Citation

Khoo HL, Ahmed M. Accid. Anal. Prev. 2018; 113: 106-116.

Affiliation

Department of Civil Engineering, LKC Faculty of Engineering and Science, Universiti Tunku Abdul Rahman (UTAR), Building KB, Level 8, Room 17(2), Jalan Sungai Long, Bandar Sungai Long, 43000 Kajang, Selangor, Malaysia.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.aap.2018.01.025

PMID

29407657

Abstract

This study had developed a passenger safety perception model specifically for buses taking into consideration the various factors, namely driver characteristics, environmental conditions, and bus characteristics using Bayesian Network. The behaviour of bus driver is observed through the bus motion profile, measured in longitudinal, lateral, and vertical accelerations. The road geometry is recorded using GPS and is computed with the aid of the Google map while the perceived bus safety is rated by the passengers in the bus in real time. A total of 13 variables were derived and used in the model development. The developed Bayesian Network model shows that the type of bus and the experience of the driver on the investigated route could have an influence on passenger's perception of their safety on buses. Road geometry is an indirect influencing factor through the driver's behavior. The findings of this model are useful for the authorities to structure an effective strategy to improve the level of perceived bus safety. A high level of bus safety will definitely boost passenger usage confidence which will subsequently increase ridership.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Language: en

Keywords

Bayesian network; Bus accident; Traffic safety