Crowdriving:Detection of Safe Driving Via Crowd Sensing

Yun Du, Xin Guo, Chenyang Shi, Yifan Zhu, Bohan Li

This work is supported by National Natural Science Foundation of China (61672284, 41301407), Funding of Security Ability Construction of Civil Aviation Administration of China (AS-SA2015/21), Fundamental Research Funds for the Central Universities (NJ20160028, NT2018028, NS2018057).

In this project, we tried to detect extreme driving behavior by adopting CrowdSensing, and then synthesized the results of group decision based on Bayesian voting theory to get a more accurate result. Considering the application scenario, we combined the above functions with other additional functions in an Android APP for our campus shuttle bus. The application scenario can be extended to today’s shared mobility to ensure the safety of drivers and passengers.

Details could be seen in our paper .