Identification of Road Crashes Characteristics using Data Visualization for Sustainable Campus

• Published in: AIP Conference Proceedings
• Main Author: Mohd Nusa F.N.; Abdul Rahim M.A.; Mohamad N.D.; Ishak S.Z.; Mat Isa C.M.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178030302&doi=10.1063%2f5.0178661&partnerID=40&md5=bcb76dd9168f5b55ded55992e838631e

Road crash cases that cause death and significant injuries have reported to occur in university campuses. The data of these cases such as crash location, collision type, and fatality rate could help understand and identify the road crash profiles on university campuses. This study aimed to achieve two objectives: (1) to identify the road crash blackspots on a university campus and (2) to develop an interactive road crash data visualisation dashboard for the campus. This study applied the crash characteristics and patterns of road crashes on the university campus. Secondary data in this study was retrieved from the campus police. The data were analysed using descriptive and frequency analyses. The results showed that 52% of the road crash cases involved collisions with motorcycles, and 39% were two-vehicle collisions. Most crash cases occurred along the traffic roads that were heavily congested during the peak hours (9 am to 12 pm and 2 pm to 5 pm). These cases were reported as non-severe injuries due to minor collisions. The findings from this study may assist in understanding the road crash data using the interactive data visualisation technique. Thus, this dynamic and informative data visualisation dashboard can be used by police campuses to prepare intervention plans to control and manage future road crashes for a sustainable transportation system on campus. © 2023 American Institute of Physics Inc.. All rights reserved.