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7A_4_Gps data collection setting for pedestrian activity modelling
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7A_4_Gps data collection setting for pedestrian activity modelling

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  • 1. GPS Data Collection Setting For Pedestrian Activity Modelling Adel Bolbol Fernández Tao Cheng Department of Civil, Environmental & Geomatic Engineering UCL
  • 2. Outline • Background – Research Area – Positioning Sensor Devices – Scenario • Why – Epoch Rate Detection? – Pedestrians? • Test – Data – Method – Limitations • Observations – Positional Error – Route Length Error – Average Speed Error – Start & End Error • Conclusions Background Why? Test Analysis Conclusions
  • 3. Background: Research Area Location Information Activity Recognition “Sensor Data” •Diaries/logs GPS GSM Wi-Fi RFID •Algorithms Inferring Trip Trip Start Transport Trip Route Purpose & End Mode Modelling •Spatio-Temporal Human Activity •Travel Behaviour Background Why? Test Analysis Conclusions
  • 4. Background: Positioning Sensor Devices Travel Data Wi-Fi, GSM GPS & RFID Indoor Wide High Long Life Small Size Coverage Coverage Accuracy Battery Non- Logged Data Real Time Interactivity Desirable Properties Interactive Background Why? Test Analysis Conclusions
  • 5. Why Pedestrians? 1. Almost every journey starts and ends in the “Pedestrian” Mode (Walking) 2. Unlike vehicles, No Traffic Routing rules are followed Background Why? Test Analysis Conclusions
  • 6. Why Find Best Epoch Rate? “Epoch Rate” The frequency at which GPS measurements are taken “Data Collection Rate” (e.g. every 30 seconds) “Capture Rate” Is the more data the better? When is data too much? & Where is the threshold? Practicability of battery requirements? Best epoch rate for a realistic, accurate, battery efficient representation of human behaviour Background Why? Test Analysis Conclusions
  • 7. Scenario 1. Route Detection Walk 5 2. Detection of MoT 3. Start & End Locations 2 Work Bus 4. Trip Purpose GPS points User GPS Walk 3 Home – Work Home Walk Trip 4 Tube 1 Background Why? Test Analysis Conclusions
  • 8. Why Find Best Epoch Rate Detection? 10S 1. For Route Detection Epoch rate = 10 Seconds Background Why? Test Analysis Conclusions
  • 9. Why Find Best Epoch Rate Detection? 20S 1. For Route Detection Epoch rate = 20 10 Seconds Background Why? Test Analysis Conclusions
  • 10. Why Find Best Epoch Rate Detection? 60S 1. For Route Detection Epoch rate = 60 20 Seconds Background Why? Test Analysis Conclusions
  • 11. Why Find Best Epoch Rate Detection? 4 1. For Route Detection 2. For Mode Detection 3. For Detecting Start-End Work Epoch rate = 60 Seconds Walk Bus Home Background Why? Test Analysis Conclusions
  • 12. Test: Data • 7-8 minute walking journey • Data was collected every 1 second • Data was thinned to the following epoch rates: (1, 10, 20, 30, 60, 120 and 300 seconds) • 11 datasets were collected for the exact same journey Background Why? Test Analysis Conclusions
  • 13. Test: Method 1. Route taken 1. Positional Errors (Map matching) 2. Distance Travelled 2. Route Length Errors 3. Trajectory Speed 3. Average Speed Errors 4. Identifying Trip Start 4. Distances from First & End & last points to Trips’ Start & End Background Why? Test Analysis Conclusions
  • 14. Analysis: 1. Positional Errors From Averages of All Thinned Data Groups From Thinned Data Group 1 From Thinned Data Group 2 50 Positional Error (m) 40 Bearing in mind; 100 100 Positional Error (m) Positional Error (m) •Road links in London (278,691 links): 80 80 30 •Average Length of Road links = 80 m 60 SD = 98.47 60 20 •Average Speed of Pedestrians = 1.2 m/s40 40 Average 20 20 = 15 m 10 Therefore; 0 0 0 •To select the correct Road Link  We need1 at least 2 points 120 each -20 1 10 20 30 60 120 300 -20 10 20 30 60 on 300 •Most AppropriateMin Outlier Max Rate = Approx. 66s -10 Epoch Outlier Min Outlier Max Outlier 1 10 20 30 60 120 300 Epoch Rate (s) Epoch Rate (s) Epoch Rate (s) Min Outlier Max Outlier Results from 11 Datasets Background Why? Test Analysis Conclusions
  • 15. Analysis: 2. Route Length Errors 1100 4200 1000 900 Total Route Length (m) 800 Actual Route 700 Length = 600 667m 500 400 300 200 100 0 1 10 20 30 60 120 300 Epoch Rate (s) Min Outlier Max Outlier Background Why? Test Analysis Conclusions
  • 16. Analysis: 3. Average Speed Errors 2.5 2.3 2.0 1.8 Average Route Speed (m/s) 1.5 Actual Average 1.3 Speed = 1.0 Approx. 1.2 m/s 0.8 0.5 0.3 0.0 1 10 20 30 60 120 300 Epoch Rate (s) Min Outlier Max Outlier Background Why? Test Analysis Conclusions
  • 17. Analysis: 4. Distances from last points to Trips Starts & Ends 250 200 Distance from End Destination (m) 150 100 50 0 1 10 20 30 60 120 300 Epoch Rate (s) •Pedestrians Average Speed = 1.2 m/s Min Outlier Max Outlier •Worst Case: 10s = 12m 20s = 24m 30s = 36m + Positional Errors 60s = 72m •Do we require the exact location? 120s = 144m •If not ---- Land Use/Mix data 300s = 360m Background Why? Test Analysis Conclusions
  • 18. Conclusions 1. Positional Accuracy = Approx. 15-20m 2. Length Calculation: 20 sec was most accurate 3. Speed Calculation: 30 & 60 sec 4. Start & End: 10 & 20 sec – 1 sec good accuracy & high uncertainty 5. Around 20 or 30 sec is most appropriate for pedestrian route modelling Background Why? Test Analysis Conclusions
  • 19. Thank You & what are your questions? a.bolbol@ucl.ac.uk

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