The marketing meme of Rahul Dravid, losing his otherwise patient demeanour while commuting in Bengaluru traffic, stands testimony to the impact traffic blockage can create on the human psyche. It can trigger dramatic behavioural change amplified by the blaring of horns, nausea due to the surrounding pollution, and the deteriorating road conditions created by incessant human activity in a perpetual rush. Changing weather conditions can further add to the misery of the long commute during peak hours in mega cities. But leveraging deeper insights from mobility and better use of city data such as traffic speed, road condition, pollution, weather, etc. to enhance commute experience, can reverse this trend easily.
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Data-led solutions are essential for commuting in cities like Mumbai, Bengaluru, and New Delhi which have the dubious distinction of featuring among the top ten most congested cities in 2020 as per the TomTom Traffic Index. The cost of gridlock traffic in these cities was estimated at over $22 billion in 2018, which was approximately 90 percent of India’s railway budget. Traffic congestion not only inflicts loss of precious time but also leads to excess fuel burn and other opportunity costs. No wonder, many corporations have initiated flexible hours and options to work remotely, reducing future investments in cities like Bengaluru citing mainly traffic woes. In retrospect, working remotely became a new normal during the Covid-19 pandemic, with several technology companies claiming higher productivity and happier employees.
Most Indian cities often lack decision-making ability due to budgetary constraints, ambiguity in administrative functions, scattered and unorganised data, and lack of political will, derailing priority infrastructure. However, the burgeoning vehicular traffic and deteriorating quality of ride, has compelled megacities like Mumbai and Bengaluru to upgrade their road and transit infrastructure. But until the improvements are completed, ‘swalpa adjust maadi’ (Kannada for “kindly adjust”).
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Cities are updating their Master Plans or Comprehensive Mobility Plans to envision a sustainable future, but there are rarely any monitoring or budgetary mechanisms to ensure implementation. This could be addressed using an action plan consisting of attributes for a delightful commute experience, such as comfort, safety, flexibility, reliability, affordability, sustainability and shorter travel time, to make a positive change and move people forward. Cities need to change gears from reactive to proactive planning and prioritise funding for projects that can lead to measurable and impactful results with strict timelines to accelerate effective movement of people and ensure travel delight.
The declining mode share of public transport across major cities like Delhi where it reduced from 51.9 percent in 2007 to 40.2 percent in 2018 along with 7-10 percent CAGR vehicular ownership indicates rapidly changing commuter preferences. The loss of ridership can also be attributed to delays in investment in quality public transport, lack of reliability and increase in income levels. This shifting trend from shared to personal mobility needs to be arrested with effective alternatives like new shared mobility options which can be hailed with the click of a button, without compromising on the commuting experience.
The ubiquity of smartphones and smart use of data empowers citizens to make informed choices about travel modes and routes. The 'smartness of mobility' could help plug-in larger data points such as weather conditions, traffic events, externalities etc. thereby improving trip planning and realisation. For example, a popular radio station that claims its listeners are always happy, relays crowdsourced traffic updates for commuters to use the information in planning and improvising their journey. The programme is sponsored by a popular car manufacturer, probably as a service to the society or penitence to it contributing to traffic congestion or perhaps just brand marketing.
Notably, enriched open traffic data will enable predictive modelling to identify traffic bottlenecks and enable solutions to decongest our already saturated road capacity. Through the assimilation of GPS data and CCTV camera feed from different nodes of the city, real time traffic updates can be aggregated and analysed. In London, over 4,000 traffic signals use SCOOT (Split Cycle Offset Optimization Technique) adaptive control system which changes traffic lights in response to demand. The signals are connected to manage flow through junctions and key corridors. Thus, Artificial intelligence (AI) could reduce traffic stress.
Undoubtedly, the future of mobility will be data-driven, powered by shared, connected, electric, AI-powered, and autonomous mobility solutions. If widely adopted, and policy compels this preferential shift, cities in India may breathe a sigh of relief. Until then, the city administration should strive to aggregate relevant data repositories, streamline protocols enabling sharing of data and catalyse an innovative mobility ecosystem that creates better working cities with happier citizens.
The author, Roshan Toshniwal, is an Associate Director and the Urban Mobility Lead at Ola Mobility Institute. The views expressed are personal.
(Edited by : Anshul)
First Published: IST