For the second year in a row, the City of Vancouver, Canada hosted a Decode Congestion Hackathon that challenged residents to use data and new technologies to create solutions that optimize street use for an efficient, safe, and reliable transportation network.
Using data and information provided by the city, about 150 participants focused on five key areas:
- improving road safety;
- improving the monitoring of traffic conditions and trends;
- ensuring a smart and efficient transportation system;
- coordinating street use; and,
- prioritizing people and goods movement.
Solutions were judged on innovation, feasibility, user experience, strategic thinking, and alignment with the challenge.
First place winner, Busjoust, is a tool that gamifies data collection on public transportation through an augmented reality game, encouraging users to collect data samples while using transit, and rewards them with points that can be used in inter-bus competitions. Busjoust could help the City and TransLink collect more data and develop a further understanding of its transit usage, as well as encourage people to take transit.
TracSmart took second place with a tool which uses machine learning to review existing traffic stills from City of Vancouver intersection cameras to quantify congestion and provide alerts for anomalous patterns or identify high congestion periods. This could help the City monitor the performance of its network and collect further data.
Policy Based Traffic Signals was third with a tool that uses machine visions combined with edge computing technology to detect buses, pedestrians, and people on bikes to initiate signal preemption. This could help the City monitor travel performance and improve people moving capacity.
“The DeCode Congestion Hackathon was a great success, highlighting the diversity of viewpoints and complexity of the challenge statement through the different proposed solutions,” said Sherwood Plant, senior street use and traffic coordination engineer.