporated in the model as a set of nonlinear constraints. A dual-based heuristic algorithm is employed to solve the problem, by sequentially solving a relaxed turning restriction design problem and a design updating problem.

Cordon-Based Pricing Schemes for Mixed Urban-Freeway Networks using Macroscopic Fundamental Diagrams

2021 ◽  
pp. 036119812110159
Author(s):  
Xuting Wang ◽  
Vikash V. Gayah
Keyword(s):  
Control Strategies ◽  
User Equilibrium ◽  
Real Time Control ◽  
Urban Networks ◽  
Time Control ◽  
The Difference ◽  
Freeway Networks ◽  
Mixed Networks ◽  
Urban Freeway ◽  
Pricing Schemes

The development of traffic models based on macroscopic fundamental diagrams (MFD) enables many real-time control strategies for urban networks, including cordon-based pricing schemes. However, most existing MFD-based pricing strategies are designed only to optimize the traffic-related performance, without considering the revenue collected by operators. In this study, we investigate cordon-based pricing schemes for mixed networks with urban networks and freeways. In this system, heterogeneous commuters choose their routes based on the user equilibrium principle. There are two types of operational objective for operating urban networks: (1) to optimize the urban network’s performance, that is, to maximize the outflux; and (2) to maximize the revenue for operators. To compare those two objectives, we first apply feedback control to design pricing schemes to optimize the urban network’s performance. Then, we formulate an optimal control problem to obtain the revenue-maximization pricing scheme. With numerical examples, we illustrate the difference between those pricing schemes.

scholarly journals A Traffic Flow Evolution Process toward Mixed Equilibrium with Multicriteria of Route Choice Behaviour

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiangjun Jiang ◽  
Zhongxiang Huang ◽  
Zhenyu Zhao
Keyword(s):  
Equilibrium State ◽  
Traffic Flow ◽  
Complete Information ◽  
User Equilibrium ◽  
Evolution Model ◽  
Choice Behaviour ◽  
Flow Evolution ◽  
Quantity Adjustment ◽  
Mixed Equilibrium ◽  
Equilibrium Pattern

Based on the price-quantity adjustment behaviour principle of disequilibrium theory, the route choices of travellers are also affected by a quantity signal known as traffic flow, while the route cost is considered as a price signal in economics. Considering the quantity signal’s effect among travellers, a new route comfort choice behaviour criterion and its corresponding equilibrium condition are established. The network travellers are classified into three groups according to their route choice behaviour: travellers in the first group choose the shortest route following the route rapidity behaviour criterion with complete information forming the UE (user equilibrium) pattern, travellers in the second group choose the most comfortable route following the route comfort behaviour criterion with complete information forming the QUE (quantity adjustment user equilibrium) pattern, and travellers in the third group choose a route according to their perceived travel time with incomplete information forming the SUE (stochastic user equilibrium) pattern. The traffic flows of all three groups converge to a new UE-QUE-SUE mixed equilibrium flow pattern after interaction. To depict the traveller-diversified choice behaviour and the traffic flow interaction process, a mixed equilibrium traffic flow evolution model is formulated. After defining the route comfort indicator and the corresponding user equilibrium state, the equilibrium conditions of the three group flows are given under a mixed equilibrium pattern. In addition, an equivalent mathematical programming of the mixed equilibrium traffic flow evolution model is proposed to demonstrate that the developed model converges to the mixed equilibrium state. Finally, numerical examples are examined to evaluate the effect of route comfort proportions on the traffic network flow evolution and analyse the performance of the proposed model.

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