Mobility change in Delhi due to COVID and its’ immediate and long term impact on demand with intervened non motorized transport friendly infrastructural policies

The COVID pandemic severely impacted mobility during lockdown as well as the period after that observing different phases of unlocking process. Lockdown has resulted in drastic mobility reduction and subsequent unlocking process brought back mobility gradually to a certain level, substantially lower than the Pre-COVID periods. However, this is expected to be back gradually to same level of Pre-COVID after certain period of time. While this change is planned to be gradual, it creates an opportunity to improve mobility towards non-motorized transport (NMT) which can influence travel behavior for present as well for the future covering Pre and Post-COVID periods. Apart from studying the influencing travel behavior during Pre and Post-COVID conditions, change in quantum of commuting population is required to be studied for various estimations related to transport planning. This quantum of commuting population is largely affected by the adopted locking/unlocking strategies by Government of India. Commuting population and travel behavior got influenced by the large migration from metro cities to smaller towns, adopted work from home (WFH) styles, reduced commute of elderly and children and other restrictions on gatherings, etc. Considering the range of allowed activities, influenced by the phases of locking/unlocking strategies, twelve different scenarios have been developed for various estimations. The developed scenarios have been named with alpha numeric style ranging from A0 to E5. A0 presenting the Pre-COVID scenario. Alphabet “A” represent Pre-COVID scenario, “B”, “C”, “D” and “E” Scenarios represent the unlocking phases, while number 1, 2, 3, 4 and 5 represents the different policy aspects related to the change on capacity of transport services (i.e. public transport capacity and change due to infrastructural improvement for NMT). Scenario A0 represents the Pre-COVID situation, while other ranges (viz., B1, B2, B3, C2, C3, C4, D2, D3, D5) represents various locking/unlocking levels. The Scenario E5 represents the situation without any movement restrictions, where public transport systems are assumed to be functioning with full capacity and infrastructure has been improved for NMT trips. Estimations for all the 12 scenarios include commuting population, their modal split, vehicle kilometers travelled by these vehicles and corresponding vehicular emission. Estimated modal split also includes the influence of improved NMT friendly infrastructure and reduced capacity of public transport systems. The results of developed scenarios provide a handy information for the policy makers to choose right policy to promote sustainable transportation with adequate emphasis on NMT. It is evident that as compared to the Pre-COVID scenario (A0), Post-COVID scenario with improved NMT infrastructure (E5) has VKT reduction of 19% in MTWs, 5% in Cars and 49% in Buses. Increase in bicycle trips have been estimated to be 5.88 million for Post-COVID scenario as compared to 1.1 million trips estimated for the Pre-COVID Scenario. Similar trend has also been observed for fuel consumption (reduction of 4.7%–11.8%) and corresponding vehicular emission (reduction of 14%). This study estimated the potential benefits of providing NMT friendly infrastructure considering the gradual shift influenced by locking/unlocking phases of COVID pandemic.