NDLI: Stochastic collective model of public transport passenger arrival process

Content Provider	IET Digital Library
Author	Kieu, Le Minh Cai, Chen
Abstract	It is essential to understand how transit passengers arrive at stops, as it enables transit operators and researchers to anticipate the number of waiting passengers at stops and their waiting time. However, the literature focuses more on predicting the total passenger demand, rather than simulating individual passenger arrivals to transit stops. When an arrival process is required especially in public transport planning and operational control, existing studies often assume a deterministic uniform arrival or a homogeneous Poisson process to model this passenger arrival process. This study generalises the homogeneous Poisson process (HPP) to a more general non-HPP (NHPP) in which the arrival rate varies as a function of time. The proposed collective NHPP (cNHPP) simulates the passenger arrival using less time regions than the HPP, takes less time to compute, while providing more accurate simulations of passenger arrivals to transit stops. The authors first propose a new time-varying intensity function of the transit passenger arrival process and then a maximum likelihood estimation method to estimate the process. A comparison study shows that the proposed cNHPP is capable of capturing the continuous and stochastic fluctuations of passenger arrivals over time.
Starting Page	1027
Ending Page	1035
Page Count	9
ISSN	1751956X
Volume Number	12
e-ISSN	17519578
Issue Number	Issue 9, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/12/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2018.0085
Journal	IET Intelligent Transport Systems
Publisher Date	2018-07-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	CNHPP Collective NHPP Deterministic Uniform Arrival Homogeneous Poisson Process Maximum Likelihood Estimation Maximum Likelihood Estimation Method Number-of-waiting Passengers Operational Control Public Transport Passenger Arrival Process Public Transport Planning Statistics Stochastic Collective Model Stochastic Linearised SCUC System Theory Application in Transportation Time-varying Intensity Function Total Passenger Demand Transit Operators Transit Passenger Arrival Process Transportation Waiting Time
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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