The network operation of the subway can reduce the number of passenger transfers and improve subway operation efficiency. Based on the subway smart card data, this paper proposes an optimal design method for the cross-line operation scheme of subway trains. The method firstly calculates the OD matrix between subway stations, the passenger section flow, and the transfer flow according to the passenger smart card data. It then optimizes the design of the subway train cross-line operation plan, including determining the routing type of cross-line operation and the number of trains running. Finally, for the lines with cross-line operation conditions in the urban subway system, we design the cross-line operation schemes under all possible combinations. According to the volume of the cross-line passenger flow that the cross-line trains can carry, the top-ranked operation plans are preferably recommended. Taking the Chengdu subway network as an example, the research results show that, in the Chengdu subway network, the North Railway Station, Xibo City Station, and South Railway Station bear the highest transfer demand. The transfer demands that can be undertaken by cross-line trains are 23,934, 16,710, and 13,024 trips per hour, respectively. This shows that the proposed design method can accurately and reasonably screen out the transfer stations and lines with an urgent need for cross-line trains.

A notable feature of a city or a region with close economic and social connections with its neighbors is reflected in its highly mixed local and external traffic, and in some cases the external traffic volume is almost as high as that of local traffic. Whilst local traffic volume may be largely made up of the same regular local commuters making frequent trips, the external traffic from outside of the city (region) may not be the same people making regular trips to/from the city, but from a large pool of people making in-frequent trips to/from the city, the existence of external traffic is proven by data from the license plate recognition system of road vehicle in Changde of China. The function of value of time correlated with income/wage rate and trip frequency is exploited and verified statistically. The time value distorted by trip frequency is defined as perceived time value (PTV), which also influences the way travelers perceive any travel impedance such as congestion delay and toll charges. This paper analyses the price of anarchy (POA) when explicitly considering the travel frequency of the trip-makers and their PTV, and compares with previous analysis without considering travel frequency. We show that when travel frequency is considered, the optimal toll of congested road pricing schemes which converts road traffic flow from User Equilibrium into System Optimization, is much lower than that without considering travel frequency, and cost of license plate auction cannot be treated as congestion toll, which is only threshold of vehicle ownership. That travelers choose route by PTV rather than TV (time value) is proven by an example of Heishipu bridge of Changsha of Hunan Province in China.