Dynamic route choice behaviour and simulation-based dynamic traffic assignment model for mixed traffic flows

Hu, Ta-Yin; Tong, Chee Chung; Liao, T. Warren; Chen, Li Wen

doi:10.1007/s12205-017-1025-8

Cited by 16 publications

(12 citation statements)

References 5 publications

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“…(5) Knowledge level of the network: users can be classified by their ability to access real-time traffic information (ATIS). Each class of users attempts to optimize the travel cost based on their information from the network status [46,50,51]. (6) Risk taking attitude: generally speaking, risk, uncertainty, and reliability are three concepts that can be defined for both sides: supplier (traffic network system) and demander (traveler) [52].…”

Section: Discussionmentioning

confidence: 99%

Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case

Ameli

Lebacque

Leclercq

2021

Journal of Advanced Transportation

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This study reviews existing computational methods to calculate simulation-based dynamic network equilibrium. We consider a trip-based multimodal approach for the dynamic network loading. Mode and path choices are carried out at the same level; therefore, travel times depend on the travel path and the mode attributes of travelers. This study develops a multiclass model with several parameters per class. Two different categories of algorithms (heuristic and metaheuristic) are considered in order to solve the discrete dynamic traffic assignment (DTA) problem. Finally, we analyze the equilibrium in a large-scale multimodal DTA test case (Lyon 6th + Villeurbanne) in order to investigate the performance of different optimization approaches to solve trip-based DTA. The results show that, in a multimodal and heterogeneous setting, the metaheuristic methods provide better solutions than the heuristic methods in terms of optimality and computation time. These improvements are even more significant than in a homogeneous setting.

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Section: Discussionmentioning

confidence: 99%

Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case

Ameli

Lebacque

Leclercq

2021

Journal of Advanced Transportation

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“…Travel time is selected as the operating cost because travel time can reflect other travel characteristics, such as fuel consumption. To consider volume when we estimate travel time, we applied a traffic simulation software DynaTAIWAN, proposed by Hu et al ( 15 ). Therefore, the expected travel time of each link is estimated:…”

Section: Methodsmentioning

confidence: 99%

Comparisons of a Multi-Objective Compromise Weight Model and a Multi-Objective Evolutionary Algorithm in Hazmat Transportation Route Planning

Hsu

Liao

2020

Transportation Research Record

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On July 31, 2014, a series of gas pipeline explosions occurred in Kaohsiung City, causing 32 deaths and 321 injuries. Following this accident, the Kaohsiung City government decided to replace the use of pipelines with trucks for transporting hazmat, transfering the risk from beneath the road to the surface. This means that careful consideration needs to be given to safety and cost in hazardous material (hazmat) transportation route planning. The issue of how to design optimal routes for the transportation of hazmat is, therefore, important and involves consideration of various criteria. This research focuses on three objectives: cost, risk, and emergency response capability. It then constructs two solution algorithms, the compromise weight model and the evolutionary algorithm, to solve the multi-objective problem. The results from these two algorithms are observed and compared. In addition, this research also provides some recommendations for stakeholders, including the hazmat industry, government, and residents.

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“…The simulation framework is implemented in the object-oriented approach, and four major modules are developed. Validations of DynaTAIWAN have been conducted in different research projects (Hu et al, 2007;Hu et al, 2008;Liao et al, 2010;Liao et al, 2012). We use DynaTAI-WAN to construct the simulation platform to generate realistic traffic environments and evaluate the proposed routing algorithm through vehicle simulation in the traffic network.…”

Section: Implementation Frameworkmentioning

confidence: 99%

“…The simulation‐assignment model, DynaTAIWAN, is applied within the framework. The emission models are integrated with DynaTAIWAN and the validations of DynaTAIWAN have been conducted in different research projects (Hu et al., ; Hu et al, ; Liao et al., ; Liao et al., ). Numerical results obtained with the proposed models and algorithms for route updates and different levels of on‐level demands are analyzed and compared.…”

Section: Introductionmentioning

confidence: 99%

On‐Line Vehicle Routing Problems for Carbon Emissions Reduction

Liao

2017

Computer aided Civil Eng

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This paper proposes formulations and a hybrid meta‐heuristic algorithm to solve the on‐line vehicle routing problem (VRP) for minimizing costs related to economics and emissions. The on‐line VRP considers real‐time demands. Vehicle emissions are affected by travel speed and vehicle load. A hybrid meta‐heuristic algorithm GA‐Tabu is designed to solve the on‐line VRP and a solution framework using DynaTAIWAN simulation is implemented. The numerical results show CO2 can be reduced by combining the emission factors into the objective function. Also, the route updates for on‐line demands are analyzed and the performance measures of the on‐line VRP are investigated by using various on‐line demands.

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Dynamic route choice behaviour and simulation-based dynamic traffic assignment model for mixed traffic flows

Cited by 16 publications

References 5 publications

Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case

Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case

Comparisons of a Multi-Objective Compromise Weight Model and a Multi-Objective Evolutionary Algorithm in Hazmat Transportation Route Planning

On‐Line Vehicle Routing Problems for Carbon Emissions Reduction

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