The team also integrated its detection data with reference maps to create a spot-accurate map of parking availability. They faced a major challenge accomplishing this because the location coordinates provided by a GPS receiver are only typically accurate to three meters. With an approximate parking spot length of about seven meters, a vehicle could easily be matched to an incorrect adjacent spot. So they developed another algorithm that uses the ultrasonic sensor readings to detect certain fixed objects, such as trees and street signs. This allowed them to decrease their error rate by more than half.
After proving that the concept worked, Gruteser and his colleagues wanted to see whether such a system could effectively be deployed in a large city by putting sensor systems in vehicles that regularly drive around, such as taxis, police cars, and other government vehicles. The team used a public data set of 536 taxicabs in San Francisco to study the cars’ mobility patterns. While the cabs visited some parts of the city too rarely to make any data they collected useful for a real-time parking map, the sampling provided by these same cabs in the downtown area of San Francisco was more than adequate to cover the smaller area.
The engineers estimate that they could cover the downtown San Francisco area using only 300 cabs for roughly $200,000, a cost-saving factor of about 15 over a fixed-sensor system. “We know that this savings is related to the fact that we’re getting a nonguaranteed, random sampling of parking spaces, versus the continual monitoring offered by fixed sensor systems,” Gruteser says.
Developing a system for real-world deployment shouldn’t be that difficult, Gruteser says. The team chose to use ultrasonic range finders because of their relatively low cost compared to laser range finders and automotive radars, better nighttime operation compared to cameras, and their increasing availability in parking-assistance and automated parking systems in cars. This means that engineers could potentially use ultrasonic sensors already present in vehicles in a future parking-monitoring system.
While the researchers relied on opportunistic Wi-Fi connections to transmit their data from the cars to the central server, vehicles could report their data over widely available cellular modems, they say. Finally, Gruteser says, it would be fairly simple to distribute parking availability information over the Internet, similar to the way Google overlays traffic congestion data on its maps. Or, working with navigation device companies, it could be sent to commercial GPS receivers.
The Rutgers team has submitted its project report to the Annual International Conference on Mobile Systems, Applications, and Services (Mobisys), to be held in June in San Francisco.
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