Research on dynamic prediction method for traffic demand based on trip generation analysis

Xu, Haijing; Li, Wenyong; Wang, Tao; Yang, An-lei

doi:10.1177/1687814019854561

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…The traffic network supports urban-rural material flow and is the necessary basis for urban-rural integration. Many studies have predicted traffic flow and explained spatial-temporal correlations [77,78], or forecasted traffic volume through a significant number of surveys [79], but their aims were not to explore the spatial layout of the traffic network. According to the simulation result of this study, the traffic network structure of Harbin in 2035 tends to be more complex.…”

Section: Discussionmentioning

confidence: 99%

Simulation of an Urban-Rural Spatial Structure on the Basis of Green Infrastructure Assessment: The Case of Harbin, China

Guo

Bai

2019

Land

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Due to their long-term dual structures and rapid urbanization, cities and villages in developing countries are undergoing the challenges of urban-rural integration and ecological security. This study aims to determine the pattern of urban-rural spatial structures under the circumstances of ecological security in the future to promote the integrated, coordinated, green, and sustainable development of urban-rural spaces. Using a quantitative evaluation method, the logistic-CA model, the LCP (least cost path) model, and a classification of ecological importance, this study constructed an integrated simulation model based on a green infrastructure assessment and applied the model to simulate and predict the urban-rural spatial structure of the Harbin city territory (Harbin) in 2035. The results indicate that the urban-rural hierarchical scale structure of Harbin comprises a central city, sub-central city, central town, major town, common town, central village, and general village. The urban-rural traffic network structure forms a pattern of “radiation + grid”, with Harbin city at the center of the structure. The urban-rural land use zoning structure consists of eco-spaces, agricultural spaces, and construction spaces. It can be concluded that in 2035, the urban-rural spatial structure of Harbin will show an increasing development tendency, where single-center, medium, and small cities in will Harbin develop, and traffic systems above the county level will also improve.

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Section: Discussionmentioning

confidence: 99%

Simulation of an Urban-Rural Spatial Structure on the Basis of Green Infrastructure Assessment: The Case of Harbin, China

Guo

Bai

2019

Land

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“…In many planning works, analytic hierarchy approaches are used to calculate the weights of various indicators in the index evaluation system to calculate the comprehensive score. For example, the main influencing factors of residents' travel in transportation research are summarized and the weight of the travel impact factor in the travel prediction stage was established by the analytic hierarchy method [21]. Their works could be extended to modify the location influence coefficient in the population, land use, and urban travel models to characterize the dynamic state of residents' travel demand in the travel stage.…”

Section: Literature Reviewmentioning

confidence: 99%

A Model Assembly Approach of Planning Urban–Rural Transportation Network: A Case Study of Jiangxia District, Wuhan, China

Zhao

et al. 2023

Sustainability

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Planning transportation networks between urban and rural areas is of crucial importance for the integration of urban and rural development, for socio-economic connectivity, and for sustainable growth. The study offers a model assembly approach in order to logically plan an integrated urban–rural transportation network that may support the coordinated development of its living–production–ecological space. Within this approach, the ordinary least squares (OLS) linear regression analysis method is used to investigate the correlation between urban and rural areas of a transportation network and the influencing factors in the living–production–ecological space so as to objectively analyze their degree of influence. These factors are size of town, urban and rural settlements, life services, supporting transportation facilities, trunk layout, external transport links, cargo hubs, logistics and transportation, enterprise distribution, agricultural production, terrain, distribution of water systems, tourism resources, heritage preservation, and ecological protection. The analytic hierarchy method is used to assign weight to the urban and rural transportation network planning impact index system. As a result, a transportation network planning decision hierarchy model is implemented to identify suitable areas for urban and rural transportation network construction and to provide guidance and reference for planning. Jiangxia District, Wuhan, China is selected as the study area to verify the feasibility and effectiveness of the model. The findings indicate that the influencing factors of urban and rural industrial and ecological space have a significant impact on the transportation network in the research area. Planning should prioritize optimizing the central region’s transportation network structure and enhancing traffic flow between urban and rural communities, which is effectively in line with the current reality. The suggested approach is helpful in establishing case-study-specific planning and development strategies of urban and rural integrated transportation networks in the age of big data, as well as in balancing these influencing factors in living, production, and ecological spaces when planning an integrated urban and rural transportation network.

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“…Hence, future scenarios can be established with higher probability of occurrence. Xu et al (2019) presented a "dynamic" method to forecast traffic demand based on trip generation analysis. Combined with classical demand forecasting method, they used the AHP to evaluate and determine the influence of factors.…”

Section: Fu Et Al 2020mentioning

confidence: 99%

Multi-criteria approach to adjust demand forecast for products: application of analytic hierarchy process

Oliveira

Pacheco

Piratelli

2022

Prod.

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Demand forecasting is related to anticipating future levels of demand for a company's products and/or services. According to Werner & Ribeiro (2006), forecasting is fundamental for structuring the company to determine the quantity of goods or services it will produce so that it can predict and meet the consumer market's demand. With that in mind, Pellegrini & Fogliatto (2001) consider that demand forecasting plays an important role in the strategic planning of production, sales, and finances of organizations in general. For Werner & Ribeiro ( 2006), reliable forecasts require the use of various methods and the largest amount of available information. Based on these definitions, one infers the importance and extent to which demand forecasting is a determining factor for the company's performance in the market as a whole.The company analyzed is a textile industry with an average portfolio of 812 models per collection, supplying products to more than 30 thousand stores in Brazil, besides exporting to such countries as Saudi Arabia,

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Research on dynamic prediction method for traffic demand based on trip generation analysis

Cited by 3 publications

References 13 publications

Simulation of an Urban-Rural Spatial Structure on the Basis of Green Infrastructure Assessment: The Case of Harbin, China

Simulation of an Urban-Rural Spatial Structure on the Basis of Green Infrastructure Assessment: The Case of Harbin, China

A Model Assembly Approach of Planning Urban–Rural Transportation Network: A Case Study of Jiangxia District, Wuhan, China

Multi-criteria approach to adjust demand forecast for products: application of analytic hierarchy process

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