COVID-19 effects on urban driving, walking, and transit usage trends: Evidence from Indian metropolitan cities

• Published in: Cities 2022-07, Vol.126, p.103697-103697, Article 103697
• Main Authors: Padmakumar, Athul, Patil, Gopal R.
• Format: Article
• Language: English
• Subjects: Cities; Comparative analysis; Contagion; Coronaviruses; COVID-19; Data collection; Density; Employment; Generalized linear mixed effects mode; Google and Apple mobility data; Government; Indian cities; Mobility; Pandemics; Policy making; Public transportation; Regulation; Transportation; Travel; Travel modes; Trends; Walking
• ISSN: 0264-2751; 1873-6084; 0264-2751
• DOI: 10.1016/j.cities.2022.103697

The outbreak of the COVID-19 pandemic disrupted all walks of life, including the transportation sector. Fear of the contagion coupled with government regulations to restrict mobility altered the travel behavior of the public. This study proposes integrating freely accessible aggregate mobility datasets published by tech giants Apple and Google, which opens a broader avenue for mobility research in the light of difficult data collection circumstances. A comparative analysis of the changes in usage of different mobility modes during the national lockdown and unlock policy periods across 6 Indian cities (Bangalore, Chennai, Delhi, Hyderabad, Mumbai, and Pune) explain the spatio-temporal differences in mode usages. The study shows a preference for individual travel modes (walking and driving) over public transit. Comparisons with pre-pandemic mode shares present evidence of inertia in the choice of travel modes. Association investigations through generalized linear mixed-effects models identify income, vehicle registrations, and employment rates at the city level to significantly impact the community mobility trends. The methods and interpretations from this study benefit government, planners, and researchers to boost informed policymaking and implementation during a future emergency demanding mobility regulations in the high-density urban conglomerations. •Compared mobility change by different modes during COVID-19 in 6 Indian cities•Integrated mobility reports published by Google and Apple for mobility analysis•Spatio-temporal variations during the lockdown and unlock period analyzed•Generalized linear mixed-effect models developed to analyze mobility trends•People preferred walking and driving over public transit•Income, vehicle registrations, and employment rates affected mobility trends.