Miovision, a traffic systems technology company, this week announced at the Transportation Research Board annual meeting the creation of Miovision Labs.
Miovision Labs is a new division within the company focused on leveraging transportation data and smart traffic technology to take cities closer to embedding intelligence in urban infrastructure.
The United Nations projects that 66 percent of the world’s population will live in cities by 2050, which puts enormous pressure on urban traffic and infrastructure, considering cities already struggle with moving people and goods within their cores.
“For the last century, transportation infrastructure ‘progress’ has been all about building more roads and adding more lanes to try to move more people, cars, trucks and freight from Point A to Point B,” said Kurtis McBride, CEO and cofounder of Miovision. “That brute force approach has become obsolete. In the next decade, cities will undergo rapid changes, and transportation networks will be one of the most important piece in smart cities of the future.”
Miovision Labs is composed of a team of technologists and product strategists focused on the future of traffic. The team will apply its expertise in communications, computer vision, deep learning, AI, big data analytics, and embedded device design to improve traffic flow for cities.
In one of its first research projects, Miovision Labs has partnered with CPCS, a management consulting firm focused on transportation strategy, policy and economics, to conduct research on freight data. The objective is to study how new types of traffic data from passive sensors, video cameras, GPS, and other sources can be used to understand and improve how freight moves through urban and metropolitan areas.
“Typically, cities have manually counted trucks or done surveys about how commodities flow through and around their communities, but those methods were time intensive, prone to mistakes and only provided a partial picture,” said Donald Ludlow, managing director of CPCS’s US operations. “Today we have a variety of new data sources from road sensors, vehicle data streams, image data, truck permits and more. Most of these are just starting to be understood, and we’re going to figure out how to use them.”
Miovision Labs will also work with the University of Toronto on research around conflict analysis. Because real-world data collection for conflict analysis is so labor intensive, agencies rarely use conflict analysis to identify where infrastructure investments can be prioritized or to measure the impacts of infrastructure improvements. This necessitates crashes occurring in order for improvements to happen.
“Miovision has made great progress in vehicle tracking using computer vision and can provide trajectories of real vehicles, pedestrians, and bicycles,” said Matthew Roorda, professor of civil engineering at the university. “The partnership with the university will identify dangerous interactions that happened between these roadway users, and will give insights that can lead to better decisions about infrastructure. The important piece with this project is that is using real-world data, not a simulation.”
Also, Miovision Labs is working with the new World Bank-led Open Transport Partnership to change the way data companies collaborate with governments for the public good. The partnership will empower resource-constrained transport agencies to develop better, evidence-based solutions to traffic and road safety challenges.
“The research being conducted through these partnerships represent important steps toward smart cities,” McBride said.