Human Factors and VII Enabled Applications

1. Human Factors and VII Enabled Applications A Role for Naturalistic Data Jim Sayer University of Michigan Transportation Research Institute

2. UMTRI • Established in 1966 • Founding sponsors: vehicle manufacturers • Research oriented toward highway safety • $17 million per year research budget • About 120 staff members • Report to the Vice President for Research

3. Combining Human Factors and Engineering Domains of Research Dynamics and control of the motor vehicle, modeling Capabilities, limitations, driver behavior, test methodologies UMTRI SBA AAD HF ERD TSA Biosci KNOWLEDGE The normal driving process, as controlled by people - manually and with driver assistance systems. Program on the Driving Control Process

4. Driver Assistance Systems Research • Much of this work is field operational tests (FOTs) • Fleets of instrumented vehicles (cameras, radars, DGPS, accelerometers, etc.) • Data acquisition systems • Data archiving • Includes a wealth naturalistic baseline data

5. Today’s Discussion • What naturalistic driving data currently exist that could help guide/support VII weather related applications? • Driving behavior in inclement weather • What is the behavioral baseline? • A need to better understand driver visibility and the use of windshield wipers • I need historical precipitation data • Sharing of previously unknown resources

6. Origins of the Naturalistic Data

7. UMTRI Naturalistic Data with Driver Assistance Systems • All studies include baseline periods • Almost 800K miles of naturalistic data collection with passenger cars and heavy trucks • With additional experience on test tracks, on-road and pilot testing

8. Data Acquisition & Remote Monitoring End-of-trip data upload cellular modem: Webpage tracking vehicle and system 750K miles of naturalistic data with 350 drivers

9. Approx. 3200 hrs (312 weeks, 1250 trips) >400 signals About 700 GB including video/audio 10 Hz, 1Hz, event-triggered, histograms Cameras (forward and face), in-cabin microphone Objective data: vehicle motion and state, environment, driver activities, sensing and processing (vision, GPS/map, radar, constructed maps) Remote system monitoring Linked objective data to subjective responses/ demographic data Recent FOT Data Scope

10. ACAS Project database Data Archive/Server Test Vehicle DAS Visualization/Analysis Tools DAS files to tables ACAS SQL analyzer Ÿ Analyst’s DBs Sensor DB manager Ÿ CAN Fusion Data browser Ÿ Threat Video viewer Ÿ Radar... Desktop database Ÿ Participant DB ACAS Spreadsheet Ÿ subjective Main Cpu Data DB C questionnaires e l l p h o n e Forward camera Phone DB Face camera Audio ... Video/Audio Video Cpu files Integrated Data Collection

11. Data Analysis and Warehousing Relational database to analyze and mine FOT data

12. Video and Visualization Tools

13. Overlaying Vehicle Data with Crash and Roadway Data Date of Crash Gender of Driver Weather condition Functional Class Selected crash data spatially “joined” to road segments Functional Class AADT Urban/Rural Selected HPMS data spatially “joined” to road segments Geographic Reference Map of ADAS warnings

14. A Naturalistic Examination of Windshield Wiper Usage

15. The Data Set • 96 drivers from Michigan, USA • Urban, suburban and rural residents • Ranged in age (20-70) • Drove 4 weeks each, instrumented vehicle replaced their personal cars • 137,000 miles (220,000 km), 13,600 trips • 325,000 wiper cycles on 1,700 trips • 170 windshield cleaning events

16. Wiper Utilization by Month Rain? Spray? Rain?

17. Wiper Speed Selection: Ambient Light Level

18. Summary • No relationship between wiper speed selected and road class or vehicle speed • Average wiper usage is 8.6% of the time the car is running, or 3.9 events/100 miles • Neither wiper use nor speed selected is readily predicted by precipitation • Attempts to relate wiper use with rain rates was very poor using hourly historic data

19. Naturalistic Use of High-Beam Headlamps

20. High-Beam Usage • Drivers vastly under use high-beam headlamps • Even in conditions when glare is not an issue • Data from 87 drivers • ~ 100k miles, of which ~ 21k miles were driven at night • Night defined by a solar zenith angle ≥ 96°

21. Headlamp Usage

22. Results • Best case scenario for using high beams: Rural roads, no opposing traffic, not following a vehicle

23. Summary • Collapsed across road types, high beams are used 3.1% of the mileage driven at night • Even under ideal conditions, high-beam usage averages ~ 25% • Drivers continue to under use high-beam headlamps • Automatic high/low switching could improve this situation

24. Naturalistic ABS Events

25. The Data Set • 96 drivers from Michigan, USA • Urban, suburban and rural residents • 137K miles, 13,600 trips, ~ 10 driving yrs • 851 ABS events • ~ 1 every 161 miles • ~ 1 every 16 trips • ~ 85 per year

26. ABS and Precipitation? 81% of ABS events are without active precipitation

27. ABS and Temperature 70% of ABS events occur above freezing

28. ABS and Road Class ABS events over rep. on dirt roads

29. ABS and Speed 90% of ABS events are initiated under 40 mph 50% of ABS events are initiated under 25 mph

30. Video Samples

31. What This Means for VII Weather • There is a wealth of naturalistic data to be mined relative to baseline driving behavior • Data can aid in assessing the probability of a weather related event • Data can aid in determining timing required before issuing an alert • Data can be used for assessing the relative value of providing VII in certain locations

32. Questions? jimsayer@umich.edu