Abstract: The present invention relates to a multi-layer coupling relationship-based train operation deviation propagation condition recognition method, where the method includes the following steps: (1) recognizing an effective train event time sequence, including an arrival event and a departure event of a train at each passing station; (2) uniformly extracting train activity data, including a stop activity, a section operation activity, a turn-back activity, and an arrival or departure interval activity; (3) constructing coupling relationship groups between a train event and a train activity and between train activities; and (4) performing statistics on changes of train operation deviation in each relationship group, and outputting a respective distribution function and a time-space distribution visualized result. Compared with the prior art, the present invention has the advantages of being practical, automatic recognition, feedback optimization, and the like.

Abstract: The present disclosure relates to a system and method for automatic adjustment of a planned train operation chart. The system comprises a train operation data analysis module, a passenger flow data matching module, and an operation chart adjustment module that are connected in sequence. The train operation data analysis module is connected to the operation chart adjustment module; the train operation data analysis module assesses the deviation between an actual operation chart and a planned operation chart on the basis of ATS historical operation data to obtain an operation chart assessment result; the passenger flow data matching module calculates the actual passenger flow distribution on the basis of on-board weighing passenger flow data and AFC passenger flow data, and matches the actual passenger flow distribution with the actual operation chart to obtain a passenger flow matching result; and the operation chart adjustment module performs optimizing adjustment.

Abstract: The present invention relates to a multi-layer coupling relationship-based train operation deviation propagation condition recognition method, where the method includes the following steps: (1) recognizing an effective train event time sequence, including an arrival event and a departure event of a train at each passing station; (2) uniformly extracting train activity data, including a stop activity, a section operation activity, a turn-back activity, and an arrival or departure interval activity; (3) constructing coupling relationship groups between a train event and a train activity and between train activities; and (4) performing statistics on changes of train operation deviation in each relationship group, and outputting a respective distribution function and a time-space distribution visualized result. Compared with the prior art, the present invention has the advantages of being practical, automatic recognition, feedback optimization, and the like.

Abstract: The present invention relates to a full-day in each train operation diagram generation method based on a time division scheme and an activity-event relationship, the method including: S1: configuring operation scheme basic parameters; S2: constructing a quantitative relationship between a travel time and a driving interval for different routing ratios and calculating, within a given turn-back time range, an actual turn-back time of each turn-back station that can achieve a routing ratio requirement; S3: generating an arrival event time and a departure event time of a train in each time period at a station platform in accordance with routing division, direction division, and proportion division, correcting a start time and a stop time of each routing in accordance with time period division, and performing transition between the time periods; and S4: connecting a train section operation activity and a stop activity according to the full-time train arrival and departure event times obtained by executing step S3