scholarly journals Optimizing capacity of signalized road network with reversible lanes

Transport ◽  
2015 ◽  
Vol 33 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Jian Wang ◽  
Wei Deng
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Flow Direction ◽  
Network Capacity ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Mixed Network ◽  
Level Problem ◽  
Upper Level

This paper studies the network capacity problem on signalized road network with reversible lanes. A Mixed Network Design Problem (MDNP) is formulated to describe the problem where the upper-level problem is a mixed integer non-linear program designed to maximize the network capacity by optimizing the input parameters (e.g. the signal splits, circles, reassigned number of lanes and O–D demands), while the lower-level problem is the common Deterministic User Equilibrium (DUE) assignment problem formulated to model the drivers’ route choices. According to whether one way strategy is permitted in practice, two strategies for implementing reversible roadway are considered. In the first strategy, not all lanes are reversible and the reversible roadways always hold its ability to accommodate the two-way traffic flow. In the second strategy, one-way road is allowed, which means that all the lanes are reversible and could be assigned to one flow direction if the traffic flow in both directions is severally unsymmetrical. Genetic Algorithm (GA) is detailedly presented to solve the bi-level network capacity problem. The application of the proposed method on a numerical example denotes that Strategy 2 can make more use of the physical capacity of key links (signal controlled links), thus, the corresponding network capacity outperforms it is of Strategy 1 considerably.

Reserve Capacity of Mixed Urban Road Networks, Network Configuration and Signal Settings

2018 ◽  
pp. 883-906
Author(s):  
Masoomeh Divsalar ◽  
Reza Hassanzadeh ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri
Keyword(s):  
Mathematical Problem ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Reserve Capacity ◽  
Heuristic Methods ◽  
Mixed Network ◽  
Proposed Model ◽  
Level Problem ◽  
Upper Level

The authors formulate the transportation mixed network design problem (MNDP) as a mixed-integer bi-level mathematical problem, based on the concept of reserve capacity. The upper level goal is to maximize the reserve capacity by signal settings at intersections, determine street direction and increase street capacities via addition of lanes. The lower level problem is a deterministic user equilibrium traffic assignment problem to minimize the user travel time. The model being non-convex, meta-heuristic methods are used to solve the problem. A hybridization of genetic algorithm with simulated annealing and a bee algorithm are proposed. Numerical examples are illustrated to verify the effectiveness of the proposed model and the algorithms.

Reserve Capacity of Mixed Urban Road Networks, Network Configuration and Signal Settings

2017 ◽  
Vol 4 (1) ◽  
pp. 44-64 ◽  
Author(s):  
Masoomeh Divsalar ◽  
Reza Hassanzadeh ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri
Keyword(s):  
Mathematical Problem ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Reserve Capacity ◽  
Network Configuration ◽  
Mixed Network ◽  
Proposed Model ◽  
Level Problem ◽  
Upper Level

The authors formulate the transportation mixed network design problem (MNDP) as a mixed-integer bi-level mathematical problem, based on the concept of reserve capacity. The upper level goal is to maximize the reserve capacity by signal settings at intersections, determine street direction and increase street capacities via addition of lanes. The lower level problem is a deterministic user equilibrium traffic assignment problem to minimize the user travel time. The model being non-convex, meta-heuristic methods are used to solve the problem. A hybridization of genetic algorithm with simulated annealing and a bee algorithm are proposed. Numerical examples are illustrated to verify the effectiveness of the proposed model and the algorithms.

scholarly journals Charging station planning based on the accumulation prospect theory and dynamic user equilibrium

2021 ◽  
Author(s):  
Qiu Heting ◽  
Dou Shuihai ◽  
Shang Huayan ◽  
Zhang Jun
Keyword(s):  
Travel Time ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Traffic Equilibrium ◽  
Charging Station ◽  
Level Model ◽  
Upper Level ◽  
Generalized Cost ◽  
Range Limitation

AbstractThis study investigates the electric vehicle (EV) traffic equilibrium and optimal deployment of charging locations subject to range limitation. The problem is similar to a network design problem with traffic equilibrium, which is characterized by a bilevel model structure. The upper level objective is to optimally locate charging stations such that the total generalized cost of all users is minimized, where the user’s generalized cost includes two parts, travel time and energy consumption. The total generalized cost is a measure of the total societal cost. The lower level model seeks traffic equilibrium, in which travelers minimize their individual generalized cost. All the utilized paths have identical generalized cost while satisfying the range limitation constraint. In particular, we use origin-based flows to maintain the range limitation constraint at the path level without path enumeration. To obtain the global solution, the optimality condition of the lower level model is added to the upper level problem resulting in a single level model. The nonlinear travel time function is approximated by piecewise linear functions, enabling the problem to be formulated as a mixed integer linear program. We use a modest-sized network to analyze the model and illustrate that it can determine the optimal charging station locations in a planning context while factoring the EV users’ individual path choice behaviours.

scholarly journals Determining Optimal Link Capacity Expansions in Road Networks Using Cuckoo Search Algorithm with Lévy Flights

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Ozgur Baskan
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Search Algorithm ◽  
Road Networks ◽  
Cuckoo Search ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Lévy Flights ◽  
Link Capacity ◽  
Levy Flights

During the last two decades, Continuous Network Design Problem (CNDP) has received much more attention because of increasing trend of traffic congestion in road networks. In the CNDP, the problem is to find optimal link capacity expansions by minimizing the sum of total travel time and investment cost of capacity expansions in a road network. Considering both increasing traffic congestion and limited budgets of local authorities, the CNDP deserves to receive more attention in order to use available budget economically and to mitigate traffic congestion. The CNDP can generally be formulated as bilevel programming model in which the upper level deals with finding optimal link capacity expansions, whereas at the lower level, User Equilibrium (UE) link flows are determined by Wardrop’s first principle. In this paper, cuckoo search (CS) algorithm with Lévy flights is introduced for finding optimal link capacity expansions because of its recent successful applications in solving such complex problems. CS is applied to the 16-link and Sioux Falls networks and compared with available methods in the literature. Results show the potential of CS for finding optimal or near optimal link capacity expansions in a given road network.

scholarly journals Cordon- or Link-Based Pricing: Environment-Oriented Toll Design Models Development and Application

2019 ◽  
Vol 11 (1) ◽  
pp. 258 ◽  
Author(s):  
Xijie Li ◽  
Ying Lv ◽  
Wei Sun ◽  
Li Zhou
Keyword(s):  
Road Network ◽  
Network Performance ◽  
Evaluation Method ◽  
User Equilibrium ◽  
Mixed Integer ◽  
Emissions Reduction ◽  
Pricing Models ◽  
Modeling Framework ◽  
Design Models ◽  
Congestion Mitigation

This study focuses on an environment-friendly toll design problem, where an acceptable road network performance is promised. First, a Traffic Performance Index (TPI)-based evaluation method is developed to help identify the optimal congestion level and the management target of a transportation system. Second, environment-oriented cordon- and link-based road toll design models are respectively proposed through the use of bi-level programming. Both upper-level submodel objectives are to minimize gross revenue (the total collected toll minus the emissions treatment cost) under different pricing strategies. Both lower-level submodels quantify the user equilibrium (UE) condition under elastic demand. Moreover, the TPI-related constraints for the management requirements of the network performance are incorporated into the bi-level programming modeling framework, which can lead to 0–1 mixed integer bi-level nonlinear programming for toll design problems. Accordingly, a genetic algorithm-based heuristic searching method is proposed for the two pricing models. The proposed cordon- and link-based pricing models were then applied to a real-world road network in Beijing, China. The effects of the toll schemes generated from the two models were compared in terms of emissions reduction and congestion mitigation. In this study, it was indicated that a higher total collected toll may lead to more emissions and related treatment costs. Tradeoffs existed between the toll scheme, emissions reduction, and congestion mitigation.

Highway Alignment Optimization Using Cost-Benefit Analysis Under User Equilibrium

2013 ◽  
pp. 313-327 ◽  
Author(s):  
Avijit Maji ◽  
Manoj K. Jha
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
User Equilibrium ◽  
User Cost ◽  
Benefit Analysis ◽  
Road Design ◽  
Highway Alignment Optimization ◽  
Highway Alignment

Usually, selection of a highway alignment depends on an economical route that minimizes alignment sensitive costs, such as construction cost, user cost, right-of-way cost, and earthwork cost. Most of the available highway alignment optimization algorithms do not consider traffic assignment and distribution of traffic as a result of the new road network consisting of the new alignment as well as other pre-existing alignments. Constructing a new highway will ease the traffic in the existing road network. Based on Wardrop’s principle, the users will choose a route that will minimize their travel-time. Users will unilaterally shift to the available routes for their benefit and thus, traffic flow will attain equilibrium. Theoretically, the equilibrium of traffic flow between the existing highway and the newly designed highway alternative can be achieved by a user equilibrium model. A new methodology is developed in this paper to optimize a new three-dimensional highway alignment based on the existing highway alignment system information using a cost-benefit analysis approach. The results are quite promising for new road design and bypass construction since benefit maximization and cost minimization is performed simultaneously while attaining user equilibrium.

Cascade defense in urban road network by inserting modular topologies

Kybernetes ◽  
2014 ◽  
Vol 43 (5) ◽  
pp. 750-763 ◽  
Author(s):  
Zhiyun Zou ◽  
Jinlong Wu ◽  
Jianzhi Gao ◽  
Xuecai Xu
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Random Network ◽  
Small World ◽  
User Equilibrium ◽  
Cascading Failures ◽  
Urban Road Network ◽  
Content Type ◽  
Urban Road ◽  
Critical Components

Purpose – By aiming at defending cascade failures effectively, the purpose of this paper is to present a strategy of inserting modular topologies into urban road network through reducing the burdens of critical components with too much traffic flow. Design/methodology/approach – Each module is considered as a small-world random network, which is inserted into the initial Barabási-Albert scale-free network. Based on the user-equilibrium assignment, the strategy searches for remote nodes with low betweeness and flow in the network, and sets these nodes to be connected with the modular topologies. In this sense, the inserted modules are supposed to attach to the nodes with lower intensity of shorter path, and avoid bringing more impact to the nodes with higher betweeness and traffic flow. By using efficiency as the measurement of cascading failures, the performance of the networks generated through the strategy is tested. Findings – The results show that the performance of the strategy is sensitive to the average degree of the inserted modular, and the modular size with a better effect on reducing the size of cascading failures or delaying the time of breakdown, while the other factors (e.g. the rewired probability) present few differences among various values. Meanwhile, it is found that the importance-based attachment mechanism has a better effect on preventing the cascading failures, especially delaying the step time of the larger reduction. Practical implications – The strategy aims at alleviating the burdens in critical components to prevent the cascading failures of the network, and provides practical guidance on the decision of the urban road network evolving process. Originality/value – An effective strategy for cascade defense in urban road network is proposed in this paper.

Highway Alignment Optimization Using Cost-Benefit Analysis Under User Equilibrium

2011 ◽  
Vol 2 (4) ◽  
pp. 19-33 ◽  
Author(s):  
Avijit Maji ◽  
Manoj K. Jha
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Cost Benefit Analysis ◽  
Cost Minimization ◽  
Cost Benefit ◽  
User Equilibrium ◽  
User Cost ◽  
Benefit Analysis ◽  
Highway Alignment Optimization ◽  
Highway Alignment

Usually, selection of a highway alignment depends on an economical route that minimizes alignment sensitive costs, such as construction cost, user cost, right-of-way cost, and earthwork cost. Most of the available highway alignment optimization algorithms do not consider traffic assignment and distribution of traffic as a result of the new road network consisting of the new alignment as well as other pre-existing alignments. Constructing a new highway will ease the traffic in the existing road network. Based on Wardrop’s principle, the users will choose a route that will minimize their travel-time. Users will unilaterally shift to the available routes for their benefit and thus, traffic flow will attain equilibrium. Theoretically, the equilibrium of traffic flow between the existing highway and the newly designed highway alternative can be achieved by a user equilibrium model. A new methodology is developed in this paper to optimize a new three-dimensional highway alignment based on the existing highway alignment system information using a cost-benefit analysis approach. The results are quite promising for new road design and bypass construction since benefit maximization and cost minimization is performed simultaneously while attaining user equilibrium.

scholarly journals Incorporating Variable Demand Assignment Into Discrete Network Design Problem

2020 ◽  
Author(s):  
Alireza Rahimi
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Network Design Problem ◽  
Variable Demand ◽  
Total Cost ◽  
Demand Models ◽  
Level Problem ◽  
Level Method ◽  
Upper Level ◽  
Discrete Network Design Problem

The network design problem (NDP) is a bi-level problem with integer and decimal variables that aims to minimize the users' total cost under the budget constraints. Although utilizing variable demand models will theoretically change the NDP’s result, the demand was assumed to be fixed and known in the literature. In this paper, a mathematical analysis will be presented to justify the importance of using variable demand in the discrete network design problem (DNDP). The DNDP for Sioux-falls network will be solved in both variable and fixed demand conditions by using total enumeration (in the upper-level) and Frank-Wolf (in the lower-level) method. The result shows that DNDP findings for variable and fix demand conditions have significant differences, especially in the mid-budget level.

scholarly journals Transportation Network Design considering Morning and Evening Peak-Hour Demands

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hua Wang ◽  
Gui-Yuan Xiao ◽  
Li-Ye Zhang ◽  
Yangbeibei Ji
Keyword(s):  
Network Design ◽  
Programming Model ◽  
Transportation Network ◽  
User Equilibrium ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Network Efficiency ◽  
Demand Distribution ◽  
Traffic Characteristics ◽  
Evening Peak

Previous studies of transportation network design problem (NDP) always consider one peak-hour origin-destination (O-D) demand distribution. However, the NDP based on one peak-hour O-D demand matrix might be unable to model the real traffic patterns due to diverse traffic characteristics in the morning and evening peaks and impacts of network structure and link sensitivity. This paper proposes an NDP model simultaneously considering both morning and evening peak-hour demands. The NDP problem is formulated as a bilevel programming model, where the upper level is to minimize the weighted sum of total travel time for network users travelling in both morning and evening commute peaks, and the lower level is to characterize user equilibrium choice behaviors of the travelers in two peaks. The proposed NDP model is transformed into an equivalent mixed integer linear programming (MILP), which can be efficiently solved by optimization solvers. Numerical examples are finally performed to demonstrate the effectiveness of the developed model. It is shown that the proposed NDP model has more promising design effect of improving network efficiency than the traditional NDP model considering one peak-hour demand and avoids the misleading selection of improved links.

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