Volume 42 Issue 2
Apr.  2024
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CHENG Guozhu, LI Weijun, FENG Tianjun. A Method for Allocating Bus Passenger Flow by Considering Comprehensive Cost[J]. Journal of Transport Information and Safety, 2024, 42(2): 166-174. doi: 10.3963/j.jssn.1674-4861.2024.02.017
Citation: CHENG Guozhu, LI Weijun, FENG Tianjun. A Method for Allocating Bus Passenger Flow by Considering Comprehensive Cost[J]. Journal of Transport Information and Safety, 2024, 42(2): 166-174. doi: 10.3963/j.jssn.1674-4861.2024.02.017

A Method for Allocating Bus Passenger Flow by Considering Comprehensive Cost

doi: 10.3963/j.jssn.1674-4861.2024.02.017
  • Received Date: 2023-03-10
    Available Online: 2024-09-14
  • The inefficiencies and inaccuracies of traditional survey methods for bus passenger flow data need to be addressed. Moreover, bus passenger flow allocation methods are inadequate due to the incomplete consideration of travel cost and significant disparities in travel cost among individuals. Therefore, a study on a bus passenger flow allocation method that considers comprehensive cost is conducted. A mobile signaling data platform based on Data-as-a-Service is developed as a source of data for bus passenger flow allocation. Spatial relationships between users and traffic zones are determined by matching latitude and longitude coordinates. Using a data warehousing tool, data dictionary indexes are filtered to define parameters such as time, speed, and origin-destination types. Transportation modes are identified through time matching and path matching. User proportions are extrapolated to the national population to obtain the bus commuting origin-destination (OD) matrix during the morning peak period for permanent residents. Travel time cost, congestion cost, and fare cost for bus passengers are analyzed. A bus passenger flow allocation model is established based on the principle of maximizing individual benefits while considering comprehensive cost. The problem of bus passenger flow allocation between traffic zones is transformed into a directed weighted graph path selection problem. A hybrid algorithm combining depth-first search and successive averages method is employed to solve this problem, facilitating bus travel plan selection and passenger flow allocation. Taking typical traffic zones in Harbin as a case study, bus passenger flow allocation is conducted and compared with results from the traditional Logit path selection probability model and manual surveys. The results show that the average absolute percentage error between the proposed model and manual surveys is 4%, compared to 17.5% for the Logit model. After allocating passenger flows using the proposed model, the extreme difference, variance, and total sum of individual travel cost are 0.03, 0.000 1, and 1 108.35, respectively, compared to 3.28, 1.58, and 1 127.02 for the Logit model. These results validate the accuracy of the proposed model in allocating passenger flows and highlight the necessity of considering comprehensive cost. After passenger flow allocation, the difference in individual travel cost is smaller, aligning better with the principle of maximizing benefits.

     

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