By Elena Aung, MEng ’20 (CEE)
The technologies that will put order to the chaos that is urban mobility aren’t the trendy new ones like ride-hailing or autonomous vehicles. The complex urban mobility problem requires technologies that enable connection and adaptability. The transportation industry has envisioned seamless mobility which is a digitally connected multi modal transportation network that is more efficient and more convenient than the status quo. The foundational technologies that make seamless mobility systems possible lie in internet of things (IoT) and big data.
“Imagine a single application that allows you to book a trip to your final destination and provides a combination of different transportation mode options like using a car via private ride-hail service followed by train via public transit, all while adjusting prices based on demand and routes based on congestion and weather.”In order to create this interoperability, a seamless mobility system relies on data which will mainly be produced by the IoT. IoT is the concept of having a collection of devices that are embedded into the physical environment and are connected to the internet to provide information. From providing information about a train’s engine or about traffic congestion on a highway, the data that these devices collectively provide serves as the lifeblood of a seamless mobility system. Without data, interoperability between the different subsystems is impossible since there is no information to share or analyze. The data produced from IoT will be massive and a seamless mobility system will need to use big data technology in order to store, analyze and share that data efficiently. Big data itself is high volume data that is generated at a high velocity and may come in a variety of different formats (NIST, 2015). Big data is too large and complex for traditional database systems and requires a scalable architecture to store, process, and analyze this data efficiently. In order to achieve the required scalability, big data architecture typically stores the data across multiple servers and distributes processing across multiple processors that are working in parallel. Big data architecture serves as the backbone of the digital layer of seamless mobility systems as it enables the system to use real time data analysis to make dynamic decisions that efficiently match supply and demand. In the long term, storing all that data also allows transportation officials to observe trends in supply and demand over time which could be used to adapt the mobility system for the future. The technologies that make seamless mobility possible — IoT and big data — are already established and in use in different fields today. While popular upcoming technologies like autonomous vehicles can certainly address some mobility issues, seamless mobility really hinges on meaningfully integrating the different subsystems of the transportation network together.
About the author
Eindra (Elena) Aung is a current Master of Engineering student at UC Berkeley graduating in May 2020 with 3 years of work experience in Transportation Engineering and Planning. Connect with Elena.References
- DuPuis, Nicole, Cooper Martin, and Brooks Rainwater. “City of The Future: Technology & Mobility.” National League of Cities, 2015.
- World Economic Forum (WEForum). “Designing a Seamless Integrated Mobility System (SIMSystem) — A Manifesto for Transforming Passenger and Goods Mobility.” World Economic Forum (WEForum), January 2018.
- National Institute of Standards and Technology (NIST). “NIST Big Data Interoperability Framework: Volume 1, Definitions.” National Institute of Standards and Technology (NIST), September 2015.
Op-ed: The technologies behind the future of transportation was originally published in Berkeley Master of Engineering on Medium, where people are continuing the conversation by highlighting and responding to this story.