The Canadian city of Vancouver has hosted a Decode Congestion Hackathon that called on residents to create safe, efficient solutions for the city’s streets and transportation network, using data and new technologies.
The city outlined five key areas for the hackathon’s 150 participants to focus on: improve road safety; improve the monitoring of traffic conditions and trends; ensure a smart and efficient transportation system; coordinate street use; and prioritise people and good movement.
Busjousting, an AR gamification tool that can help collect bus data and encourage transit use, won first prize. TracSmart, a machine learning solution that can detect vehicles in static images, placed second, and Policy Based Traffic Signals, a traffic camera that uses machine vision and edge computing technology to detect cyclists, pedestrians and buses, finished third.
Participants were given access to data sets about traffic count; city fleet telematics; street infrastructure; traffic safety; community amenities; bike share and demographics. The winners were awarded C$5,000 (£2,914), C$2,000 (£1,165) and C$500 (£291), respectively.
“This was an opportunity for our tech industry, our students, people who are transportation professionals or just really interested in the topic to try and take a stab at solving the challenge statement we presented them with,” said Sherwood Plant, senior street use and traffic coordination engineer for the City of Vancouver.
The hackathon was designed in part to help Vancouver understand baseline traffic congestion pain points and encourage walking, cycling, transit and shared vehicles over private cars. The effort could also help the city achieve its goal of having zero transit-related deaths.
“We are a built-out city,” added Plant. “It’s very challenging to add additional capacity in single-occupancy vehicles so we have to look at how can we best move the most people, the most goods efficiently on our network.”
