scholarly journals Optimal Design of Signal Controlled Road Networks Using Differential Evolution Optimization Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Huseyin Ceylan
Keyword(s):  
Differential Evolution ◽  
Optimization Algorithm ◽  
Performance Index ◽  
Traffic Congestion ◽  
Network Performance ◽  
Harmony Search ◽  
User Equilibrium ◽  
Simulation Software ◽  
Computational Time ◽  
Stochastic User Equilibrium

This study proposes a traffic congestion minimization model in which the traffic signal setting optimization is performed through a combined simulation-optimization model. In this model, the TRANSYT traffic simulation software is combined with Differential Evolution (DE) optimization algorithm, which is based on the natural selection paradigm. In this context, the EQuilibrium Network Design (EQND) problem is formulated as a bilevel programming problem in which the upper level is the minimization of the total network performance index. In the lower level, the traffic assignment problem, which represents the route choice behavior of the road users, is solved using the Path Flow Estimator (PFE) as a stochastic user equilibrium assessment. The solution of the bilevel EQND problem is carried out by the proposed Differential Evolution and TRANSYT with PFE, the so-called DETRANSPFE model, on a well-known signal controlled test network. Performance of the proposed model is compared to that of two previous works where the EQND problem has been solved by Genetic-Algorithms- (GAs-) and Harmony-Search- (HS-) based models. Results show that the DETRANSPFE model outperforms the GA- and HS-based models in terms of the network performance index and the computational time required.

scholarly journals A Multistage Multiobjective Model for Emergency Evacuation Considering ATIS

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Ming-Hua Zeng ◽  
Ke-Jun Long ◽  
Zi-Wen Ling ◽  
Xi-Yan Huang
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Network Performance ◽  
Programming Model ◽  
Choice Model ◽  
Compliance Rate ◽  
Emergency Evacuation ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Traffic Demand

The impacts of advanced traveler information system’s (ATIS’s) penetration and compliance rates on network performances during hybrid traffic emergency evacuation are investigated in a degraded road network. Before traffic incident a Path-Size Logit (PSL) route choice model is integrated with constraints on the level of service (LOS) of traffic to formulate a bilevel programming model. It aims at minimizing traffic demand in road network which may locally deteriorate the LOS. The lower level is a PSL-stochastic user equilibrium model for multiple classes of users. During the ongoing incident, a multiobjective multiuser-class stochastic optimization model is established with the objectives of maximizing evacuation reliability and minimizing expected network travel time. Furthermore, computations and analyses are completed for five designated scenarios including a method proposed in previous literature. The results show that the evacuation reliability and different kinds of total expected travel time costs regularly increase with emergency traffic’s ATIS compliance rate and decrease with general traffic’s ATIS penetration rate. The research will help improve transport network performance when considering ATIS’s effect on hybrid traffic.

scholarly journals Bounding the Inefficiency of the Multiclass, Multicriteria C-Logit Stochastic User Equilibrium in a Transportation Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Lekai Yuan ◽  
Xi Zhang ◽  
Chaofeng Shi
Keyword(s):  
Variational Inequality ◽  
Variational Inequalities ◽  
Stochastic System ◽  
Traffic Congestion ◽  
Transportation Network ◽  
User Equilibrium ◽  
Upper Bounds ◽  
Choice Probability ◽  
Stochastic User Equilibrium ◽  
System Optimum

We derive the exact inefficiency upper bounds of the multiclass C-Logit stochastic user equilibrium (CL-SUE) in a transportation network. All travelers are classified on the basis of different values of time (VOT) into M classes. The multiclass CL-SUE model gives a more realistic path choice probability in comparison with the logit-based stochastic user equilibrium model by considering the overlapping effects between paths. To find efficiency loss upper bounds of the multiclass CL-SUE, two equivalent variational inequalities for the multiclass CL-SUE model, i.e., time-based variational inequality (VI) and monetary-based VI, are formulated. We give four different methods to define the inefficiency of the multiclass CL-SUE, i.e., to compare multiclass CL-SUE with multiclass system optimum, or to compare multiclass CL-SUE with multiclass C-Logit stochastic system optimum (CL-SSO), under the time-based criterion and the monetary-based criterion, respectively. We further investigate the effects of various parameters which include the degree of path overlapping (the commonality factor), the network complexity, degree of traffic congestion, the VOT of user classes, the network familiarity, and the total demand on the inefficiency bounds.

scholarly journals A Stochastic User Equilibrium Model Under Traffic Rationing Based on Mode Shifting Rate

2020 ◽  
Vol 12 (13) ◽  
pp. 5433
Author(s):  
Xueyan Wei ◽  
Wei Wang ◽  
Weijie Yu ◽  
Xuedong Hua ◽  
Yun Xiang
Keyword(s):  
Equilibrium Model ◽  
Traffic Congestion ◽  
Travel Demand ◽  
User Equilibrium ◽  
License Plate ◽  
Stochastic User Equilibrium ◽  
Long Distance ◽  
Traffic Demand ◽  
Proposed Model ◽  
Reasonable Approach

As a countermeasure to urban exhaust pollution and traffic congestion, traffic restriction based on the last digit of license plate numbers has been widely introduced throughout the world. However, the effect of traffic restriction is weakened as it causes the long-distance detour of restricted travel modes and induces travel demand to shift to unrestricted travel modes. To consider detour and shift of traffic demand caused by traffic restriction, we propose a stochastic user equilibrium model under traffic rationing based on mode shifting rate and the corresponding solution algorithm. A case study is conducted to verify the effectiveness of proposed model and algorithm. Main findings of numerical experiments include: (1) Compared with traditional stochastic user equilibrium model, the temporary traffic demand shift caused by long-distance detour are well considered in proposed model. (2) Sensitivity analysis of the consumption parameters used in the proposed model shows that, the involved cost parameters have different effectiveness on the mode shifting rate. This study provides a reasonable relaxation of the intensively used assumption, that all restricted vehicles outside the restricted district will detour in traffic rationing research, and provides a reasonable approach to evaluate the change of link flow and the beneficial effectiveness on the sustainability of traffic environment after implementation of traffic restriction policy.

scholarly journals Dynamic Analysis of Traffic State and Congestion Propagation on Bidirectional Grid Network

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shu-bin Li ◽  
Bai-bai Fu ◽  
Jian-feng Zheng
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Network Performance ◽  
Simulation Software ◽  
Urban Traffic ◽  
Grid Network ◽  
Traffic State ◽  
Proposed Model ◽  
Air Pollutions ◽  
Density Relationship

Many traffic problems in China such as traffic jams and air pollutions are mainly caused by the increasing traffic volume. In order to alleviate the traffic congestion and improve the network performance, the analysis of traffic state and congestion propagation has attracted a great interest. In this paper, an improved mesoscopic traffic flow model is proposed to capture the speed-density relationship on segments, the length of queue, the flow on links, and so forth, The self-developed dynamic traffic simulation software (DynaCHINA) is used to reproduce the traffic congestion and propagation in a bidirectional grid network for different demand levels. The simulation results show that the proposed model and method are capable of capturing the real traffic states. Hence, our results can provide decision supports for the urban traffic management and planning.

scholarly journals Traffic Equilibrium for Mixed Traffic Flows of Human-Driven Vehicles and Connected and Autonomous Vehicles in Transportation Networks under Tradable Credit Scheme

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Fang Zhang ◽  
Jian Lu ◽  
Xiaojian Hu
Keyword(s):  
Autonomous Vehicles ◽  
Network Performance ◽  
Penetration Rate ◽  
User Equilibrium ◽  
Unit Price ◽  
Mixed Traffic ◽  
Traffic Flows ◽  
Stochastic User Equilibrium ◽  
Tradable Credit Scheme ◽  
Tradable Credit

In this paper, the traffic equilibriums for mixed traffic flows of human-driven vehicles (HDV) and connected and autonomous vehicles (CAV) under a tradable credit scheme (TCS) are established and formulated as two variational inequality (VI) problems with exogenous and endogenous CAV penetration rate, respectively. A modified Lagrangian dual (MLD) method embedded with a revised Smith’s route-swapping (RSRS) algorithm is proposed to solve the problems. Based on the numerical analysis, the impacts of CAV penetration and the extra expense of using a CAV on network performance are investigated. A novel driveway management, autonomous vehicle/credit charge (AVCC) link, is put forward to improve the efficiency of TCS. Under the TCS with exogenous CAV penetration rate, a logit-based model is applied to describe the stochastic user equilibrium for mixed traffic flow. It is found that the penetration of CAV gives rise to a better network performance and it can be further improved by the deployment of AVCC link. Under the TCS with endogenous penetration rate, a nested-logit model is applied to describe travelers’ choices of vehicle types and routes. It is found that the deployment of AVCC links can slow down the decline rate of CAV penetration with increasing expense and thus ensure a lower average travel time for CAVs. In both cases, the deployment of AVCC links can stimulate credit trading and drop down its unit price.

scholarly journals Traffic Paradox Under Different Equilibrium Conditions Considering Elastic Demand

2019 ◽  
Vol 31 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Qiang Tu ◽  
Lin Cheng ◽  
Dawei Li ◽  
Jie Ma ◽  
Chao Sun
Keyword(s):  
Traffic Management ◽  
Network Performance ◽  
Transportation Network ◽  
Travel Cost ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Equilibrium Conditions ◽  
Traffic Demand ◽  
Travel Costs ◽  
Cost Sensitivity

Traffic paradox is an important phenomenon which needs attention in transportation network design and traffic management. Previous studies on traffic paradox always examined user equilibrium (UE) or stochastic user equilibrium (SUE) conditions with a fixed traffic demand (FD) and set the travel costs of links as constants under the SUE condition. However, traffic demand is elastic, especially when there are new links added to the network that may induce new traffic demand, and the travel costs of links actually depend on the traffic flows on them. This paper comprehensively investigates the traffic paradox under different equilibrium conditions including the user equilibrium and the stochastic user equilibrium with a fixed and elastic traffic demand. Origin-destination (OD) mean unit travel cost (MUTC) has been chosen as the main index to characterize whether the traffic paradox occurs. The impacts of travelers’ perception errors and travel cost sensitivity on the occurrence of the traffic paradox are also analyzed. The conclusions show that the occurrence of the traffic paradox depends on the traffic demand and equilibrium conditions; higher perception errors of travelers may lead to a better network performance, and a higher travel cost sensitivity will create a reversed traffic paradox. Finally, several appropriate traffic management measures are proposed to avoid the traffic paradox and improve the network performance.

scholarly journals Fuel-Efficient on-Orbit Service Vehicle Allocation Based on an Improved Discrete Particle Swarm Optimization Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Wu Jian ◽  
Liu Qingguo ◽  
Liu Xinxue ◽  
Li Yaxiong
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Performance Index ◽  
Optimization Problem ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Computational Time ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Discrete Particle

Given the limited fuel capacity of an on-orbit service vehicle (OSV), proper OSV allocation to satellites during each service mission is critical for economic fuel consumption. This allocation problem can be formulated as an optimization problem with many continuous and discrete design variables of wide domains. This problem can be effectively handled through the proposed approach that combines the tabu search with the discrete particle swarm optimization algorithm (DPSO-TS). First of all, Pontryagin’s minimum principle and genetic algorithm (GA) are exploited to find the most fuel-efficient transfer trajectory. This fuel efficiency maximization can then serve as the performance index of the OSV allocation optimization model problem. In particular, the maximization of the minimum residual fuel over individual OSVs is proposed as a performance index for OSV allocation optimization. The optimization problem is numerically solved through the proposed DPSO-TS algorithm. Finally, the simulation results demonstrate that the DPSO-TS algorithm has a higher accuracy compared to the DPSO, the DPSO-PDM and the DPSO-CSA algorithms in the premise that these four algorithms have the basically same computational time. The DPSO-TS algorithm can effectively solve the OSV allocation optimization problem.

scholarly journals A robust algorithm to solve the signal setting problem considering different traffic assignment approaches

2017 ◽  
Vol 27 (4) ◽  
pp. 815-826 ◽  
Author(s):  
Ludovica Adacher ◽  
Andrea Gemma
Keyword(s):  
Optimization Algorithm ◽  
Network Performance ◽  
Traffic Assignment ◽  
Transportation Network ◽  
User Equilibrium ◽  
Route Choice Behavior ◽  
Road Congestion ◽  
Stochastic Discrete Optimization ◽  
Flow Propagation ◽  
Real Test

AbstractIn this paper we extend a stochastic discrete optimization algorithm so as to tackle the signal setting problem. Signalized junctions represent critical points of an urban transportation network, and the efficiency of their traffic signal setting influences the overall network performance. Since road congestion usually takes place at or close to junction areas, an improvement in signal settings contributes to improving travel times, drivers’ comfort, fuel consumption efficiency, pollution and safety. In a traffic network, the signal control strategy affects the travel time on the roads and influences drivers’ route choice behavior. The paper presents an algorithm for signal setting optimization of signalized junctions in a congested road network. The objective function used in this work is a weighted sum of delays caused by the signalized intersections. We propose an iterative procedure to solve the problem by alternately updating signal settings based on fixed flows and traffic assignment based on fixed signal settings. To show the robustness of our method, we consider two different assignment methods: one based on user equilibrium assignment, well established in the literature as well as in practice, and the other based on a platoon simulation model with vehicular flow propagation and spill-back. Our optimization algorithm is also compared with others well known in the literature for this problem. The surrogate method (SM), particle swarm optimization (PSO) and the genetic algorithm (GA) are compared for a combined problem of global optimization of signal settings and traffic assignment (GOSSTA). Numerical experiments on a real test network are reported.

scholarly journals Effects of Users’ Bounded Rationality on a Traffic Network Performance: A Simulation Study

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
S. F. A. Batista ◽  
Chuan-Lin Zhao ◽  
Ludovic Leclercq
Keyword(s):  
Bounded Rationality ◽  
Network Performance ◽  
User Behavior ◽  
Dynamic Traffic Assignment ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Aspiration Levels ◽  
Different Types ◽  
Wave Effects ◽  
Search Order

In this paper, we revisit the principle of bounded rationality applied to dynamic traffic assignment to evaluate its influences on network performance. We investigate the influence of different types of bounded rational user behavior on (i) route flows at equilibrium and (ii) network performance in terms of its internal, inflow, and outflow capacities. We consider the implementation of a bounded rational framework based on Monte Carlo simulation. A Lighthill-Whitham-Richards (LWR) mesoscopic traffic simulator is considered to calculate time-dependent route costs that account for congestion, spillback, and shock-wave effects. Network equilibrium is calculated using the Method of Successive Averages. As a benchmark, the results are compared against both Deterministic and Stochastic User Equilibrium. To model different types of bounded rational user behavior we consider two definitions of user search order (indifferent and strict preferences) and two settings of the indifference band. We also test the framework on a toy Braess network to gain insight into changes in the route flows at equilibrium for both search orders and increasing values of aspiration levels.

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