Using Perspectives of Private Vehicle Users to Identify Priority Areas for Improving Accessibility to Metro Stations
Publication: Journal of Urban Planning and Development
Volume 149, Issue 4
Abstract
The present research investigates priority areas of interventions for improving accessibility to Metro stations in Delhi based on private vehicle users' perceptions. The focus is on identifying the avenues of infrastructure improvement in parking facilities near Metro stations. A tablet-based face-to-face questionnaire survey was adopted to collect 1,050 responses regarding perceived importance and satisfaction ratings of 17 service quality attributes under study on a 6-point Likert scale. The data were checked, cleaned, and analyzed using revised importance–performance analysis. A fuzzy c-means clustering technique was used to develop the factor structure and management scheme clusters. Finally, priority intervention areas were identified, and resources allocated by relating factor structures and management schemes. The findings indicated that the presence of designated parking facilities, provision of variable message signs (VMSs), parking guidance information, parking charges, and in-vehicle travel time were top priority attributes and warranted immediate improvement. Security, luggage space, extreme weather conditions, and universal design considerations were under low priority. Security at the Metro parking lots had optimum service levels and was expected to be maintained. Travel route information, safety, riding comfort, convenience, egress time, operational and maintenance cost, and illumination were attributes under “possible overkill,” indicating the need to transfer resources to improve other service attributes. The findings of the current work shall be useful to transport planners, traffic engineers, and officials in enhancing accessibility of private vehicle users to Metro stations by providing better Park-and-Ride facilities.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to acknowledge the Ministry of Education (MoE), Government of India for awarding the assistantship to Ms. Manaswinee Kar to conduct this study.
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Information & Authors
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Published In
Journal of Urban Planning and Development
Volume 149 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Sep 10, 2022
Accepted: Aug 16, 2023
Published online: Oct 9, 2023
Published in print: Dec 1, 2023
Discussion open until: Mar 9, 2024
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Computer programming
- Computing in civil engineering
- Data analysis
- Engineering fundamentals
- Fuzzy logic
- Highway transportation
- Infrastructure
- Methodology (by type)
- Parking facilities
- Railroad stations
- Research methods (by type)
- Surveys (non-geomatic)
- Terminal facilities
- Transportation engineering
- Transportation management
- Vehicles
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