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Data-Driven Transportation:
The Smart Imperative

pencil By Arushi Srivastava
calendar 27 January 2022

When we talk about smart or intelligent transportation, you might think of modernized railroads, traffic lights connecting to autonomous vehicles or even flying cars or hi-tech drones. A lot of these possibilities are right around the corner and beyond. A more modern, digital, human-centric intelligent transport future is closer than ever, with many public and private organizations currently laying the foundations to bring smarter, more intelligent transportation into reality.

Through discussions as part of my role with the NTT Smart World team, almost every city or government agency had questions, concerns, opinions and vision. Yet, it was clear that traffic and transport needed to be a vital part of the conversation to make cities truly smart. During one chat, we were asked what smart transport meant to us. You can’t define smart transport without mentioning the data analytics platform that enables the system of systems, from the legacy and modern ticketing and tolling systems to the futuristic, intelligent vehicle to infrastructure solutions and everything in between. When it comes to smart transport, we took a use case centric approach to developing our analytics platform.

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Fig 1. The use cases for Smart Transportation

Some of the primary challenges that face the public and private sector in transportation for which Smart Transportation Solutions can help are:

  • Decreasing ridership due to changing socio-economic needs of citizens
  • Variety of customer experience needs to be served by “one-size” solutions
  • Inequity in providing services to the people who need it most
  • Declining customer confidence, especially in the wake of COVID-19
  • Concerns on environmental sustainability

We found that even though these challenges are fundamentally different, the master key to resolving them strategically and tactically was data and the insights that disparate data sets hold across systems. If managed and analyzed optimally, data that is ever-changing and mostly underutilized can solve the most complex challenges for commuters, drivers, policymakers, government agencies, technology providers, OEMs, service operators and most importantly - the traffic and transportation agencies.

For example, understanding the needs of the commuters in real-time and the journeys they take or intend to take can help traffic and transport agencies customize a solution for individual commuter groups. By using advanced analytics and machine learning, agencies can understand future demand and design operational and sanitization schedules and inform customers about predicted occupancy, status etc. to enhance their confidence in returning to transit after a pandemic such as COVID-19 or large sporting events. Understanding the fuel consumption, asset usage, conditions, maintenance needs and predicted demands could help understand the current environmental impact and gaps in reaching the sustainable future enabled via electric, autonomous, on-demand mobility services.

Technology enablement, user-centric systems, or optimized asset utilization, irrespective of what combination of goals are the target of your next transportation initiative, you will need a data-driven transport network that supports the delivery of today’s services while providing advanced insights and flexibility to embrace the transportation models of tomorrow. Such resiliency can help agencies and their service networks adapt to changes in how transportation services are delivered, flexibly respond to issues or outages, and use analytics to predict changing transport requirements.

NTT Smart Solutions can help create data-driven transportation solutions by enabling data ingestion, advanced analysis, and the overall delivery of data-driven insights. How? Read more here.

author

Arushi Srivastava

Senior Director, Deployment, Operations & Expert Services at NTT Smart World

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