RedEye: Preventing Collisions Caused by Red-Light Running Scooters With Smartphones

In this paper, the authors present a scooter collision avoidance system that can identify red-light runners (RLRs) at intersections. When the RLR behavior is detected, the system would advise the RLR to slow down immediately and warn nearby vehicles on the intersecting road in real time. In particular, the authors do not consider infrastructure-based solutions such as those utilizing a radar or a camera. This is because, in addition to high implementation costs, collisions can be only avoided at intersections where such infrastructure configurations are deployed. Instead, they advance an on-scooter solution using smartphones carried by scooter riders. Smartphones provide a useful platform that has a high penetration rate, more than sufficient computational power, inertial sensors to reflect the driving behavior, and the communication capability to transmit or receive information from other vehicles. In the authors' system, they utilize a support vector machine and design an RLR classifier for learning and predicting RLR behaviors. The evaluation results show that their system is able to achieve over 70% recognition rates when distinguishing between RLR and non-RLR cases, as compared with approximately 80% recognition rates of the infrastructure-based (and higher cost) solution using a laser range finder (LADAR).


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  • Accession Number: 01601104
  • Record Type: Publication
  • Files: TLIB, TRIS
  • Created Date: May 3 2016 9:07AM