Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network

The area rate of the toll road network is designed to influence the regional road network traffic flow configuration and an important factor of goods vehicle path selection, transportation, and other related departments in formulating the related standard. The toll rate is usually combined with the...

Full description

Saved in:
Bibliographic Details
Main Authors: Hua Zhao, Zifeng Peng, Zhihong Li, Weiting Yao
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2022/8668808
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832564054789455872
author Hua Zhao
Zifeng Peng
Zhihong Li
Weiting Yao
author_facet Hua Zhao
Zifeng Peng
Zhihong Li
Weiting Yao
author_sort Hua Zhao
collection DOAJ
description The area rate of the toll road network is designed to influence the regional road network traffic flow configuration and an important factor of goods vehicle path selection, transportation, and other related departments in formulating the related standard. The toll rate is usually combined with the local passenger and cargo loading conditions. Adjusting and optimizing the charge policy, optimization of processes and methods is still facing many difficulties. In this paper, the model parameters and toll status of various goods vehicles are considered, and an optimization algorithm of toll rates for different vehicles in a large-scale road network is proposed. By constructing a traffic demand prediction model based on multiple truck classification, this paper analyzes the distribution status of network trucks and the final charging under the influence of different rates. At the bottom of the algorithm is an analytical model composed of nonlinear equations whose dimensions scale linearly with the scale of the road network. The scale of the road network is independent of the path set and link attribute. The model is verified and the parameters are calibrated by a small network. Finally, the Road network is selected for empirical analysis in Xinjiang Autonomous Region. A case study shows that the analytical structure information provided by the analytic network model enables the algorithm to quickly identify high quality solutions, and the algorithm has better simulation accuracy and premium rate design advantages.
format Article
id doaj-art-57f91d2fc9764ddfb76681b991ad0b6c
institution Kabale University
issn 2042-3195
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Journal of Advanced Transportation
spelling doaj-art-57f91d2fc9764ddfb76681b991ad0b6c2025-02-03T01:11:54ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/8668808Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale NetworkHua Zhao0Zifeng Peng1Zhihong Li2Weiting Yao3Jiangxi Transportation Institute Co., LtdJiangxi Transportation Engineering Group Co., LtdSchool of Civil and Transportation EngineeringSchool of Civil and Transportation EngineeringThe area rate of the toll road network is designed to influence the regional road network traffic flow configuration and an important factor of goods vehicle path selection, transportation, and other related departments in formulating the related standard. The toll rate is usually combined with the local passenger and cargo loading conditions. Adjusting and optimizing the charge policy, optimization of processes and methods is still facing many difficulties. In this paper, the model parameters and toll status of various goods vehicles are considered, and an optimization algorithm of toll rates for different vehicles in a large-scale road network is proposed. By constructing a traffic demand prediction model based on multiple truck classification, this paper analyzes the distribution status of network trucks and the final charging under the influence of different rates. At the bottom of the algorithm is an analytical model composed of nonlinear equations whose dimensions scale linearly with the scale of the road network. The scale of the road network is independent of the path set and link attribute. The model is verified and the parameters are calibrated by a small network. Finally, the Road network is selected for empirical analysis in Xinjiang Autonomous Region. A case study shows that the analytical structure information provided by the analytic network model enables the algorithm to quickly identify high quality solutions, and the algorithm has better simulation accuracy and premium rate design advantages.http://dx.doi.org/10.1155/2022/8668808
spellingShingle Hua Zhao
Zifeng Peng
Zhihong Li
Weiting Yao
Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network
Journal of Advanced Transportation
title Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network
title_full Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network
title_fullStr Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network
title_full_unstemmed Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network
title_short Differentiated Toll Optimization on Goods Vehicles Based on Prediction of Demand for Large-Scale Network
title_sort differentiated toll optimization on goods vehicles based on prediction of demand for large scale network
url http://dx.doi.org/10.1155/2022/8668808
work_keys_str_mv AT huazhao differentiatedtolloptimizationongoodsvehiclesbasedonpredictionofdemandforlargescalenetwork
AT zifengpeng differentiatedtolloptimizationongoodsvehiclesbasedonpredictionofdemandforlargescalenetwork
AT zhihongli differentiatedtolloptimizationongoodsvehiclesbasedonpredictionofdemandforlargescalenetwork
AT weitingyao differentiatedtolloptimizationongoodsvehiclesbasedonpredictionofdemandforlargescalenetwork