ParkNet

Sutha Mathur, Tong Jin, Nikhil Kasturirangan,Janani Chandrashekharan, Wenzhi Xue, Marco

Gruteser, Wade Trappe

Rutgers University

Michael BetancourtUCF - EEL 6788

Dr. Turgut

Drive-by Sensing of Road-Side Parking Statistics

Overview

1.Introduction2.Design Goals and Requirements3.Prototype Development4.Parking Space Detection5.Occupancy Map6.Mobility Study7.Improvements8.Conclusion

Introduction - Problems

• Traffic congestion costs tons of moneyo 4.2 billion lost hourso 2.9 billion gallons of gasoline wastedo Looking for parking contributes to these numbers

• Lack of informationo Hard to determine best prices for meters and

where they should be placedo Current parking detection systems are costly

Introduction - ParkNet

• Drive-by Parking Monitoringo  Uses ultrasonic sensor

attached to the side of cars

o Detects parked cars and vacant spaces

• Attaches to vehicles that comb through a city (taxi, police, etc.)

• Location accuracy based on GPS and environmental fingerprinting

Introduction - Objectives

• Demonstrating  the feasibility of the mobile sensing approach including the design, implementation and evaluation of the system

• Proposing and evaluating a method of environmental fingerprinting to increase location accuracies

• Showing that if the mobility system were currently attached to operating taxis, it would operate with enough samples to determine parking availability

Design Goals - Real-time Information• Improve traveler decisions with respect to mode of

transportation• Suggesting parking spaces to users driving on the

road• Allow parking garages to adjust their prices

dynamically according to demmand• Improve efficiency of parking enforcement in

systems that utilize single pay stations for multiple parking spots

Design Goals - Parking Information

• Space counto Sufficient for most parking applications

• Occupancy Mapo Useful for parking enforcemen

Design Goals - Cost and Participation• Low-cost Sensors

o Typical per spot parking management systems ranges from $250 to $800 per spot

o Current systems are difficult to place in areas without marked parking spots

•  Low Vehicle Participationo Be able to function without a lot of cars fittedo Keep costs down

Prototype Development - Hardware• Moxbotix WR1

rangefindero Waterproofo Emits every 50mso 12-255 inches 

• PS3 Eye webcamo 20 fpso Used for ground

trutho Not in production

• Garmin GPSo Readings come at

5Hzo Errors can be less

than 3m

• On-board PCo 1GHz CPUo 512 MB Ramo 20 GB HDo PCI WiFi cardo 6 USB ports

Prototype Development - Deployment• System was placed on 3

vehicles• 3 specific areas were

marked off to be analyzed

• Data was collected over a 2 month period

• Drivers were oblivious to the data collection

• All range sensor data is tagged with:Kernel-time, range, latitude, longitude, speed

Prototype Development - Verification• PS3 Eye

o Mounted just above the rangefindero Took pictures at 20fps that were time tagged

• Each picture was manually checked to see if there was a car parked

• This was used to verify the data collected from the system

Parking Space Detection - Challenges• Ultrasonic sensor does not have a perfectly narrow-

width• GPS Errors• False alarms

o Other impeding objects: Trees, people, recycling bins

• Missed detectionso Parked vehicles classified to be something other

than a parked car

Parking Space Detection - Dips

• A "dip" is a change in the rangefinder readings which usually occurs when there is an object in view

Two Cars Parked Together

Far Close

Parking Space Detection - Algorithms• Slotted Model

o Determines which dips are classified as carso Subtracts the total number of cars found with the

total number of spaces available in the area• Unslotted Model

o Determines which dips are classified as carso Measures the distance between dips to see if it is

large enough to fit a car• Training

o 20% of the data is used for trainingo 80% of the data is used for evaluating

performance

Parking Space Detection - SlottedSlotted Model Accuracy

Parking Space Detection - UnslottedUnslotted Model Accuracy

Occupancy Map - GPS Error

• Selected 8 objects and determined their absolute GPS position using Google Maps

• Corresponded the GPS reading gathered from the trials to the objects

• Used the reading from one object to correct the others

Occupancy Map - Environmental Fingerprinting• Fixed objects in the

environment used to increase positional accuracy

• Recognition Walkthrough1.GPS coordinates indicate

system is near known object• Parses rangefinder readings• Determines what is not a

parked car• Tries match the pattern with

the known object• If object found, correct

position if within 100m

Mobility Study - Taxicab Routes

• Public dataset of 536 taxicabs GPS position every 60 seconds

• Routes were approximated by linear interpolation• Found that taxicabs spend the most time in

downtown areas where parking is scarce• Determined the mean time between cabs visiting a

particular street.

Mobility Study - Taxicab Mean Time

Greater San Francisco Downtown San Francisco

Mobility Study - Cost Analysis

• Current Cost:o Parknet: (~$400 per sensing vehicle) x (number of

vehicles needed to get desired rate of detection)o Fixed Sensor: ($250-800 per space) x (number of

spaces)• Uses opportunistic WiFi connections to transfer data• Easily managed due to the much smaller number of

fixed sensors• Example

o 6000 parking spotso Parknet: 300 cabs, 80% coverage every 25

minutes, $0.12 milliono Fixed Sensor: $1.5 million

Improvements

• Multilane Roadso Moving cars could be determined by long dipso Rangefinder would need to be longer

• Speed Limitationso Sensors currently work best at speeds below

40mph• Obtaining Parking Spot Maps

o Difficult for large areaso Algorithms could determine location surroundings

after data collection has been started• Using vehicles current proximity sensors

Conclusion

• Data collectedo 500 miles over 2 months

• Accuracyo 95% accurate parking space counts o 90% accurate parking occupancy maps

• Frequency and Coverageo 536 vehicles equippedo Covers 85% every 25 minutes of a downtown areao Covers 80% every 10 minutes of a downtown area

• Cost Benefitso Estimated factor of 10-15 times cheaper than

current systems• Questions?

Links

Fixed Parking System (SFpark)http://sfpark.orghttp://vimeo.com/13867453