Next Article in Journal
Stress-Testing Food Security in a Socio-Ecological System: Qatar’s Adaptive Responses to Sequential Shocks
Previous Article in Journal
Entrepreneurial Orientation and Firm Performance: A Digital Innovation Opportunity Transformation Framework in Emerging Markets
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Systems
Volume 14
Issue 1
10.3390/systems14010045
systems-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Investigating User Acceptance of Autonomous Vehicles in Developing Cities Using Machine Learning: Lessons from Alexandria, Egypt

by
Sherif Shokry
1,*,
Ahmed Mahmoud Darwish
2,*,
Hazem Mohamed Darwish
3,
Omar Elsnossy Ibrahim
4,
Maged Zagow
5,
Marwa Elbany
6 and
Usama Elrawy Shahdah
7
1
The Center of Road Traffic Safety, Naif Arab University for Security Sciences, Riyadh 11452, Saudi Arabia
2
Department of Transportation Engineering, Faculty of Engineering, Alexandria University, Alexandria 21533, Egypt
3
Civil Engineering Department, Faculty of Engineering, Alexandria University, Alexandria 21533, Egypt
4
Faculty of Engineering, Port Said University, Port Said 42526, Egypt
5
Department of Architecture Engineering, Faculty of Engineering, Tanta University, Tanta 31527, Egypt
6
Department of Civil Engineering, Faculty of Engineering, Port Said University, Port Said 42526, Egypt
7
Public Works Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt
*
Authors to whom correspondence should be addressed.
Systems 2026, 14(1), 45; https://doi.org/10.3390/systems14010045
Submission received: 21 November 2025 / Revised: 11 December 2025 / Accepted: 17 December 2025 / Published: 31 December 2025
(This article belongs to the Special Issue AI Applications in Transportation and Logistics)
Versions Notes

Abstract

The willingness to adopt Autonomous Vehicles (AVs) represents a crucial advancement from the sustainable mobility perspective. This is progressively continuing in the developed countries. A comparable shift is expected in developing nations; however, empirical studies remain limited, especially in areas where AVs have not yet been deployed. This study investigates the willingness to adopt AVs in a developing city where AVs have not been deployed yet. A comprehensive travel behavior questionnaire was conducted among local commuters in Alexandria, Egypt, to identify the influential variables affecting AV choice. The well-known machine learning classifier, Extreme Gradient Boosting (XGB), was employed to develop a forecasting model, which indicated a notable accuracy. The results indicated that trip cost was the most influential feature. On the other hand, there is a considerable level of mode captivity, since most travelers prefer to remain with their current mode, regardless of the effects of other variables. A significant share of travelers expressed concerns about shifting to AVs due to safety worries associated with the travel behavior of other transportation modes’ commuters. The analysis provides nuanced perspectives on the variables promoting modal shift toward the AVs, supporting future policies for smart urban mobility.
Keywords: Autonomous Vehicles (AVs); human-driven vehicles (HDVs); Extreme Gradient Boosting (XGB); Machine Learning (ML); transportation choice modelling Autonomous Vehicles (AVs); human-driven vehicles (HDVs); Extreme Gradient Boosting (XGB); Machine Learning (ML); transportation choice modelling

Share and Cite

MDPI and ACS Style

Shokry, S.; Darwish, A.M.; Darwish, H.M.; Ibrahim, O.E.; Zagow, M.; Elbany, M.; Shahdah, U.E. Investigating User Acceptance of Autonomous Vehicles in Developing Cities Using Machine Learning: Lessons from Alexandria, Egypt. Systems 2026, 14, 45. https://doi.org/10.3390/systems14010045

AMA Style

Shokry S, Darwish AM, Darwish HM, Ibrahim OE, Zagow M, Elbany M, Shahdah UE. Investigating User Acceptance of Autonomous Vehicles in Developing Cities Using Machine Learning: Lessons from Alexandria, Egypt. Systems. 2026; 14(1):45. https://doi.org/10.3390/systems14010045

Chicago/Turabian Style

Shokry, Sherif, Ahmed Mahmoud Darwish, Hazem Mohamed Darwish, Omar Elsnossy Ibrahim, Maged Zagow, Marwa Elbany, and Usama Elrawy Shahdah. 2026. "Investigating User Acceptance of Autonomous Vehicles in Developing Cities Using Machine Learning: Lessons from Alexandria, Egypt" Systems 14, no. 1: 45. https://doi.org/10.3390/systems14010045

APA Style

Shokry, S., Darwish, A. M., Darwish, H. M., Ibrahim, O. E., Zagow, M., Elbany, M., & Shahdah, U. E. (2026). Investigating User Acceptance of Autonomous Vehicles in Developing Cities Using Machine Learning: Lessons from Alexandria, Egypt. Systems, 14(1), 45. https://doi.org/10.3390/systems14010045

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop