LAUSR

Lane change is a valuable piece of traffic information. An abnormally high number of lane changes on a road section typically suggests that some lanes are blocked due to traffic incidents. Currently, the lane change information of vehicles on an urban road is typically obtained from over-roadway fixed sensors such as surveillance cameras. However, using fixed sensors has limitations in terms of cost and coverage. It is more effective to collect the lane change information directly from each individual vehicle. In addition, lane changing behavior of a driver can help assess his driving risk. One convenient way to detect a lane change directly from each vehicle is to take advantage of sensors on smart mobile devices such as smartphones. In this paper, we explore a new way to identify a lane change event based on a pattern of steering wheel angles detected by a smartphone. This is distinguishable from all of the existing steering wheel-based lane change detection methods, which need to retrieve the steering wheel angle signal from the On-board Diagnostic (OBD) port of the vehicle via the Controller Area Network-Bus (CAN-Bus). In addition, unlike others, our method does not require a lot of complex features to make an accurate detection. In fact, we demonstrate that a high level of accuracy can already be attained with a single simple feature called rotation span. Results show that the proposed detection method performs very well both in terms of precision and recall.