摘要：Based on the driver surveillance video data and controller area network(CAN)data,the methods of studying commercial vehicles’driving behavior is relatively ***,these methods have difficulty in covering private *** driving studies have disadvantages of small sample size and high cost,one new driving behavior evaluation method using massive vehicle trajectory data is put *** automatic encoding machine is used to reduce the noise of raw data,and then driving dynamics and self-organizing mapping(SOM)classification are used to give thresholds or the judgement method of overspeed,rapid speed change,rapid turning and rapid lane *** proportion of different driving behaviors and typical dangerous driving behaviors is calculated,then the temporal and spatial distribution of drivers’driving behavior and the driving behavior characteristics on typical roads are *** behaviors on accident-prone road sections and normal road sections are *** show that in Shenzhen,frequent lane changing and overspeed are the most common unsafe driving behaviors;16.1%drivers have relatively aggressive driving behavior;the proportion of dangerous driving behavior is higher outside the original economic special zone;dangerous driving behavior is highly correlated with traffic accident frequency.

摘要：A double-dimensional big data assessment method on the characteristics of on-line taxi traffic operation is proposed to provide a scientific basis for carrying out the taxi industry reform and standardizing the on-line taxi hailing management work. Taking Shenzhen as an example, multi- source data such as on-line taxi license plate data, plate identification data and taxi （including on-line taxis） operation data are combined with the results of the stated preference （SP） survey on taxi operating characteristics to assess the overall operation characteristics of on-line taxis. The results show that the current on-line taxis in Shenzhen can be divided into three categories, that is, full-time on-line taxis, non- active on-line taxis and part-time on-line taxis, accounting for 4%, 55%, and 41%, respectively, of the total quantity. In terms of the characteristics of space-time operations, full-time on-line taxis have similar operating characteristics as those of traditional taxis; the operation of non-active on-line taxis and part-time on-line taxis coincides with commuting requirements during morning and evening peak hours. however, part-time on-line taxis operate for a much longer time period at night. Due to the convenient hailing and favorable price, on-line taxis have a significant impact on trip modes of citizens; and the substitution eflbct of on-line taxis on traditional buses and cruising taxis is obvious. It is beneficial for helping the government departments to objectively understand the development law of the on-line taxi industry and providing decision reference for the formulation of relevant management policies during the critical development stage of on-line taxi industry.