Driver Distraction Recent Results: 100 Car Re-Analysis / Teen / Commercial Truck Studies

Transcription

1 Driver Distraction Recent Results: 100 Car Re-Analysis / Teen / Commercial Truck Studies Thomas A. Dingus Ph.D., CHFP Director, Virginia Tech Transportation Institute Newport News Shipbuilding Professor of Engineering

2 Introduction Driver distraction, defined here as engaging in a secondary task or activity that is not central to the primary task of driving, has been shown to be a contributing factor for many crashes. Secondary tasks and other activities in which drivers choose to engage while driving is also known to be highly varied, including very complex activities (e.g., text messaging on a cellular device) to very simple activities (e.g., selecting a radio preset).

3 A New Method of Study: Large-Scale Naturalistic Driving 20 to 3500 drivers No instructions 6 mos. to 3 yrs. 100,000 s of hours 100 s MVMT

4 Naturalistic Data Collection Approach Highly capable instrumentation (well beyond EDRs) Multiple channels of digital, compressed video Multiple radar sensors front, rear and/or side Machine vision-based lane tracker Many other sensors: GPS, glare, RF, acceleration, yaw rate, controls, etc. Cell phone, wireless internet, or hardwire download Ties into vehicle networks to obtain other information

5 In these studies, drivers are not given any instructions and often there are also no specific evaluations. Studies capture a large number of crash events, there has yet to be a single study large enough to capture a statistically significant number of crashes. To overcome this limitation several studies have utilized near crashes in combination with crashes. Near crashes, in this case, are defined as having all of the elements of a crash with the exception that the driver implements a successful evasive maneuver.

6 Example: What are the contributing factors? Video removed to permit distribution

7 Analysis Approach Data analyses were conducted utilizing several naturalistic driving databases. These data were specifically analyzed for the purpose of assessing secondary task distraction. From these data, an event databases of crashes and near crashes was created with crashes, minor collisions and near crashes. These data were also used to develop a nonevent or baseline database to assess exposure. Used both a case-control and case-crossover baseline databases, which did not produce significant differences in risk calculations.

8 Results: Driver inattention is a key contributing factor in crashes for both truck and light vehicles. The largest single contributing factor is looking away from the roadway just prior to an unexpected event or condition. This accounts for somewhere between 70% and 90% of unsafe events. Engaging in activities that are unrelated to driving (i.e., secondary tasks ) and external distractions account for most of the inattentionrelated risk. High Risk: Looking away many times and/or long periods Includes: Cell phone dialing, text messaging, Ipod/MP3 manipulation, and internet interaction. Much less risk: Eating/drinking, talking to passengers, simple radio functions, and even talking on a cell phone. Teens are four times more likely to be involved in a near crash or crash while performing a secondary task than their adult counterparts.

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11 Tertiary Task Odds Ratios for Tractor Trailers/Tankers Only in the Current Study Odds Ratios in Olson et al. (2009) Any Cell Phone Use Dialing Cell Phone 5.44* 5.93* Talk/Listen Hands-Free Cell Phone 0.58* 0.44* Talk/Listen Hand-Held Cell Phone Reaching for Bluetooth Device 4.43* 6.72* Reaching for Cell Phone 7.60* Included in dial cell phone Text/ /Web * Food/Drink 1.53* 1.01 * Asterisk indicates a significant odds ratio. These ratios are also shown in bold. + odds ratio calculation was only performed across all vehicle types

12 Teen Distraction Example Video removed to permit distribution

13 These results have significant implications for the design of driver-vehicle interfaces Includes the need for future integration of nomadic devices into the driver-vehicle interface in a manner which will minimize crash and near crash risk. Auditory-voice secondary task interfaces will generally be less risky than visuo-manual secondary tasks. The tasks with the highest crash risk are those that require multiple glances away from the road.

14 Hand-held is substantially riskier than true hands-free. Operating a complex hand-held device is significantly more risky than a hands-free counterpart. Dialing, texting, reading and answering a hand-held phone were both higher risk tasks, even in comparison to the often longer task of talking on a hand held phone. Greatest proportion of risk does not come from the conversation or act of holding a phone to one s ear, it comes from the complex task components of dialing, answering, texting, etc. that require multiple glances away from the roadway.

15 An interruptible task is risky if it involves eyes-off-road. Recent research indicates that if an in-vehicle secondary task is interruptible, the driver can manage the task while driving without increasing crash risk. Results show no indication of a constant, or nearly constant, crash/near crash risk, for a broad range of in-vehicle tasks given that multiple glances away from the roadway are required. Crash/near crash most often involves an unexpected external event occurring when the driver is not looking in the direction of the event.

16 Driver Attention Monitoring holds great promise as a countermeasure Particularly true for selected groups like commercial drivers or teens. Allows direct feedback to drivers. Allows enforcement of administrative rules.

17 The importance of countermeasures: Identification and elimination of extreme, high risk behavior Video removed to permit distribution

18 VTTI Driver Monitor used for drowsiness detection (post hoc, compressed video sample) Video removed to permit distribution Mask_Perclose

19 Thanks!