Electronic ticket machine data analytics for public bus transport planning

Cyril, Anila; Varghese, George; Mulangi, Raviraj H.

doi:10.1109/icecds.2017.8390198

Cited by 14 publications

(4 citation statements)

References 8 publications

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“…The e-ticket contains details of the bus, information of the route and trip details. The machine records information such as the bus type, bus number, minimum fare, fare increment, fare stages, bus stop details, route number, passenger type and the number of passengers [4]. The raw data from the ETM has to be processed to obtain the required passenger demand data.…”

Section: Data Source-the Electronic Ticketing Machinesmentioning

confidence: 99%

“…On the other hand, APC gives the number of passengers by receiving "On or Off counts" or sometimes "On and Off counts" using sensors installed near the doors. In some cases, APC data is the by-product of fare transactions as the data is recorded when the passenger pays for the ticket [4]. When a passenger purchases a ticket, AFC data gets recorded.…”

Section: Introductionmentioning

confidence: 99%

“…In the case of a developing country like India where smart card or travel card facilities are not commonly available, it is required to develop methods to use the readily available alternative data sources like ETMs. The ETMs generate a large amount of data, known as big data, pertaining to the number of passengers, time of ticket issuing, fare collected, earnings per kilometre and operated kilometre [4]. The ETM data is available on a time scale since the time of ETM implementation for the entire public transport network and the fleet.…”

Section: Introductionmentioning

confidence: 99%

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Bus Passenger Demand Modelling Using Time-Series Techniques- Big Data Analytics

Cyril¹,

Mulangi²,

Varghese³

2019

TOTJ

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Background: Public transport demand forecasting is the fundamental process of transport planning activity. It plays a pivotal role in the decision making, policy formulations and urban transport planning procedures. In this paper, public bus passenger demand forecasting model is developed using a novel approach. The empirical passenger demand for a bus depot is modelled and forecasted using a data-driven method. The big data generated by Electronic Ticketing Machines (ETM) used for issuing tickets and collecting fares is sourced as the data for demand modelling. This big data is time indexed and hence has the potential for use in time-series applications which were not previously explored. Objectives: This paper studies the application of time-series method for forecasting public bus passenger demand using ETM based time-series data. The time-series approach used is the four Holt-Winters’ modeling methods. Holt-Winters’ additive and multiplicative models with and without damping have been empirically compared in this study using the data from the inter-zonal buses. The data used in the study is a part of the transaction on ticket sales by Kerala State Road Transport Corporation (KSRTC) maintained at the Trivandrum City depot of an Indian state Kerala, for the period between 2010 and 2013. The forecasting performance of four time-series models is compared using Mean Absolute Percentage Error (MAPE) and the model goodness of fit is determined using information criteria. Conclusion: The forecasts indicate that multiplicative models with and without damping, which better account for seasonal variations, outperform the additive models.

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Section: Data Source-the Electronic Ticketing Machinesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bus Passenger Demand Modelling Using Time-Series Techniques- Big Data Analytics

Cyril¹,

Mulangi²,

Varghese³

2019

TOTJ

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“…The electronic based transport ticketing system was developed for general transport [1] and railways [2] . Some Smart cards are secure, compact and intelligent data carriers.…”

Section: Introductionmentioning

confidence: 99%

Development of Microcontroller based Automated Public Transport Ticketing System

2019

IJRTE

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In India, generally printed tickets are issued for all kinds of transportation, and the printed tickets become useless once the passenger reaches their destination. For multiple modes of transportation like Bus, Trains, Metros, a multiple tickets are printed as well as a human verification is also required. Furthermore, it leads to financial loss and wastage of papers. In order to reduce the financial loss, time and human resource, a microcontroller based automated public transport ticketing system has been developed using a smart card and IoT. This ticketing system can be used to manage the billing in any mode of transportation like Bus, Trains, Metros, and Cabs. The automated public transport ticketing system is developed using a microcontroller and a single smart card which can be used for multiple transportation.

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