Real-Time Scheduling on a Transit Bus Route

Li, Yihua; Rousseau, Jean-Marc; Wu, Fujun

doi:10.1007/978-3-642-85968-7_15

Cited by 15 publications

(18 citation statements)

References 4 publications

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“…Shen [22] shows that holding strategies combined with short-turning strategies reduced the mean passenger waiting time in case of disruptions. In [12], the author computes the wait time considering the interval time between the passage of successive vehicles and the number of travelers in the station, where the arrival of passengers is assimilated to a Poisson processus.…”

Section: Noria Processmentioning

confidence: 99%

Advanced approach for the public transportation regulation system based on cybercars

et al. 2010

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In the last decade, the authorities require the use of safe, comfortable vehicles to assure a door to door aspect with respect of environment in the urban context. In this paper, we propose an advanced approach of transport regulation where we integrate cybercars into a regulation process as an alternative in disruption cases. For that, we propose an ITS architecture including public transportation and cybercars into the same framework. We will show that collaboration between these two systems provides better results than managing them separably.

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Section: Noria Processmentioning

confidence: 99%

Advanced approach for the public transportation regulation system based on cybercars

et al. 2010

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“…e popular method to stabilise the buses' headways is to implement a holding strategy [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] which slows down a fast bus if its headway with respect to the bus ahead of it is deemed to be too small. Other approaches include stop-skipping [11, [22][23][24][25][26] or deadheading (i.e., sending an empty bus directly to a set of designated bus stops) [23,[26][27][28][29], limiting boarding [30][31][32][33][34][35], as well as despatching buses with wide doors [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Buses in a Loop Service: Emergence of No-Boarding and Holding Strategies

2020

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We study how N intelligent buses serving a loop of M bus stops learn a no-boarding strategy and a holding strategy by reinforcement learning. The no-boarding and holding strategies emerge from the actions of stay or leave when a bus is at a bus stop and everyone who wishes to alight has done so. A reward that encourages the buses to strive towards a staggered phase difference amongst them whilst picking up passengers allows the reinforcement learning process to converge to an optimal Q-table within a reasonable amount of simulation time. It is remarkable that this emergent behaviour of intelligent buses turns out to minimise the average waiting time of commuters, in various setups where buses move with the same speed or different speeds, during busy as well as lull periods. Cooperative actions are also observed, e.g., the buses learn to unbunch.

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“…However, research on bus transit scheduling using computers in China has just started in recent years. Much of it attempts to build a mathematical or heuristic model to tackle the bus vehicle scheduling problem on a line-by-line basis (Li et al, 1992(Li et al, , 1995Liu and Shen, 2007;Chen et al, 2004;Xia, 2003, 2004b). Unfortunately, it still requires much effort to meet the practical requirements of bus operators.…”

Section: Introductionmentioning

confidence: 99%

Integrated bus transit scheduling for the Beijing bus group based on a unified mode of operation

Shen

Xia²

2009

Int Trans Operational Res

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This paper presents an applied study of scheduling buses and drivers for the Beijing Bus Group (BJBUS), the largest bus company in China. This is pioneering research in China for bus transit scheduling using computers based on a unified mode of operation. It is anticipated that the research fruits and experiences obtained would be of benefit to other bus operators in China. The bus transit scheduling problem in BJBUS is first presented in the paper. The particular characteristics are pointed out, which are different from those in developed countries, while many are common in China. After a brief review and analysis of the appropriateness of some currently successful approaches, the paper focuses on reporting the solution ideas and methods for BJBUS, especially those developed to solve the specific problems of BJBUS, such as scheduling buses with built‐in meal periods, multi‐type bus scheduling, restricting drivers to one or two particular buses, etc. Finally, the implementation and computational results are reported before the concluding remarks.

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Real-Time Scheduling on a Transit Bus Route

Cited by 15 publications

References 4 publications

Advanced approach for the public transportation regulation system based on cybercars

Advanced approach for the public transportation regulation system based on cybercars

Intelligent Buses in a Loop Service: Emergence of No-Boarding and Holding Strategies

Integrated bus transit scheduling for the Beijing bus group based on a unified mode of operation

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