Public transport planning is one of the most important criteria in the development strategy of any country. India is a developing country, and the smart card facilities are rare; hence, it is suitable to look upon easily available data sources which could be helpful for public transport planning. One such big data source is the electronic ticketing machine (ETM) data. This study focuses on the long-distance bus services operated under Kerala State Road Transport Corporation (KSRTC) in Thrissur district, Kerala. KSRTC has been identified as one of the major losses making public sector services according to the Shushil Khanna Panel report. In order to improve the situation, a study on the existing conditions was essential. This study explores the use of ETM data in the generation of origin destination matrix for the long-distance bus services. The ETM data of the long-distance routes maintained by KSRTC has been collected from all the five bus depots in Thrissur. An algorithm has been developed which defines the sequential procedure followed to get the desired matrix output. Based on the developed algorithm, a Python code has been framed so as to estimate the origin destination matrix. The network model was created in VISUM, and desire line and flow bundle analysis has been carried out based on the consolidated OD Matrix in VISUM. The analysis found out Thiruvananthapuram to Attingal as the OD pair with maximum demand and the route sections that are contributing to the loss in the sector has been identified.


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    Titel :

    Potential of Electronic Ticketing Machine Data in Public Transport Planning


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Devi, Lelitha (Herausgeber:in) / Das, Animesh (Herausgeber:in) / Sahu, Prasanta Kumar (Herausgeber:in) / Basu, Debasis (Herausgeber:in) / Francis, Susan (Autor:in) / Sunitha, V. (Autor:in) / Mathew, Samson (Autor:in)

    Kongress:

    Conference of Transportation Research Group of India ; 2021 December 14, 2021 - December 17, 2021



    Erscheinungsdatum :

    19.09.2022


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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