A Unique Metro Choice Behaviour of Suburban Rail Passengers in India

Abstract

This study aims to analyse the inter-rail modal shift behaviour of suburban rail passengers to examine ridership for the proposed metro extension corridor in Chennai, India. This investigation was conducted in 2019 as part of a feasibility study for the extension of the metro line spanning between Chennai Airport and Kilambakkam, a southern suburb of Chennai. The same origin–destination pair is also served by the suburban rail system. It is an extension of the operating line from Washermenpet to the airport of the Phase I metro project. For this inter-rail competition study, a sample of 272 suburban rail passengers covering work, education and other trip purposes were interviewed using a stated preference questionnaire. Six stated scenarios were considered for analyses which included travel time saving by using the metro along with the fare difference between metro and bus. The study revealed that suburban rail passengers were less concerned about travel time saving and gave priority to fare difference irrespective of trip purpose. This shows the unique metro choice behaviour of suburban rail travellers in the Indian context.

Keywords

Modal shift / Metro / Logit / Stated preference survey / India

References

[1] Tischer ML, Dobson R. An empirical analysis of behavioural intentions of single-occupant auto drivers to shift to high occupancy vehicles. Transp Res, 1979, 13A: 143-158.

[2] Nurdden A, Rahmat RAOK, Ismail A. Effect of transportation policies on modal shift from private car to public transport in Malaysia. J Appl Sci, 2007, 7(7): 1014-1018

[3] Aditya VS, Thomas M, Krishna Rao KV. Mode shift behavior of commuters due to the introduction of new rail transit mode. Trans Res Procedia, 2016, 25: 2603-2618.

[4] Selvakumar M, Abishek Reddy M, Sathish V, Venkatesh R. Potential influence of metro on bus: a case study. J Inst Eng Ser A, 2018, 99(2): 379-384

[5] Das S, Boruah A, Banerjee A, Raoniar R, Nama S, Maurya AK. Impact of COVID-19: a radical modal shift from public to private transport mode. Trans Policy, 2021, 109: 1-11

[6] Satiennam T, Jaensirisak S, Satiennam W, Detdamrong S. Potential for modal shift by passenger car and motorcycle users towards Bus Rapid Transit (BRT) in an Asian developing city. IATSS Res, 2016, 39: 121-129

[7] Majeed S, Batool Z. Identification of factors affecting modal shift in lahore: factors affecting modal shift in Lahore. Proc Pak Acad Sci Phys Comput Sci, 2016, 53(4): 373-379.

[8] Vedagiri P, Arasan VT. Modelling modal shift due to the enhanced level of bus service. Transport, 2010, 24(2): 121-128

[9] Wang Y, Li L, Wang Z, Lv T, Wang L. Mode shift behavior impacts from the introduction of metro service: case study of Xi’an, China. J Urban Plann Dev, 2013, 139(3): 216-225

[10] Census of India (2011) District Census Handbook Chennai. Series 34, Part XII-B, Directorate of Census Operations, Tamil Nadu

[11] Hyderabad Metro Rail Limited (HMRL) https://hmrl.co.in/index.html. Accessed on 2.10.2022

[12] Asian Development Bank (2021) Mumbai metro transforming transport: contributing towards an equitable, safer and cleaner city, 1–98

[13] Khaki AM, Zargari SA, Moayedfar R. Developing the composed probability model to predict household trip production (a case study of Isfahan city). Transport, 2009, 24(1): 30-36

[14] Batty P, Palacin R, González-Gil A. Challenges and opportunities in developing urban modal shift. Travel Behav Soc, 2015, 2(2): 109-123

[15] Abdel-Aal MMM. Value of time determination for the city of Alexandria based on a disaggregate binary mode choice model. Alexandria Eng J, 2017, 56: 567-578

[16] Wright PH, Ashford NJ. Transportation engineering: planning and design, 1989 3 New York: Wiley

[17] Hensher DA. Stated preference analysis of travel choice: the state of practice. Transportation, 1994, 21: 107-133

[18] Niggol Seo S. The behavioral economics of climate change adaptation behaviors, global public goods, breakthrough technologies, and policy-making, 2017, London: Academic Press

[19] Borghetti F, Caballini C, Carboni A, Grossato G, Maja R, Barabino B. The use of drones for last-mile delivery: a numerical case study in Milan Italy. Sustainability, 2022, 14: 1-20

[20] Kanafani A. Transportation demand analysis, 1983, New York: McGraw-Hill Book Company

[21] Swierstra AB, Nes R, v, Molin E J E, Modelling travel time reliability in public transport route choice behaviour. Eur J Transport Infrastruct Res, 2017, 17(2): 263-278.

[22] Bruce da Silva T, Baptista P, Santos Silva CA, Santos L. Assessment of decarbonization alternatives for passenger transportation in Rio de Janeiro Brazil. Trans Res Part D Trans Environ, 2022, 103(3): 103161