During the Community Engagement Meetings, better public transportation/new transportation/anti-congestion was one of the top 10 trending responses regarding what participants wanted to create in Corktown.
We combine machine learning (ML) with our patented stochastic model dynamics, to offer real time analytics and predictions which improve the commute of people and cargo, traffic management, safety and quality of life. Our algorithms have shown high accuracies for predictions 2 hours into the future. In Gothenburg, Sweden we tested 99% prediction accuracy for traffic demand. Our findings are backed by scientific publications. Unlike Google Maps, Waze, INRIX, TomTom, we provide reliable ETAs that hold true even in dense traffic.
For the Indianapolis challenge we suggest an innovative way to address urban congestion, emissions and associated costs based on proven field solutions that work by shifting traffic demand to alternate times when demand is lower. The approach will use our existing patented technology for congestion prediction and traffic demand, including predicting best times to departure. It is a model that works opposite to the traditional toll road concept. We propose then, a small-scale pilot on a congested city corridor that will be directed towards peak time commuters to promote a change of driver behavior by attempting to shift their departure times to alternate time slots and away from peak hour traffic, leading to reduction of morning and afternoon peak commute. Apart from using this method to manage Monday-Friday traffic demand, these shifts can also be applied to manage demand during special events.
A parallel goal of this project is to convert more Car-Centric users, currently estimated at 45%, to Combiners, currently estimated at 37%. To that end, collaboration with the City, IndyGo and accessibility of the MyStop app platform by our API, for enhanced functionalities, monitoring participation and promotion of the pilot incentives, will go a long way for this approach to be properly implemented.
Other goals include the identification of challenges and solutions for a wider project implementation and the promotion of flexible work hour policies by employers.