A Complete Information Interaction-Based Bus Passenger Flow Control Model for Epidemic Spread Prevention

Xinghua Hu, Yimei Xu, Jianpu Guo, Tingting Zhang, Yuhang Bi, Wei Liu and Xiaochuan Zhou
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Xinghua Hu: School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Yimei Xu: School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Jianpu Guo: Chongqing Productivity Council, Chongqing 401147, China
Tingting Zhang: School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Yuhang Bi: Ningbo Citizen Card Operation Management Co., Ltd., Ningbo 315199, China
Wei Liu: School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Xiaochuan Zhou: Chongqing Ulit Technology Co., Ltd., Chongqing 408319, China

Sustainability, 2022, vol. 14, issue 13, 1-11

Abstract: Because the strategy of stopping bus lines during an epidemic can negatively impact residents, this study proposes a bus passenger flow control model to optimize the safety of and access to bus transport. The information interaction environment can provide a means for the two-way regulation of buses and passengers. In this model, passengers first request their pick-up and drop-off location, and then the bus feeds back information on whether it accepts the request. Through this method, passenger flow control can be realized through complete information interaction. The study aimed to establish a multi-objective function that minimizes the weighted total cost of the safety cost, the passenger travel cost, and the bus travel cost during an epidemic. The constraints were the full load and riding rates of urban buses in peak periods under the condition of epidemic prevention and control. The results showed that, in the morning peak period, the passenger flow control scheme reduced the passenger infection probability by 17.89%, compared with no passenger flow control scheme. The weighted total cost of the epidemic safety cost, the passenger travel cost, and the bus operation cost was reduced by 8.04%. The optimization effect of the passenger flow control scheme of this model is good, and not only reduces the probability of passengers being infected, but also meets the requirements of epidemic prevention and the travel needs of residents.

Keywords: epidemic; passenger flow control; multi-objective function; passenger scheduling; information interaction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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