Issue |
E3S Web Conf.
Volume 347, 2022
2nd International Conference on Civil and Environmental Engineering (ICCEE 2022)
|
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Article Number | 01019 | |
Number of page(s) | 12 | |
Section | Infrastructure and Building Construction | |
DOI | https://doi.org/10.1051/e3sconf/202234701019 | |
Published online | 14 April 2022 |
Conceptual intelligent travel demand modelling framework for universities - Case study: King Abdulaziz University
Department of Civil and Environmental Engineering, Jeddah, Kingdom of Saudi Arabia
* Corresponding author: alaasindi@gmail.com
King Abdulaziz University provides its educational services to over 180 thousand students. The number of vehicles entering and existing the university’s reached 350 thousand vehicles per day; Based on that, the transportation network within and around the campus experiences high vehicles delay. The first step to deal with the issue is by developing a conceptual travel demand modelling framework, which set the map for developing the travel demand models. This research presents a conceptual travel demand modelling framework, which is divided into four stages: define the evaluation time period (short, mid, long time span), establish a data collection program, prioritize transportation issues at campus, and model the transportation issues and propose solutions. The university has various departments. Each one contributes to the transportation movement by one way or the other. The framework incorporates these departments in the modelling framework with the aid of technology with the aim of relieving the pressure on the university’s transportation network in a timely manner and with minimum cost. Implementation of this modelling framework showed that management strategies supported with specialized transportation studies will accomplish that aim, while in the same time, it will ensure a sustainable transportation system, and improve the quality of life.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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