A few years back I had written an oped with some ideas for addressing traffic problems. This blog post outlined the contours of a transportation management plan for cities.
While improvements in the quality of transport infrastructure and expanding the quality and coverage of public transport are central to any meaningful effort, they will take time and resources. In capacity and resource constrained as well as deeply politically polarised environments, the challenges are daunting and it is unrealistic to expect transformational changes.
But there is at least one area which is promising and in which immediate action is possible. An important cross-cutting requirement for most interventions is the availability of relevant and actionable transportation related data. This data includes spatial and temporal information about commute patterns of people stratified by their transport modes, their likely income and occupational categories, their origin and destinations and so on. This information is just as much important to trigger demand response among commuters as it is in urban planning. Consider these questions.
How to optimise the use of the existing road network? Can the existing road network be utilised more efficiently by re-routing traffic spatially and temporally? What should be the optimal directional configuration of roads, given the current traffic pattern?
Which are the highest density bus routes at any point in time? Do the bus schedules reflect the current commute patterns of the the bus-taking population groups? Are the bus schedules at least reasonably synchronised with that of the other mass transit modes? Are metro and commuter railways adequately serviced by last-mile connects involving buses or other private bulk-transport modes? How to inform various last-mile connectors, including auto drivers and informal minivan operators, about demand conditions?
How can the transportation data serve as decision-support for urban planning decisions? How to make road widenings and new road proposals informed by such data? How to ensure that land-use conversions and large construction approvals are informed by the latest transportation data? How can land-use conversion decisions be informed by transportation constraints? How can such data inform and shape the expectations and decisions of investors and entrepreneurs, and existing businesses? How can such data be institutionally integrated into urban planning and infrastructure investment decisions of a city?
How do we make available all the information on the spatial and temporal traffic congestion levels to vehicle users so as to trigger demand response - which routes to take at any time to minimise commute times? How can it most effectively inform individual decisions on commutes to office, for shopping, and for weekend leisure? How can the latest transportation information be made available in a manner that can be a meaningful decision-support for people's choices on where to buy or rent their houses?
Transportation data can be harvested from mass transit operators, mobile telephone companies, smart phone makers, transport solution providers, and the different categories of public-owned sensors available at various locations within the city. All this should be complemented with periodic surveys to update information. Such data, appropriately anonymised and aggregated (to limit both privacy concerns as well as any significant commercial loss for data generators), can be captured and made available on a platform with public APIs. It is no good merely providing associated data. The data has to be analysed into meaningful information which is relevant, proximate and actionable decision-support for different stakeholders. The design of the platform should keep this in mind.
This would most likely require hard-bargaining with mobile operators and mobile phone manufacturers (or App providers, chiefly Google and Apple). The metro railway agencies across cities and state road transportation corporations (where applicable) should overcome their hesitations and make public real-time information about their services.
Making the data available would allow independent App developers to develop applications and figure out commercial models that respond to the demands of various stakeholders. In a large country with over 4000 cities and towns, mere provision of this information is likely to open up numerous opportunities which at least some among the stakeholders will seize and create business models. It is a great opportunity for creating the conditions for mass-flourishing.
But we should be prudent about the expectations from such an intervention. A few among the cities, with both the requisite capacity and eco-system as well as committed city leaders, will adopt it immediately with vigour. The others will have to surmount formidable behaviour, capacity and political economy challenges. But it will doubtless create a strong foundation for urban planning and demand response across cities. In some ways, it will get cities to the starting line in the urban transformation race. After that who know how the emergent dynamics of systems play out?
We should not underestimate the cumulative effect of countless decisions by people informed by such data. Over time, they can radically shift commute patterns, the fortunes of localities, behaviours of businesses, and so on. Most importantly, they can lead to informed public debates on the critical issue of urban transport. Public policy would invariably follow, at first in a few cities and towns. They are perhaps our biggest hope. What can public policy, through, say, the Smart Cities Mission, do to enable this vision?
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