Innovation Sphere

Projects Sharing Researchers


  • Bo Xu
  • Bhaskar DasGupta
  • Ouri Wolfson
  • Jie Lin
  • Daniel Ayala



Project TitleSoftware to Optimize Parking Spot Assignment and Navigation
Track CodeUIC-2012-069
Short Description

An automated guidance algorithm used to safely locate and guide drivers to available parking spaces in urban settings. 


Finding parking is a major hassle for drivers in urban environments. Studies conducted in 11 major cities revealed that the average time to search for curbside parking was 8.1 minutes and cruising for these parking spaces accounted for 30% of the traffic congestion in these cities on average. In Chicago, with over 35,000 curbside parking spots, 63 million vehicle miles per year are due to cruising while searching for parking! This adds up to over 3.1 million gallons of wasted gasoline and over 48,000 tons of CO2 emissions annually.

With the advent of location-based services and embedded wireless sensors, drivers are searching for applications that enable mobile devices to find open parking spots in urban environments. A prime example of this type of application is SFPark. However, services like these do not automatically guide users to the optimal spot; they simply identify where open spots are located and require the drivers to look at maps and decide where to park. UIC researchers have developed an automated guidance algorithm to more efficiently and safely guide drivers to parking spaces, saving as much as 30% in parking time compared to current methods.


  • Parking spot guidance systems


  • A 30% reduction in parking time compared to other methods
  • A significant reduction in the use of fossil fuels and CO2 emissions

For more information, contact Mark Krivchenia.

Posted DateMar 17, 2016 10:50 AM


Bo Xu
Bhaskar DasGupta
Ouri Wolfson
Jie Lin
Daniel Ayala


Mark Krivchenia
Sandra Thompson