Towards Better Driver Safety: Empowering Personal Navigation Technologies with Road Safety Awareness

June 05, 2020 Β· Declared Dead Β· πŸ› 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

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Authors Runsheng Xu, Shibo Zhang, Yue Zhao, Peixi Xiong, Allen Yilun Lin, Brent Hecht, Jiaqi Ma arXiv ID 2006.03196 Category cs.HC: Human-Computer Interaction Citations 4 Venue 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) Last Checked 4 months ago
Abstract
Recent research has found that navigation systems usually assume that all roads are equally safe, directing drivers to dangerous routes, which led to catastrophic consequences. To address this problem, this paper aims to begin the process of adding road safety awareness to navigation systems. To do so, we first created a definition for road safety that navigation systems can easily understand by adapting well-established safety standards from transportation studies. Based on this road safety definition, we then developed a machine learning-based road safety classifier that predicts the safety level for road segments using a diverse feature set constructed only from large-scale publicly available geographic data. Evaluations in four different countries show that our road safety classifier achieves satisfactory performance. Finally, we discuss the factors to consider when extending our road safety classifier to other regions and potential new safety designs enabled by our road safety predictions.
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