The invention provides a method for detecting an accidental congestion path. The method comprises the following steps: acquiring global positioning system (GPS) trajectory data of a plurality of vehicles in a research area in a target time period; dividing a road network of the research area into a plurality of path units, and determining road direction information of each path unit according to the obtained GPS track data; determining the average speed difference of each path unit in the current time period according to the GPS track data of the plurality of vehicles in the target time period; determining candidate paths according to the topological relation of each path unit in the road network and the average speed difference of each path unit in the current time period; and judging thesignificance of teach candidate path, and when the significance of the candidate path meets a preset significance level, determining the candidate path as the accidental congestion path. According tothe invention, detection of the accidental congestion path can be completed under the condition of considering the road direction, and the accuracy of the detection of the accidental congestion pathis improved.

Method for detecting accidental congestion path

The invention provides a scenic spot traffic and tourism prediction method and a scenic spot traffic and tourism early warning system. The method includes the following steps that: a time-varying parameter vector autoregressive model is adopted, and correlations between scenic spots in a target area are analyzed; at least one of the scenic spots is selected as a reference scenic spot, the tourismdata and traffic flow data of the reference scenic spot are utilized to construct the scenic spot traffic and tourism index of the reference scenic spot; and the correlations between the scenic spotsand the scenic spot traffic and tourism index predicted result of the reference scenic spot are adopted to predict the traffic and tourism indexes of the other scenic spots in the scenic spots. According to the method and system of the invention, tourism and traffic are combined; correlations and pulse response relationships between scenic spots and traffic are revealed on the basis of data; traffic tourism indexes are constructed and predicted; and the traffic volume change of the scenic spots can be monitored; the traffic and tourism information of the scenic spots can be provided for tourists; and the tourism quality of the tourists can be improved.

Scenic spot traffic and tourism prediction method and early warning system

The invention provides a multi-mode traffic demand influence analysis method, for different areas of public traffic demands and private cars, based on a spatial vector autoregression model. The methodmainly comprises that (1) a multi-mode traffic demand cooperation model among the areas is established, a traditional spVAR model is improved, a regional POI index is introduced to define the spatialweight for the areas of different traffic modes, and a multi-mode traffic demand spatial VAR model including the regional space structural relation is constructed; and (2) a multi-mode traffic demandcooperation strategy of different areas is provided. Pulse response and variance decomposition results of different traffic modes are solved on the basis of the constructed regional multi-mode traffic spatial VAR model, further, a spatial overflow effect of the traffic demands is obtained by analysis, and the cooperative strategy model for different spatial states and traffic states is provided and constructed. It is proved that the model can improve the availability and scientific performance of traffic efficiency.

Zhang Xian

Papers

Multi-mode traffic demand influence analysis method based on spatial vector autoregression model