When people choose to take their car to go to work, they don't usually take into consideration the time it takes to find a parking spot and walk. This creates a bias towards car usage and contribute to the constant rise of traffic in the metropolis.

What it does

IncitaPark shows us a better way to commute that is not available on Google Maps. It suggests hybrid path ideas, along with the usual alternatives (car and public transport). The idea of hybrid paths takes into account the existence of incentive parking lots and produces house -> parking by car then parking -> work by public transport itineraries. It also explicitly calculates the traditional alternatives in order to show how advantageous the hybrid option is.

IncitaPark tries to remove the bias for car usage by calculating an estimate of parking time and the time it takes to walk to the destination. Using a trimmed down, no nonsense interface, the user can easily visualize the possible parking spots.

How we built it

The app is built to work in a browser. It works using a client-server architecture. The server has the responsibility to analyse and digest all the data required to calculate the different types of path and the possible parking spots.

Challenges we ran into

We had a lot of trouble understanding the Montreal parking dataset.

Accomplishments that we're proud of

We are proud to present a fully working prototype that provides a great user experience.

What we learned

As junior programmer, we all acquired experience while having to solve problem quickly and efficiently.

What's next for IncitaPark

We are hoping to start a partnership with EXO, a company focused on incentive parking lots. We eventually would like to include live parking data for smart sensors into our infrastructure to improve the accuracy of our estimates.

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