MIT Researchers Develop Parking-Aware Navigation System
Looking for a parking space in a crowded lot could soon get easier. MIT researchers have announced the development of a parking-aware navigation method that steers drivers to parking lots…
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Looking for a parking space in a crowded lot could soon get easier.
MIT researchers have announced the development of a parking-aware navigation method that steers drivers to parking lots that offer the best balance between proximity to the destination and the likelihood of finding a space.
According to an MIT news release, in Seattle-area simulations, this new approach yielded up to 66% time savings in congested scenarios (about 35 minutes less per trip) and approximately a 60% reduction in total travel time compared with waiting for spots. Additionally, researchers reported a 20% improvement over the always-drive-to-the-nearest-lot strategy.
According to MIT, to solve the parking problem, researchers developed a “probability-aware approach” that takes into account the following criteria:
- All possible public parking lots near a destination
- The distance to drive to the parking lots from a point of origin
- The distance to walk from each lot to the destination
- The likelihood of parking success
“This frustration is real and felt by a lot of people, and the bigger issue here is that systematically underestimating these drive times prevents people from making informed choices. It makes it that much harder for people to make shifts to public transit, bikes, or alternative forms of transportation,” said MIT graduate student Cameron Hickert, the lead author on a paper describing the work that was published in Transactions on Intelligent Transportation Systems.
Researchers note that the data on parking availability could come from several sources. For example, some parking lots use magnetic detectors or gates to count cars entering and exiting. They considered these sources in their evaluation, but they believe their system is more practical for real-world deployment. They also studied the effectiveness of using crowdsourced data.
“Right now, a lot of that information goes nowhere. But if we could capture it, even by having someone simply tap ‘no parking' in an app, that could be an important source of information that allows people to make more informed decisions,” Hickert explains.
The research team for the project includes Hickert and collaborators Sirui Li, Zhengbing He, and Cathy Wu. Cintra, MIT Energy Initiative, and the National Science Foundation (NSF) supported the study.
