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Development of composite motorcycling safety index for addressing motorcycle crash in Malaysia


Citation

Tan, Ai Ping (2020) Development of composite motorcycling safety index for addressing motorcycle crash in Malaysia. Doctoral thesis, Universiti Putra Malaysia.

Abstract

Motorcycle is a popular private transportation mode in developing ASEAN countries due to affordability and ease of door-to-door mobility. Although motorcycle in Malaysia represented 46% of all registered vehicles, motorcycle riders and pillions contributed to 65% of all road crash fatalities. Furthermore, the majority of fatalities occurred among individuals ageing from 16 to 25 years old. Notably, these fatalities majorly involved motorcycles on the road as a result of the interaction between vulnerable road users and other motor vehicles under mixed traffic condition. It is appreciated that roads are designed based on the characteristics of the design vehicle/driver, specifically the automobiles. However, in countries with high motorcycle number, the road designed for automobiles should be shared with the motorcycles, which leads to road crash as the motorcyclists get entangled with other vehicles. Given the expectation that motorcyclists share the roads with other mixed vehicles, a better understanding of motorcycle riders’ perception of traffic and road environment variables affecting safe motorcycling is essential for creating a safer riding environment. Notably, an effective engineering measure to address motorcycle safety in mixed traffic conditions is by segregating motorcycle along the roadways. Although this idea may be applied along full or partial access control roadways, it may not be feasible on trunk roads and arterial roads due to the substantial number of access points, short links, and limitations in road space from the linear developments. The first phase of this study involved a literature review to identify the variables relating to road users’ safety perception on the traffic and roadway segments. The variables referred to safe motorcycling along with the road segments. To corroborate the identified variables with the actual perception of motorcycle riders in Malaysia, the questionnaires related to the variables affecting safe motorcycling were answered by 137 motorcycle riders. The identified variables included mixed traffic volume, travelling speed, lane width, paved shoulder, type of roadway (with or without median), presence of parking, and pavement conditions. To further understand the seven variables from the aspect of motorcycle riders’ perception, the respondents were requested to rate 14 short video clips were presented to 483 respondents in the second phase of this study. The respondents were requested to rate each video clip based on their perception of safe motorcycling. The possibility for the respondents’ perceived safety in different scenarios of the variables was ascertained. The motorcycling safety index was computed while the composite motorcycling safety index was established based on 114 combinations of summation of the variables under different safety condition. The lowest composite motorcycling safety index value of 5.81 inferred that motorcycling was performed in an unsafe condition, while the composite motorcycling safety index value of 58.01 indicated the safest motorcycling roadway segment. The findings of this study may serve as the basis for authorities, traffic planners, and engineers with a scientific perspective to measure and prioritise the aspects of importance, which should be addressed to improve the safety of motorcyclist and reduce the number of motorcycle crashes and fatalities in Malaysia.


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Additional Metadata

Item Type: Thesis (Doctoral)
Subject: Vehicles - Safety measures
Subject: Motorcycles - Malaysia
Call Number: FK 2021 46
Chairman Supervisor: Associate Professor Hussain Hamid, PhD
Divisions: Faculty of Engineering
Depositing User: Editor
Date Deposited: 05 Jul 2022 08:45
Last Modified: 05 Jul 2022 08:45
URI: http://psasir.upm.edu.my/id/eprint/97866
Statistic Details: View Download Statistic

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