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Buses form an integral part of the public transport system; economically weaker section remain captive to its use as a means to travel, for livelihood and work. Research has highlighted the use of Intelligent Transport System (ITS) and Generalised Transit Feed Specification (GTFS) for bus system optimisation, while only a handful papers have tried to link the bus system indicator of time, speed and fleet to the urban systems.
In the year 2016, the Government of Delhi (GoD) began publishing the bus transit data for open use. The Generalised Transit Feed Specification (GTFS) data is published for DIMTS operated buses, which forms approximately 50% of the total city fleet. With GoD’s re-introduction of bus-lanes in April 2022, the conversation around bus systems and its impact on and from urban networks has taken a front seat. Thus, the study aims to present a methodology to understand the relationships between built environment indices and bus speeds.
To demonstrate the use case, the GTFS dataset, pre-processed and stored by CEEW, for 10 bus routes stratified across Delhi, were acquired for the month July 2021, February, March, April and March 2022. Using regression models the study identifies significant (p<.05) relationships between bus speeds and urban built environment indices - Normalised Difference Built Index (NDBI), Normalised Difference Vegetation Index (NDVI), Entropy Index and Network Line Density. However, since the models show high heteroscedasticity, the regression vary on filtered fits of land-use and specific bus-routes. It is noted using the t-test that, bus speeds are 10% slower (p< .05) in residential land-use dominant areas. While, the speeds around recreational and industrial areas is higher by 4% and 6 % respectively. Furthermore, using the google satellite imagery, the study is also able to validate the utility of bus speed variation as a proxy for identifying permanent and temporary infrastructure barriers. This study proposes newer use cases of GTFS data to augment urban network infrastructure planning, and at performing remote traffic and network monitoring.
Keywords: Bus Optimisation, Bus Speeds, Infrastructure Barrier, Land use, NDBI – NDVI, Network Density.
