Traffic Demand Model to Study Urban Agglomeration Transportation System

2014 ◽  
Vol 587-589 ◽  
pp. 1805-1808
Author(s):  
Cheng Bing Li ◽  
Rui Xue Guo ◽  
Min Li ◽  
Jian Chao Wang
Keyword(s):  
Travel Demand ◽  
Demand Management ◽  
Transportation System ◽  
Urban Traffic ◽  
Urban Agglomeration ◽  
Demand Model ◽  
Traffic Demand ◽  
Core Content

The determination of traffic demand for urban transportation system is one of the core content of urban traffic planning, it is the basis for the traffic demand management strategy. First of all, the paper expounds the concept of urban agglomeration and features, on this basis, the traffic supply and traffic demand of urban agglomeration transportation system is analyzed. Second, according to land area for urban residents travel demand, according to the classification of goods transport industry production requirements were determined, thus to construct a system of urban agglomeration transportation traffic demand model.

scholarly journals Network Design Algorithm Implementation for Resilient Transportation System under Continuous Risk Perturbation with Big Data Analysis

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Hongxiao Wang ◽  
Qiang Li ◽  
Sang-Bing Tsai
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Motor Vehicle ◽  
Transportation System ◽  
Urban Traffic ◽  
Distribution Model ◽  
Elastic Demand ◽  
Demand Model ◽  
Design Algorithm ◽  
Traffic Demand

With the rapid economic development and urbanization process accelerating, motor vehicle ownership in large cities is increasing year by year; urban traffic congestion, parking difficulties, and other problems are becoming increasingly serious; in ordinary daily life, continuous risk of disturbance, having a flexible transportation system network is more able to alleviate daily congestion in the city, and the main thing about flexible transportation network is its algorithm. It is worth noting that congestion in many cities is generally reflected in the main roads, while many secondary roads and branch roads are underutilized, and the limited road resources in cities are not fully utilized. As an economic and effective road traffic management measure, one-way traffic can balance the spatial and temporal distribution of traffic pressure within the road network, make full use of the existing urban road network capacity, and solve the traffic congestion problem. Therefore, it is of great theoretical and practical significance to develop a reasonable and scientific one-way traffic scheme according to the characteristics of traffic operation in different regions. Based on the fixed demand model, the influence of traffic demand changes is further considered, the lower-level model is designed as an elastic demand traffic distribution model, the excess demand method is used to transform the elastic demand problem into an equivalent fixed demand problem based on the extended network, and the artificial bee colony algorithm based on risk perturbation is designed to solve the two-level planning model. The case study gives a one-way traffic organization optimization scheme that integrates three factors, namely, the average load degree overload limit of arterial roads, the detour coefficient, and the number of on-street parking spaces on feeder roads, and performs sensitivity analysis on the demand scaling factor.

Research on the Urban Transportation Development in Our Country Based on the Traffic Congestion Pricing

2011 ◽  
Vol 97-98 ◽  
pp. 1032-1037
Author(s):  
Wei Kou ◽  
Lin Cheng
Keyword(s):  
Traffic Congestion ◽  
Marginal Cost ◽  
Demand Management ◽  
Urban Transportation ◽  
Congestion Pricing ◽  
Developed Countries ◽  
Urban Traffic ◽  
Theory And Practice ◽  
Traffic Demand ◽  
Transportation Development

With the development and realization of industrialization and urbanization in the world, urban traffic volume grows rapidly; many big cities face more and more serious traffic problem. As a mean of traffic demand management, traffic congestion pricing has important significance in theory and practice. Traffic congestion pricing can counteract external diseconomy caused by network congestion, and the price of congestion is tantamount to the difference between social marginal cost and private marginal cost. This paper analyzes the economic theory of congestion pricing. Combined the effect of traffic congestion pricing that implemented in the developed countries, it researches the influence of urban transportation development in our country in the future based on the implementing congestion pricing.

Path Reconstruction of Intelligent Traffic Based on Positive Feedback System

2014 ◽  
Vol 513-517 ◽  
pp. 3160-3164
Author(s):  
Xue Li Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Intelligent Systems ◽  
Supply And Demand ◽  
Demand Management ◽  
Reference Value ◽  
Feedback System ◽  
Urban Traffic ◽  
Urban Transport ◽  
Traffic Demand

Traffic congestion are prevalent in worldwide cities. The imbalance between demand and supply of urban traffic is the root cause of this problem. So taking effective measures to regulate traffic demand, and guiding the traffic problems of the supply and demand balance is the best way to solve traffic congestion. This paper improves the TDM measure, and combines with intelligent information platform for the design of a new urban transport demand management adaptability of dynamic traffic data analysis platform. The platform supported by the technology of wireless sensor communications, intelligent terminals, the Internet and cloud computing is facing with the dynamic needs of traffic flow and traffic congestion state to carry out the operations of spatiotemporal data mining, clustering, and track detection, and to apply it into the traffic hot spots, abnormal driving track, traffic congestion trends and traffic flow detection and analysis, which has a good reference value for the improvement of management and service level of traffic intelligent systems.

scholarly journals Strategic Development of Transportation Demand Management in Jordan

2019 ◽  
Vol 5 (1) ◽  
pp. 48 ◽  
Author(s):  
Basim Jrew ◽  
Majed Msallam ◽  
Mona Momani
Keyword(s):  
Fuel Consumption ◽  
Urban Areas ◽  
Travel Demand ◽  
Demand Management ◽  
System Management ◽  
Transportation Demand Management ◽  
Strategic Development ◽  
Transportation Demand ◽  
Traffic Demand ◽  
Urban Population Growth

The urban population growth and increase in a number of vehicles have affected the travel demand on Jordan Streets. The study aims to apply the Transportation Demand Management (TDM) policies to reduce the traffic flow in urban areas and improve the Level of Service (LOS). A group of a combination between TDM and Transportation System Management (TSM) strategies have been conducted, when TDM strategies were not successful to improve LOS. TSM concept refers to any group of actions that increase the capacity of roads network. Synchro 8 software was used to analyse the intersection conditions as important point, connecting two main arterial street in Amman area. A significant reduction in delay and fuel consumption was measured, but there was no real enhancement in LOS. The LOS was improved, when traffic demand was reduced by 20% and capacity was increased with 6 lanes on each approach for the existing conditions. The percentage of saving in fuel consumption and delay was observed to be around 64% and 63%, respectively for the next 5 years.

scholarly journals Impact assessment of short-term management measures on travel demand

2020 ◽  
Vol 53 (1) ◽  
pp. 37-52
Author(s):  
Jinit J. M. D’Cruz ◽  
Anu P. Alex ◽  
V. S. Manju ◽  
Leema Peter
Keyword(s):  
Travel Demand ◽  
Public Transit ◽  
Demand Management ◽  
Simulation Software ◽  
Demand Model ◽  
Short Term ◽  
Travel Demand Management ◽  
Management Measures ◽  
The Impact ◽  
Travel Demand Model

Travel Demand Management (TDM) can be considered as the most viable option to manage the increasing traffic demand by controlling excessive usage of personalized vehicles. TDM provides expanded options to manage existing travel demand by redistributing the demand rather than increasing the supply. To analyze the impact of TDM measures, the existing travel demand of the area should be identified. In order to get quantitative information on the travel demand and the performance of different alternatives or choices of the available transportation system, travel demand model has to be developed. This concept is more useful in developing countries like India, which have limited resources and increasing demands. Transport related issues such as congestion, low service levels and lack of efficient public transportation compels commuters to shift their travel modes to private transport, resulting in unbalanced modal splits. The present study explores the potential to implement travel demand management measures at Kazhakoottam, an IT business hub cum residential area of Thiruvananthapuram city, a medium sized city in India. Travel demand growth at Kazhakoottam is a matter of concern because the traffic is highly concentrated in this area and facility expansion costs are pretty high. A sequential four-stage travel demand model was developed based on a total of 1416 individual household questionnaire responses using the macro simulation software CUBE. Trip generation models were developed using linear regression and mode split was modelled as multinomial logit model in SPSS. The base year traffic flows were estimated and validated with field data. The developed model was then used for improving the road network conditions by suggesting short-term TDM measures. Three TDM scenarios viz; integrating public transit system with feeder mode, carpooling and reducing the distance of bus stops from zone centroids were analysed. The results indicated an increase in public transit ridership and considerable modal shift from private to public/shared transit.

scholarly journals Solving Traffic Congestion through Street Renaissance: A Perspective from Dense Asian Cities

Urban Science ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 18 ◽  
Author(s):  
Liang Wen ◽  
Jeff Kenworthy ◽  
Xiumei Guo ◽  
Dora Marinova
Keyword(s):  
Land Use Planning ◽  
Traffic Congestion ◽  
Travel Demand ◽  
Supply And Demand ◽  
Demand Management ◽  
Holistic Approach ◽  
Residential Areas ◽  
Travel Demand Management ◽  
Traffic Demand ◽  
Work Related

Traffic congestion is one of the most vexing city problems and involves numerous factors which cannot be addressed without a holistic approach. Congestion cannot be narrowly tackled at the cost of a city’s quality of life. Focusing on transport and land use planning, this paper examines transport policies and practices on both the supply and demand sides and finds that indirect travel demand management might be the most desirable solution to this chronic traffic ailment. The concept of absorption of traffic demand through the renaissance of streets as a way for traffic relief is introduced from two perspectives, with some examples from dense Asian urban contexts to demonstrate this. Firstly, jobs–housing balance suggests the return of production activities to residential areas and sufficient provision of diverse space/housing options to deal with work-related traffic. The second approach is to promote the street as a multi-activity destination rather than a thoroughfare to access dispersed daily needs, and to advocate more street life to diminish non-commuting traffic. Based on this, suggestions for better transport planning policies are put forward.

scholarly journals IF-MABAC Method for Evaluating the Intelligent Transportation System with Intuitionistic Fuzzy Information

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yanping Li
Keyword(s):  
Financial Management ◽  
Intelligent Transportation System ◽  
Travel Demand ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Urban Traffic ◽  
Distance Measures ◽  
Effective Control ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy

Intelligent transportation system (ITS) is the development direction of the future traffic system. ITS can effectively employ the existing traffic facilities and ensure the safety of traffic, urban traffic, and public security management for effective control in order to satisfy people’s travel demand. Therefore, the results of the system in-depth understanding and objective evaluation are very necessary. And it is frequently regarded as a multiattribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is required to tackle it. Depending on the conventional multiattributive border approximation area comparison (MABAC) method and intuitionistic fuzzy sets (IFSs), this article designs a novel intuitive distance-based IF-MABAC method to assess the performance of financial management. First of all, a related literature review is conducted. Furthermore, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing the maximizing deviation method. Afterwards, relying on novel distance measures between intuitionistic fuzzy numbers (IFNs), the conventional MABAC method is extended to the IFSs to calculate the final value of each enterprise. Therefore, all enterprises can be ranked, and the one with the best environmental behaviors and awareness can be identified. Eventually, an application for evaluating the intelligent transportation system and some comparative analyses have been given. The results illustrate that the designed algorithm is useful for assessing the performance of financial management.

scholarly journals Development of an urban travel demand model of the Town of Oakville

2021 ◽  
Author(s):  
Lukasz Pawlowski
Keyword(s):  
Data Management ◽  
Travel Demand ◽  
Transportation Network ◽  
Demand Model ◽  
Traffic Demand ◽  
University Of Toronto ◽  
Transportation Modelling ◽  
Microcomputer Software ◽  
The Town ◽  
Travel Demand Model

This dissertation documents the development of a travel demand model of the Town of Oakville. The purpose of the model was to predict traffic demand on study area roadways during the morning peak hour. The model focused on the prediction of auto driver trips. The model was developed based on the 1996 Transportation Tomorrow Survey data, available from the Data Management Group at the University of Toronto. The model was developed in accordance with the Urban Transportation Modelling System (UTMS) of models. Activities included: Trip Generation, Trip Distribution, and Trip Assignment. Accounting for Mode Split was unnecessary as the model focused only on auto driver trips. The final product of the model is a set of traffic flows over links in the transportation network. The model was developed using TransCAD transportation GIS (Geographic Information System) software. TransCAD is a microcomputer software specifically designed for transportation planning and data management.

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