Modeling of Backward Elimination in Order to Estimate Demand in Rural Areas (Case Study: Qazvin Villages)

<div>In any transportation planning, including rural transportation, the characteristics of existing supply and demand must be identified. According to this knowledge, the main needs and problems of the villagers in the field of transportation can be identified. In urban transportation planning, travel models are usually built in four stages. In the first stage, travel production and absorption models, in the second stage, travel distribution models, in the third stage, vehicle mode choice models, and in the final stage, route selection and traffic assignment models. In this study, and according to the studies conducted on the difference in behavioral pattern as well as the difference in the way of planning in the village and city, modeling related to the stage of production and absorption of travel is done using backward elimination regression. This study was conducted by case study of a number of villages in Qazvin city and can be generalized to other villages that have similar characteristics. Finally, according to the developed models, it was found that in work trips, the variable of employment rate, in educational trips, the number of students, in shopping trips and ethnics and medicine and in the demand of total travel variable population have the greatest impact on the model. With the current situation demand, it is possible to develop a forecast demand model for different horizons by applying the population growth rate and employment. By estimating the demand for travel, in order to create and build road and rural facilities, road pavement and road maintenance can be planned.</div>

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-04
DOI
https://doi.org/10.22034/jcema.2024.197497
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
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article

Modeling of Backward Elimination in Order to Estimate Demand in Rural Areas (Case Study: Qazvin Villages)

Zenodo (CERN European Organization for Nuclear Research)
Urban and Freight Transport Logistics
article

Modeling of Backward Elimination in Order to Estimate Demand in Rural Areas (Case Study: Qazvin Villages)

article en

Abstract

<div>In any transportation planning, including rural transportation, the characteristics of existing supply and demand must be identified. According to this knowledge, the main needs and problems of the villagers in the field of transportation can be identified. In urban transportation planning, travel models are usually built in four stages. In the first stage, travel production and absorption models, in the second stage, travel distribution models, in the third stage, vehicle mode choice models, and in the final stage, route selection and traffic assignment models. In this study, and according to the studies conducted on the difference in behavioral pattern as well as the difference in the way of planning in the village and city, modeling related to the stage of production and absorption of travel is done using backward elimination regression. This study was conducted by case study of a number of villages in Qazvin city and can be generalized to other villages that have similar characteristics. Finally, according to the developed models, it was found that in work trips, the variable of employment rate, in educational trips, the number of students, in shopping trips and ethnics and medicine and in the demand of total travel variable population have the greatest impact on the model. With the current situation demand, it is possible to develop a forecast demand model for different horizons by applying the population growth rate and employment. By estimating the demand for travel, in order to create and build road and rural facilities, road pavement and road maintenance can be planned.</div>

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 52%
Urban and Freight Transport Logistics
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