Analysis and forcaset of road safety using big data / Yan Tianyu

Yan, Tianyu (2021) Analysis and forcaset of road safety using big data / Yan Tianyu. Masters thesis, Universiti Malaya.

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      With the rapid development of China's economy and the urbanization advancement speeding up unceasingly, the motor vehicle ownership across the country are rapidly expanding and urban road system is also becoming increasingly complex. . Consequently, all kinds of traffic violations and the traffic safety problem is widespread, and this has created great trouble to majority of the people who wish to travel safely. All the above have brought great challenges to urban public traffic management. Road traffic behavior safety has a very serious impact on urban traffic running state. It is desired for the Department of Traffic Management to predict the occurrence of traffic accidents before they happen. With the advancement of existing positioning and communication technology, spatiotemporal data of vehicles can be accurately recorded and stored in the transportation platform. In this project clustering analysis of spatiotemporal data of vehicles is carried out through unsupervised learning to obtain normal and abnormal vehicle trajectories. A safety prediction model is established for the abnormal vehicle trajectory in the mid-term to effectively promote the application of big data in road traffic safety management, and put forward relevant strategies and suggestions to improve the efficiency of road traffic

      Item Type: Thesis (Masters)
      Additional Information: Research Report (M.A) - Faculty of Engineering, Universiti Malaya, 2021.
      Uncontrolled Keywords: Traffic safety; Big data; Cluster analysis
      Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
      Divisions: Faculty of Engineering
      Depositing User: Mrs Rafidah Abu Othman
      Date Deposited: 18 Mar 2024 06:19
      Last Modified: 18 Mar 2024 06:19

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