Why driverless cars, alone, won’t take us there?
2016 has been an amazing year for mobility. Autonomous car technology has been the big news of the year!
Uber, Google, GM, Peugeot, BMW, VW Group, Tesla, Ford and even apple and Intel have all been experimenting with driverless cars and have edged us closer to an autonomous transport reality.
The excitement around seeing autonomous cars rule our roads in as little as half a decade has fueled many utopian views. The assumption is that autonomous cars will relieve us from driving duties at the least, help us share such cars with many more people, and positively earn us some taxi revenues while at it. The utopia would have such cars work in sync, ending road accidents, pollution and congestion.
Cars, although, remain a versatile personal vehicle, they also are the most inefficient use of limited road space, irrespective of computers driving them! Mass urban transport options like Metro still shift thousands of passengers at unparalleled speeds while relieving precious space on roads, buses move up to 60 times more passengers, bicycles take a fraction of a typical road lane and even taxi aggregators bring last mile connectivity. Multiple modes or multimodal transport is key to keeping our cities efficiently mobile.
While money is gushing towards designing, integrating and mainstreaming autonomous cars, we remain stuck in a world with limited technological innovations for mass and public transport and little to no integration of these multiple modes.
What is multimodal transport and why it is needed?
Multimodal approach to transport acknowledges that typical commuter trips are a combination of multiple modes, each serving a unique function and delivering a unique value. Efficiency will result if one were to use the best modes for the purposes intended in their best possible combinations.
A long-distance commuter is better off taking a metro/rail option along mass transport corridors, while bus will be a better option for shorter or off mass transit destinations. Last mile is best covered on bicycles, short haul taxis/ride hailing/3-wheelers or on foot. However, metro used for short hauls (e.g. crowded zone-1 in London) or buses for long hauls defeat the purpose of these very modes. Ride hailing taxis, arguably, are best used in combination with mass transport for long distance trips but we do see trips exclusively on taxis for long journeys, leading to roadblocks and loss of efficiency for users and operators alike. Multimodal transport is not just the most logical thing to do, it is also the most desirable.
Multimodal transport thrives on seamless changeover between modes, unified payments over integrated services and above all the complete availability of information. The key ingredients remain:
1. Infrastructure — E.g. multimodal stations, diverse modes, changeovers etc.
2. Integrated operations and payment facilities- E.g. unified tickets, complementing routes, unified transport company etc.
3. Information availability and dissemination
Infrastructure involves massive capital expenditure and takes years to build/retrofit. Future infrastructure development should consider the diversity of modes E.g. train stations with integrated platforms for metro, bus and taxi.
Integration of transport services and companies running them is an institutional challenge. That said, at least the payment issue has become history with contactless cards that obviate transport cards.
Interestingly, if information is available, it is neither as costly as building infrastructure nor as administratively challenging as merging agencies and ticketing to simply integrate such information and develop useful user inferences from it.
What multimodal means for India, Indonesia and other emerging market countries?
Emerging market economies have rapidly growing cities. This results in cities often overshooting the administrative limits and the transport services therein. The organic growth of cities creates unplannable pressures on transport corridors.
Data availability is also a challenge in such cities. Where they do have data, there lie apprehensions on data sharing.
Sharing of data, can only help higher number of rides, and their judicious distribution. Last mile connectivity and overall reach of non-car-based transport will improve and city economies will gain.
TRAFI- towards multimodal mobility
TRAFI works in emerging markets, typically with low availability of accurate and real time public transport data. Ride hailing services for Taxi, bike taxi etc. do bring apps but a typical user may have to shuffle between 4–10 apps to assess the best options. Moreover, it is impossible to see multiple modes as combinations, optimized for speed, costs, convenience etc.
TRAFI is already making this impossible as possible in Indonesia. India and rest of Asia will follow soon. We are helping cities use their existing infrastructure and operations better. We do this by making data better, integrating multiple modes and using TRAFI’s unique algorithms to give the best combinations of suggestions to TRAFI users.
About the author: Rajarshi Rakesh Sahai is a Strategy consultant with specialization in Smart Cities. He is the India Director and Country Manager for TRAFI Ltd.