Road safety is a critical issue the world-over, and the problem is particularly acute in developing countries, where the combination of crowding, inadequate roads, and driver indiscipline serves up a deadly cocktail. We believe that mobile devices can play a positive role in this context by detecting dangerous conditions and providing feedback to enable timely redressal of potential dangers. This paper focuses on a specific problem that is responsible for many accidents in developing countries: the stopping behaviour of buses especially in the vicinity of bus stops. For instance, buses could arrive at a bus stop but continue rolling forward instead of coming to a complete halt, or could stop some distance away from the bus stop, possibly even in the middle of a busy road. Each of these behaviours can result in injury or worse to people waiting at a bus stop as well as to passengers boarding or alighting from buses. We present FullStop, a smartphone-based system to detect safety risks arising from bus stopping behaviour, as described above. We show that the GPS and inertial sensors are unable to perform the fine-grained detection needed, by themselves. Therefore, FullStop is based on the view obtained from looking out to the front of the vehicle using the camera of a smartphone that is mounted on the front windshield. Using optical flow vectors, with several refinements, FullStop running on a smartphone is able to effectively detect safety-related situations such as a rolling stop or stopping at a location that is displaced laterally relative to the designated bus stop.<\/p>\n","protected":false},"excerpt":{"rendered":"
Road safety is a critical issue the world-over, and the problem is particularly acute in developing countries, where the combination of crowding, inadequate roads, and driver indiscipline serves up a deadly cocktail. We believe that mobile devices can play a positive role in this context by detecting dangerous conditions and providing feedback to enable timely 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