Collision Hotspots Identification Based on Big Data about Aggressive Driving Behaviors

Traffic plays a key role in evaluating a country’s development. Urbanization, road construction, and vehicle numbers have increased worldwide, adding to the risk of accidents. Traffic accidents on freeways tend to cause more severe damage than accidents on other types of roads. Identifying collision hotspots on freeways is the first step to preventing crashes. In addition, governments need to allocate funding for safety legislation and supervision. Intelligent methods, such as smartphones, big data, and cloud computing, can be used for traffic safety, identifying hotspots by investigating traffic exposure, road attributes, and weather conditions. This paper analyzes the risk from aggressive driving behavior (ADB), including sudden accelerating, braking, and turning. Data is acquired from a Chinese smartphone application, Amap, owned by AutoNavi Software Company. A big amount of data is used by virtue of cloud computing technology. Results show the reliability of such algorithms to identify traffic accident hotspots on freeways.