Studies have estimated that on a daily basis 30% of traffic in the downtown area of major cities is due to cruising for parking spots. In addition to aggravation and the waste of time and fuel for drivers looking for parking, this also contributes to additional waste of time and fuel for other drivers as a result of traffic congestion. For example, it has been reported that over one year in a small Los Angeles business district, cars cruising for parking created the equivalent of 38 trips around the world, burning 47,000 gallons of gasoline and producing 730 tons of carbon dioxide.
Over the past two decades, so-called Parking Guidance and Information (PGI) systems have been developed for better parking management. PGI systems present drivers with dynamic information on parking within controlled areas and direct them to vacant parking spots. Parking information may be displayed on variable-message signs at major roads, streets, and intersections, or it may be disseminated through the Internet and through portable devices (e.g., smartphones). However, we notice that PGI systems have several shortcomings: (i) Drivers may not actually find vacant parking spots by merely following guidance. More drivers go toward the same available parking spots and it is possible that none is free by the time some drivers arrive. (ii) Worse, by guiding many drivers to an area with one or very few vacant spots, a PGI system often creates additional traffic congestion instead of alleviating it. (iii) Even if a driver is successfully guided to a parking spot, a PGI system encourages finding any parking spot at the expense of missing a better spot. (iv) From the point of view of parking operators (especially cities), parking space utilization becomes imbalanced.We propose a new “smart parking” system which receives a driver’s parking request and allocates the best parking space for him. In contrast with PGI systems, our system changes from “driver parking searching” to “system allocation”. The system runs as follows.
Drivers who are looking for parking send a request to a Driver Request Processing Center (DRPC). This may be done by entering a specific destination address in a standard onboard vehicle navigation system or through a smartphone. A request is accompanied by two driver-defined requirements: an upper bound on parking cost and an upper bound on the walking distance between a parking spot and the driver’s actual destination. This information may be part of “preference” settings that the driver has already input or they can be adjusted for each request. The request contains basic information such as license number, current location, etc.
The Smart Parking Allocation Center (SPAC) collects all driver requests in the DPRC over a certain time window and makes an overall allocation at decision points in time seeking to optimize a combination of driver-specific and system-wide objectives. This is accomplished through an optimization engine based on an algorithm we have developed. An assigned parking space is sent back to each driver via the DRPC. If a driver is satisfied with the assignment, he has the choice to reserve that spot. Once a reservation is made, the driver may still obtain a better parking space (with a guarantee that it can never be worse than the current one) before the current one is reached. This is accomplished through capabilities built into the optimization.
The Parking Resource Management Center (PRMC) then updates the corresponding parking spot from vacant to reserved, and provides the guarantee that other drivers have no permission to take that spot. If a driver is not satisfied with the assignment (either because of limited parking spots or his own overly restrictive parking requirements) or fails to accept it for any other reason, he has to wait until the next decision point (typically, a minute) and may change his cost or walking-distance requirements to increase the chance to be allocated if the parking system is highly utilized (it is of course possible that no parking space is ever assigned to a driver). While the driver is en route to the reserved spot, the system charges an additional fee on a per-minute basis.
“SmartParking” Lab Implementation
We implemented the “smartparking” idea in the RULE platform.
Video is taken from two overhead cameras and edited. LED display is clear in this version.
Video is taken by a video camera. The whole parking process is shown in this video.
“SmartParking” Implementation at BU
The “smartparking” idea was implemented in a garage of Boston University. We built our own ultrasonic sensors to detect parking status.
Drivers may use an iPhone App. to log into our system and make a parking reservation.
October 30, 2011
New Technology finds closest parking spots, best price