The success or failure of Active Travel (AT) schemes relies on a robust understanding of how they are performing, and how they are likely to perform in the future as user numbers grow and travel behaviours change, across all classes. Poorly monitored and managed schemes not only create immediate safety issues; they lead to costly AT infrastructure being removed, and important new schemes mothballed – often without supporting evidence or understanding of real-world data on the actual situation and issues.
Object Recognition and modelling using Artificial Intelligence is providing Urban Planners, Traffic Planners, and Active Transport managers critical insights on the types and volumes of users, and how they behave, interact, and respond to each other and their changing environment; in real-time, and with exceptional accuracy.
Bicycle Network’s Artificial Intelligence Road Surveys (AIRS) methodology, in collaboration with VivaCity Labs AI powered sensors, is providing continuous, anonymised collection of behavioural data and hyper-accurate classified counts on all road user classes including vehicles, pedestrians, cyclists, and other micromobility modes. A variety of results can be analysed, including road-user volumes, path tracing and user speed results.
In 2021, Bicycle Network and VivaCity partnered with City of Port Phillip in Melbourne’s inner south-east to provide insights at several priority intersections that form part of the connected bicycle routes in the area. 11 AIRS sensors are permanently installed and are collecting continuous data for the City, with a plan to install more to in the future.
In February 2022, an e-scooter share scheme in the city introduced 1,500 e-scooters to the City’s transport network. City of Port Phillip planners are gaining critical insights into behaviours, traffic flow, and the potential locations of conflict between bike riders, micromobility users and pedestrians, road vehicles, and other road users to ultimately make decisions to improve the safety of these roads.
AIRS has been successfully utilised in collaborative projects with Bundaberg Regional Council, City of Yarra, Department of Transport (Victoria) and City of Melbourne, with an expanding network of local governments and transport groups finding use in the rich data attained through these survey methods.