Abstract
Abstract This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to develop the model of multiple linear regression (MLR) with the stepwise regression technique in the SPSS v25 software. The results indicate that the model of trip generation is related to family size and composition, gender, students’ number in the family, workers’ number in the family, and car ownership. The ANN prediction model is more accurate than the MLR predicted model: the average accuracy (AA) was 83.72% in the ANN model but only 72.46% in the MLR model.
Highlights
Transportation is defined to be the movement of people, goods, and services from one place to another during a desirable condition, whereas transport planning is interested in the development of a plan with respect to the economic, social, and environmental effects of the populace to enhance the positive objectives
The fundamental aim of transportation planning is to accommodate the requirement for mobility in order to provide effective access to different activities that satisfy human needs
To simplify the collection of data in the transportation planning process, the research region is divided into a set of zones that are subdivided to assist in geographically connecting the origin and destination of the trip
Summary
Urban transport is a multidimensional concept and a part of metropolitan mobility that combines the movement of merchandise, inhabitants, and information between urban regions [1]. The fundamental aim of transportation planning is to accommodate the requirement for mobility in order to provide effective access to different activities that satisfy human needs. These reasons make it important to prepare comprehensive analyses of the regions in order to establish the origins of these journeys and determine the origin and destination of these journeys in order to create statistical models to forecast the movement of these journeys. Trip demand refers to the group of individuals or vehicles that could be expected to move on a given section of a transportation network during a given time span, based on land use, social, economic, and environmental variables. Forecasting of trip demand estimates the number, type, and origin of “trips” (source and target) on the transportation network
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