The Pattern Feature Study Of Road Traffic Accident Of The Great Britain

Dynamics of human behavior has been extensively studied in recent years. Road traffic as an important part of human life reflects how human behavior affects social security. But most information is hidden under the surface of the rough data, and needs in-depth research. As a typical complex system of road traffic system, the basic elements include roads, regions, vehicles, time and person. For the pattern of the road traffic accidents, particularly the temporal correlation and scaling behavior, currently there are few relevant research results. Therefore, it is essential to study the behavior pattern of road traffic accidents.Firstly, we study the time pattern of traffic accidents, and the paroxysmal has been found with the time interval. By rescaling the probability distribution and time intervals,the scaling curve is found to deviate from the Gaussian distribution, but it is well fitted by a stretched exponential function. By researching the time interval series with autocorrelation function and DFA analysis of road traffic accident, Long range time correlation is revealed for the interevent series. Gender similarity is found for the small accidental intervals, while for the large intervals, the female drivers are observed to present a higher probability than the male drivers, Moreover, by researching accidental rate in different time periods, the possible reason of gender difference is found in accidents.Secondly, we study the spatial pattern of traffic accidents. Compared with the time mode feature of traffic accidents, the spatial pattern of traffic accident region has its own unique character. By studying the spatial distance of the accident, the scaling curve is found to deviate from the Gaussian distribution, but it is well fitted by the Weibull distribution. By studying autocorrelation coefficient and DFA exponent of the accident spatial interval series, spatial interval sequence is found to have no long-range correlation.