Risk Evaluation Study of Urban Rail Transit Network Based on Entropy-TOPSIS-Coupling Coordination Model

As one of the core systems of a city, urban rail transit plays a pivotal role in ensuring the safe, rational, and efficient operation of the city. Therefore, it is of great significance to ensure the safe operation of urban rail transit network to improve the operation efficiency and economic level of the city. The prerequisite to ensure the safety of urban rail transit network is whether the risk situation of urban rail transit network can be reasonably and accurately evaluated. In order to evaluate the risk level of urban rail transit network reasonably and accurately, firstly, with full consideration of the characteristics of urban rail transit, the risk evaluation system of urban rail transit network was established in this paper based on the three levels of regional economy, social resources, and rail transit. Secondly, based on the entropy-TOPSIS-coupling coordination model, the single-factor influence and multifactor coupling influence in the index system are calculated and analyzed, respectively; thus the coupling coordination degree of urban rail transit system is obtained, so as to quantitatively evaluate and analyze the risk situation in urban rail transit network. Finally, based on the actual data of Shanghai from 2000 to 2016, the case simulation and analysis are carried out. The results show that the two indicators of regional economy and social resources are more likely to affect the safety state of urban rail transit. At the same time, the safety factor of urban rail transit coupling system is increasing year by year and gradually develops from disorder to order. This is more in line with current urban rail transit condition, demonstrating the rationality and accuracy of the entropy-TOPSIS-coupling coordination model proposed in this study.

Research on Optimization of Urban Public Transport Network Based on Complex Network Theory

The urban public transportation system is an important part of urban transportation, and the rationality of public transportation routes layout plays a vital role in the transportation of the city. Improving the efficiency of public transportation can have a positive impact on the operation of the public transportation system. This paper uses complex network theory and the symmetry of the up and down bus routes and stations to establish an urban public transit network model and calculates the probability of passengers choosing different routes in the public transit network according to passenger travel impedance. Based on passenger travel impedance, travel path probability and passenger travel demand, the links are weighed, and the network efficiency calculation method is improved. Finally, the public transit network optimization model was established with network efficiency as the objective function and solved by the ant colony algorithm. In order to verify the effectiveness of the model and the solution method, this paper selects areas in Nanguan District of Changchun City for example analysis. The result shows that the efficiency of the optimized network is 8.5% higher than that of the original network, which proves the feasibility of the optimized model and solution method.

Mining the Coopetition Relationship of Urban Public Traffic Lines Based on Time Series Correlation

Along with the evolution of passenger flows within cities, the coordination between public traffic lines should be sustainably optimized with respect to the spatial distribution of the flow, though the lines were planned well at the beginning of the construction. It is critical to determine the coopetition between bus lines to optimize a transit network continuously. A method of mining coopetition relationship (MCBTC, Mining Coopetition relationship between Bus lines based on a Time series Correlation) based on passenger flow is proposed in this study. First, noisy, inconsistent or missing data are eliminated to obtain a passenger flow time series, and the proposed merging algorithm is used to extract the line passenger flow time series (LPFTS, Line Passenger Flow Time Series) by merging the passenger flow of adjacent buses from the same line. Then, to calculate the positive and negative correlation sequence sets, a clustering algorithm is proposed. The two sequence sets represent the competition and cooperation relationships, respectively. The MCBTC method has been tested with a practical data set, and the results show that it is very promising.

The Evolvement of Rail Transit Network Structure and Impact on Travel Characteristics: A Case Study of Wuhan

The expansion of the rail transit network has a positive impact on travel characteristics under spatial and temporal constraints by changing accessibility. However, few empirical studies have examined the longitudinal evolution of the impact of accessibility and travel characteristics. In this paper, a model of the Wuhan rail transit network is constructed and the evolution of the spatial pattern of accessibility over different periods is analyzed. The correlation of accessibility with rail transit travel characteristics is studied longitudinally to provide theoretical support for rail transit construction and traffic demand management. The study shows that: (1) Wuhan’s rail transit network has evolved from a tree to a ring, improving the operational efficiency. (2) The accessibility of Wuhan’s rail transit network has evolved into a circular structure, showing a decreasing trend away from the city center. (3) The change of accessibility greatly affects travel characteristics. The higher the accessibility, the higher the traffic volume, and the lower the travel frequency, the more residents travel during peak hours, and the shorter the travel distance. These findings are useful for gaining insight into public transportation demand in large cities, and thus for developing reasonable transportation demand management policies.

Transit Network Frequency Setting With Multi-Agent Simulation to Capture Activity-Based Mode Substitution

We propose a bilevel transit network frequency setting problem in which the upper level consists of analytical route cost functions and the lower level is an activity-based market equilibrium derived using MATSim-NYC. The use of MATSim in the lower-level problem incorporates sensitivity of the design process to competition from other modes, including ride-hail, and can support large-scale optimization. The proposed method is applied to the existing Brooklyn bus network, which includes 78 bus routes, 650,000 passengers per day, 550 route-km, and 4,696 bus stops. MATSim-NYC modeling of the existing bus network has a ridership-weighted average error per route of 21%. The proposed algorithm is applied to a benchmark network and confirms their predicted 20% growth in ridership using their benchmark design. Applying our proposed algorithm to their network with 78 routes and 24 periods, we have a problem with 3,744 decision variables. The algorithm converged within 10 iterations to a delta of 0.064%. Compared with the existing scenario, we increased ridership by 20% and reduced operating cost by 25%. We improved the farebox recovery ratio from the existing 0.22 to 0.35, 0.06 more than the benchmark design. Analysis of mode substitution effects suggest that 2.5% of trips would be drawn from ride-hail while 74% would come from driving.