P ARK N ET : D RIVE - BY S ENSING OF R OAD -S IDE P ARKING S TATISTICS Suhas Mathur, Tong Jin, Nikhil Kasturirangan, Janani Chandrashekharan, Wenzhi Xue, Marco Gruteser, Wade Trappe MobiSys 10 - Sowhat

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

M OTIVATION Societal costs due to traffic congestion Parking Lack of information Value of real-time information Government – adjusting prices Driver – suggested parking spaces, better decision

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

O BJECTIVE Providing parking information in slotted / unslotted areas Parking information - Space Count Occupancy Map

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

R ELATED W ORKS SF-park project - Stationary sensor network Sensor node installed in the center of each parking spot Repeaters and forwarding nodes for connectivity Centralized parking monitoring system Drawbacks of SF-park project Large installation and maintenance cost Limited to slotted parking spots Wireless relay nodes needed

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

P ARK N ET - O VERVIEW Ultrasonic rangefinder GPS receiver Ultrasonic rangefinder GPS receiver

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

P ARK N ET - H ARDWARE Ultrasonic sensors Why ultrasonic? Low cost – compared to laser rangefinder Nighttime operation – compared to camera Increasing availability to support parking functions Setting Range >= half the width of roads, 12~255 inches(0.3~6.5m) Sampling rate – several samples over the length of a car, 50ms

P ARK N ET - H ARDWARE On-board PC 1GHz CPU 512MB RAM 20GB hard disk Atheros a/b/g mini PCI card 6 USB 2.0 ports GPS receiver Garmin 18-5Hz GPS 12 channel receiver 5 GPS readings / sec WAAS correction of errors less than 3 meters Parking estimation server

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

P ARK N ET - D EPLOYMENT 3 vehicles 2 month 3 road-side area (57 marked slotted parking spots/ 734m / 616m) Total of more than ~500 miles of data Camera for ground truth GPS trip-boxes Trigger to collect data Guard distance/time

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

P ARK N ET – D ETECTION S ENSOR R EADING

P ARK N ET – D ETECTION F LOW & P RE -P ROCESSING Pre-processing Removing dips that have too few readings < 6 sensor readings Assuming max speed = 37 mph(58.2km) a car length = 5 m

P ARK N ET – D ETECTION F ILTERING Comparing the width and depth of each dip against thresholds Threshold = the values make the minimum overall error rate Overall error rate = false positive rate + miss detection rate Depth >= 89.7 inches (2.27meters) Width >= 2.52 meters

P ARK N ET – D ETECTION W IDTH C LASSIFICATION Slotted Dips of a width > 2*threshold 2 cars Unslotted Estimating the spatial distance between dips that have been classified as parked cars Comparing the distance to the length of a standard parking space (6 meters)

P ARK N ET – D ETECTION M ETRICS & E VALUATION Missed detection rate p m False positive rate p f Slotted– n/ n Unslotted – d/ d

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

P ARK N ET - E NVIRONMENTAL POSITIONING CORRECTION GPS E RROR C ORRELATION

P ARK N ET - E NVIRONMENTAL POSITIONING CORRECTION E NVIRONMENTAL FINGERPRINTING Comparing reported location of the pattern produced by fixed objects Priori known location of this pattern Error vector e i (x,y) = t i (x,y) – l i (x,y) t i (x,y) : the true location of object i l i (x,y) : the location stamp of object i Adding error vector to the location estimates of all detected cars within 100m of this object

P ARK N ET - E NVIRONMENTAL POSITIONING CORRECTION E VALUATION Using Hungarian algorithm to match cars to parking spots

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

Areas with greater amount of street parking utilization = areas with greater presence of taxis Cost Why ParkNet better? Nonguaranteed, random sampling P ARK N ET - V IABILITY ParkNetSF-park Cost400 / vehicle / spot Number300 taxis6000 spots Total120,0001,500,000

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

D ISCUSSION Multilane roads Speed limitations Obtaining parking spot maps

O UTLINES Motivation Objective Related Works ParkNet Overview Hardware Deployment Detection Environmental positioning correction Viability Discussion Conclusion

C ONCLUSION ParkNet providing road-side parking info Space count Occupancy map 300 taxis updating every ~25min for 80% Some technical problems while implementing to real life

T HANKS FOR L ISTENING ~