Open Access Open Access  Restricted Access Subscription or Fee Access

A Rational Framework to Develop Strategies for Improvement of Travel Time Performance of Multimodal Transport System

R. Tanwar, P.K. Agarwal

Abstract


A multimodal transport system refers to a transportation network that integrates multiple modes of transportation such as buses, trains, planes, and ships to provide seamless connectivity between different origins and destinations. The system allows users to switch between different modes of transportation within a single journey, allowing for increased efficiency, convenience, and costeffectiveness. Overcrowding, hazardous and unpleasant rides, greater travel costs, environmental degradation, inadequate connection, and other issues are major challenges in Indian cities as cities grow in size. To meet these challenges, multimodal transport integration is becoming necessity in urban areas. As a consequence of the diminishing trend of transportation share in Indian cities, multimodal transportation agencies have a challenge to enhance the performance of the transportation system. As a result, there is an urgent need for developing strategies of travel time performance improvement of multimodal transport system so that current transportation challenges may be overcome. Thus, this study aims to propose a basic framework for the development of strategies for the improvement of travel time performance in multimodal transport systems. The framework is based on a comprehensive review of existing literature and consist four stages of travel time performance improvement. Stage I— identification of key performance indicators of travel time performance, Stage II—evaluation of identified key performance indicators of travel time performance, Stage III—evaluation of travel time performance level (user satisfaction level), and Stage IV—development of strategies for improvement of travel time performance of multimodal transport system. This framework will serve as a starting point for transportation planners and policymakers in their efforts to improve the efficiency and sustainability of multimodal transport systems of Indian cities.

Full Text:

PDF

References


Solanki VS, Agarwal PK. A basic framework for benchmarking of performance indicator for urban

transport system. Int J Emerg Technol. 2020; 11 (4): 521–526.

Gurjar J, Jain PK, Agarwal PK. Comparative performance evaluation of transport services from

city perspective. World Conference on Transport Research—WCTR. Mumbai, India. 2019, May

–31.

Gurjar J, Agarwal PK, Jain PK. A comprehensive methodology for comparative performance

evaluation of transport systems in urban areas. World Conference on Transport Research—WCTR.

Mumbai, India. 2019, May 26–31

Agarwal PK, Tanwar R, Jain A. Strategies for improving travel time performance of multimodal

transport system. 14th International Conference on Transportation Planning and Implementation

Methodologies for Developing Countries (TPMDC). 2022, December.

Agarwal PK, Jitendra G, Ajinkya G, Jain PK. A rational methodology for evaluation of the impact

of transit service in a city. Int J Frontier Technol. 2015; 2 (2): 18–25.

Mashrur R, Akther MShakil, Recker W. The first-and-last-mile of transportation: a study of access

and egress travel characteristics of Dhaka’s suburban commuters. J Transp; 24: 100025. doi:

1016/j.jpubtr.2022.100025.

Ugurlu S, Kaya I. A new reliability index based on fuzzy process capability index for travel time in

multimodal networks. Int J Comp Intell Syst. 2011; 4 (4): 550–565. doi:

1080/18756891.2011.9727812.

Dixit M, Brands T, van Oort N, Cats O, Hoogendoorn S. Passenger travel time reliability for

multimodal transport journeys. Transp Res Rec. 2019; 2673 (2): 149–160. doi:

1177/0361198118825459.

Ma Z, Ferreira L, Mesbah M, Zhu Sicong. Modeling distributions of travel time variability for bus

operations. J Adv Transp. 2016; 50 (1): 6–24. doi: 10.1002/atr.1314.

Hemdan S, Wahaballa AM, Kurauchi F. Travel time variability and macroscopic fundamental

diagram relationships in multimodal networks. International Journal of Intelligent Transportation

Systems Research. 2018; 17 (9): doi:10.1007/s13177-018-0161-y.

Minal RS, RaviSekhar C, Madhu E. Multimodal travel choice determinants in context of travel time

reliability. Proc Inst Civ Eng Transp. 2021: 1–10. doi: 10.1680/jtran.20.00091.

Jasti PC, Vinayaka Ram V. Sustainable benchmarking of a transport system using analytic

hierarchy process and fuzzy logic: a case study of Hyderabad, India. Public Transp. 2019; 11: 457–

doi: 10.1007/s12469-019-00219-8.

Kengpol A, Tuammee S, Tuominen M. The development of a framework for route selection in

multimodal transportation. Int J Logist Manag. 2014; 25 (3): 581–610. doi: 10.1108/IJLM-05-2013-

Monteiro N, Rossetti R, Campos P, Kokkinogenis Z. A framework for a multimodal transportation

network: an agent-based model approach. Transp Res Procedia. 2014; 4: 213–227. doi:

1016/j.trpro.2014.11.017


Refbacks

  • There are currently no refbacks.