1. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Mahalia Miller, HP Labs, NSF Research Associate / Stanford University *Chetan Gupta, HP Labs Date: August 12, 2012 An incident just occured. How severe will its impact be?

2. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Our research questions in traffic management: Understanding the past What was the spatial and temporal impact of a given incident on traffic congestion? What was the non-recurrent delay associated with a given incident? Predicting the future An incident just occurred. How severe will its impact be? 2 Photo credit: Jim Frasier/Flickr

3. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Research combines disparate sources of data 3 Sensor records Sensor metadata Weather records from web California Highway Patrol incident summaries California Highway Patrol reports free text Impact analysis

4. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Spatial graph helps link police reports, sensor records, and weather Graph is created from sensor metadata –Sensors in each corridor (I-605 North, e.g.) linked by parsing postmile and freeway for each sensor location –Free text in sensor metadata including on-ramp/off- ramp information aids linking corridors (I-605 South with I-5 South, e.g.) Reported incident start locations mapped to closest upstream sensor on given corridor Sensors linked to closest weather station 4 Sensor map created for District 7 highways (Los Angeles)

5. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Spatial graph helps link police reports, sensor records, and weather Graph is created from sensor metadata –Sensors in each corridor (I-605 North, e.g.) linked by parsing postmile and freeway for each sensor location –Free text in sensor metadata including on-ramp/off- ramp information aids linking corridors (I-605 South with I-5 South, e.g.) Reported incident start locations mapped to closest upstream sensor on given corridor Sensors linked to closest weather station 5 Diagram of relative sensor locations Traffic flow Reported incident location Closest upstream sensor, “b” Downstream sensor, “a” Upstream sensor, “c”

6. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Results of deriving delay definitions By integrating the delay definitions over space and time the following equations result: 6

7. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Algorithms track spatial and temporal spread of incidents to build baseline model 7 Spread of sample incident on I-5 in Los Angeles 4 minutes after incident start 14 minutes after incident start 29 minutes after incident start

8. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Impact Prediction Results 8 Yes False alarm Yes No Accident No Accident False alarm v-v* > 4.6 ρ > 0.22 #vehicles > 0 Yes

9. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. With high accuracy, model predicts which of 2 accidents will have higher impact Preliminary results indicate 90%+ accuracy for predicting relatively which incident will have a higher impact –Impact metric is economic losses from travel time delay –Determination done within 2 minutes of reported times Future work will compare incidents with both starting in a given time and space window to simulate traffic dispatcher’s decision where to focus limited resources 9

10. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Results indicate high degree of transfer learning possible Table: Prediction accuracy (%) by each bin selection choice for k classes of incident impact trained on the SF dataset and tested directly on LA: 10 MeasureBoundsAccuracy Cost$1090.07 Cost$10, $10086.05 Duration5 minutes91.28 Duration5, 30 minutes73.84

11. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Summary of key contributions Build baseline model for traffic conditions across time and space Predict the impact of an incident for an incident that just occurred using classification models as measured by incident duration and travel delay- induced economic losses Models show high level of transfer learning 11

12. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Thank you Contact: chetan.gupta@hp.com mahalia@stanford.edu Photo credit: ShaojingBJ/Flickr

13. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. For two regions, models predict incident duration and travel delay-induced economic losses Table: Example results from travel delay-induced economic losses 13 ExperimentClassesBounds ($)CountsAccuracyf-Measure SF-1210114,12495.590.95-0.96 … SF-3410,250,1000114,54,34,3673.730.47-0.95 LA-121075,9791.400.90-0.92 … LA-4310,10075,52,4575.870.55-0.89

14. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Model is good predictor of incident false alarms Results With 90%+ accuracy, within 2 minutes can determine if an incident will have a non-negligible delay or instead be a “false alarm” 14 Sample classification tree for incident delay impact < 1 veh-hr Yes False alarm Yes No (v*-v) up >4.6 Accident Yes No ρ>0.22 # vehicles>0 AccidentFalse alarm

15. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. State of California records highway traffic conditions California-based system (PeMS) stores billions of traffic records –from ~34,000 sensors across ~30,000 directional miles of highways (some offline) –at frequencies up to every 30 seconds for over a decade Schema: Sample: <01/06/2009_00:00:00,715918,7,5,N,ML,.615,30,100,55,.015,66.8,10,8,.0048,71.9,1, 10,22,.0155,69.7,1,10,25,.0246,62.7,1,,,,,0,,,,,0,,,,,0,,,,,0,,,,,0> We used aggregated 5-minute inductive loop Los Angeles (D7) data –Test study has ~300 sensors –Results from 5 minute periods for 2 months –Approximately 5 million records 15

16. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. California Highway Patrol (CHP) provides incident reports Summarized incident reports are available –Schema: We grouped incident types into 9 categories Approximate location, time, and raw incident details are in free text 16

17. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Weather data gives insight into rain and wind conditions facing drivers California Department of Water Resources records rain, wind, temperature, etc. We scraped this data for our test temporal period (January 1-March 1 2009) from their website Schema: Sample: 20090101 0 5.50 20090101 100 5.50 20090101 200 5.50 17

18. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Algorithms query database to access raw data Incident summary table –Schema: Devices table –Schema: Sensors table –Schema: Recurrent speed table (created after analysis of raw data) –Schema: sensorID, minutes (since midnight), computed recurrent speed> 18

19. © Copyright 2011 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. HP Confidential. Spatial graph helps link police reports, sensor records, and weather Graph is created from sensor metadata –Sensors in each corridor (I-605 North, e.g.) linked by parsing postmile and freeway for each sensor location –Free text in sensor metadata including on-ramp/off- ramp information aids linking corridors (I-605 South with I-5 South, e.g.) Reported incident start locations mapped to closest upstream sensor on given corridor Sensors linked to closest weather station 19 Diagram of relative sensor locations Traffic flow Reported incident location Closest upstream sensor, “b” Downstream sensor, “a” Upstream sensor, “c”