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A Real-Time Control Strategy for Bus Operation to Alleviate Bus Bunching

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In order to alleviate bus bunching and improve the balance and punctuality rate of bus operation, a single-line real-time control strategy based on Intelligent Transportation System (ITS) was proposed. The strategy took three measures: controlling the cruising speed, dwell time, and the bus load rate to improve the stability of bus operations and to ensure its running speed. At the same time, the proposed strategy was compared with the literature on the traditional single-point control strategy based on timetable (S1 for short) and the multi-point control strategy based on time headway (S2 for short). Finally, the No. 245 bus line in Nanchang City, China, was selected as a case. It was modeled and simulated by Python programming software, and the control effects of the three control strategies were analyzed. Compared with the uncontrolled bus operations, the simulation results show that: under the control of S1, the bus operation stability is improved, but the bus operation efficiency is reduced; under the control of S2, the problem of S1 operation efficiency reduction can be solved, and the operation stability can be improved at the same time to achieve the effect of preventing bunching. For the real-time control strategy (S3 for short), the average bus travel time is the smallest, the distance between the buses is maintained the best, and the running stability is also the best, which avoids the bus bunching to the greatest extent. Among them, the average travel time is reduced by about 34% compared with the second strategy. This study provides a theoretical basis and strategy reference for bus operators to ensure balanced bus operation.
Title: A Real-Time Control Strategy for Bus Operation to Alleviate Bus Bunching
Description:
In order to alleviate bus bunching and improve the balance and punctuality rate of bus operation, a single-line real-time control strategy based on Intelligent Transportation System (ITS) was proposed.
The strategy took three measures: controlling the cruising speed, dwell time, and the bus load rate to improve the stability of bus operations and to ensure its running speed.
At the same time, the proposed strategy was compared with the literature on the traditional single-point control strategy based on timetable (S1 for short) and the multi-point control strategy based on time headway (S2 for short).
Finally, the No.
245 bus line in Nanchang City, China, was selected as a case.
It was modeled and simulated by Python programming software, and the control effects of the three control strategies were analyzed.
Compared with the uncontrolled bus operations, the simulation results show that: under the control of S1, the bus operation stability is improved, but the bus operation efficiency is reduced; under the control of S2, the problem of S1 operation efficiency reduction can be solved, and the operation stability can be improved at the same time to achieve the effect of preventing bunching.
For the real-time control strategy (S3 for short), the average bus travel time is the smallest, the distance between the buses is maintained the best, and the running stability is also the best, which avoids the bus bunching to the greatest extent.
Among them, the average travel time is reduced by about 34% compared with the second strategy.
This study provides a theoretical basis and strategy reference for bus operators to ensure balanced bus operation.

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