s f l d i i tt tisafer glances, driver inattention, and...
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S f l d i i tt tiSafer glances, driver inattention, and crash risk in lead-vehicle
followingTrent Victor,
Jonas Bärgman, Christian-Nils Boda, Marco Dozza, Johan Engström, Carol Flannagan, John D. Lee, Gustav Markkula
SHRP2 Summer Symposium Final Report Presentation 10 July, 2014
Research Question
What is the relationship between driver inattention and crash risk in lead-vehicle pre-crash scenarios (rear-end crashes)?
Final Sample Size
• 46 crash events
• 211 near-crash events257
High degree ofmatching on: driver,
trip, no standstill, trafficflow, intersections,
speed, weather, day/night, etc
Controls in case-crossover approach.
• 257 matched baseline events
• 260 random baseline events Completely random, different drivers, trips
etc.
Controls in case-control approach.
Distracting activities 5s before Precipitating Event to 1s after
** *** *
Reduced risk from Talking/listening:• Not because of NC, nor commercial
drivers, nor poor baseline matching, nor drowsiness, nor gaze concentration.
• No slower reactions. • We propose the task & glance
displacement explanation
What are the most dangerous glances away from the road, and
what are safer glances?
Glances Only
Eyes off path more in 6s window at the Precipitating Event (replication)
>2s Klauer Present (2010) results
Matched BL (cond) 1.6 2.1Random BL (crude OR) 2.1 2.0
Eyes off Path before Crash/minTTC
Crash/Crash/minTTC
Precipitating Events= Lead Vehicle Brake Light Onset
Glance locations before Crash
Glance locations before Near Crashes (minTTC)
Glance locations in Matched Baselines
Glance locations in Random Baselines
Off-Path Glance Duration Distributions
= Proportion of eyes off path 3-1s before C/NC
= Mean single glance duration
−12 −8 −4 0Time from TTCmin at 0 seconds
Unc
erta
inty
and
eye
s of
f roa
d
= Mean level of uncertainty (Senders et al, 1967)22.2
Glance metrics are powerful predictors
• No substantial cumulative effect from segments before Off3to1. The EOP peak is what matters.
• A glance model based on a linear combination along with the interactions was most predictive of crashes and near crashes. It combined:
• Off3to1 (Proportion of eyes off path 3-1s before crash/minTTC, equivalent to the Percent Road Center metric)
• mean.off (mean single glance duration) • m.uncertainty (mean level of uncertainty)
What are the most dangerous glances away from the road, and what are safer
glances?
Adding lead-vehicle kinematics
+
How does the timing of lead-vehicle closing kinematics in relation to off-road
glances influence crash risk?
How drivers are tricked into rear-end crashesLead vehicle
brake light turnson. Don’t have an
effect. Cry wolfeffect.
Driver looks away from road whenno looming
Fast looming duringglance away
(fast invTTC changerate)
Eyes on
Date Created: [YYYY-MM-DD]
Issuer: [Name] [CDS-ID]; [Organisation]; [Name of document]; Security Class: [Proprietary]
17
Crash occurs
Eyes off
PE
The Mismatch Mechanism:
Eyes off LoomingCategory 1, Inopportune
glances(eyes off threat)
Category 2, Looking away in
an alreadycritical situation (eyes off threat)
Fastchange
Category 3, Looking away and back again before the situation has
turned critical(eyes on threat)
Slowchange
Short Glance
LongGlance
Category 1. Inopportune glance
Eyes on
Figure 9.8 Example of a Categry 1 crash (event ID 19147492)
Eyes off
Category 2. Looking away in an already critical situation
Figure 9.9 Example of a Categor 2 crash (event ID 19147617)
Category 3. Looking away and back again before the situation has turned critical (eyes on
threat)
Figure 9.10 Example of a Category 3 crash (event ID 19147493)
What are the most dangerous glances away from the road, and what are safer glances? How does the timing of lead vehicle closing kinematics in relation to off-road glances influence crash risk?
• Probability for mismatch depends on the joint probability distributions of glance durations and situation kinematics.
• Dangerous glances are those during which the driver gets exposed to the risk of a rapidly changing situationg g
• An off-road glance is safe when the safety margins adopted are sufficient to protect if the situation changes rapidly during the glance.
• A combination of 3 glance metrics strongly predicted CNC risk.• No substantial cumulative effect from time segments before the EOP peak• The majority of crashes were associated with glances shorter than 2s
Countermeasures?Countermeasures?
• Eliminating glances above a limit of 2 seconds will not eliminate the problem. Majority of crashes were associated with short glances.
• Efforts should focus on minimizing eyes off path glances to portable electronic devices, as they are clearly more assiated with risk than vehicle-integrated systems.
Human-Machine Interaction design, distraction guidelines, and other regulatory agency
countermeasures.
• Results support the potential for non-visual interfaces, as Talking/listening on a cell phone was reduced risk.
• See distraction as a joint probability problem
• Active Safety systems provide the safety margins needed to protect the driver if the situation changes rapidly during an off-path glance.
– Emergency braking (AEB), Forward Collision Warning (FCW), Adaptive Cruise Control (ACC), V2V
Vehicle design and driving support
Glance Length
Freq
uenc
y
Approximately:
V2V– More time headway, active braking (emergency
or continuously), and warnings
• Supports the need for inattention sensing (e.g. eyetracker) and its use to warn the driver of inattention mismatches, as applied to active safety systems.
• Points to improved braking performance and road surfaces
0s 1s 2s 3s
• Public awareness of mismatch mechanism• Teach importance of adopting safe headways• Performance based insurance• Particular importance in 16-17yr olds and 76+
Education and Behavioral Change
• Reduce disruptive, erratic traffic flows. Create smooth flowing traffic, reduce the occurence of sudden, unexpected kinematic changes.
• Improved road surfaces decrease stopping distance• Self-explaining roads needed
Road and Infrastructure design
End
Risk at the Precipitating Event
(=LV Brake Light Onset)
Significant age differences in crashes
76+
16-17
Significantly more visual obstructions and rain in crashes
Rain
Looming (invTTC) at Start and End of Last Glance
Figure 9.4 Inverse time-to-collision (invTTC) at the onset and offset of the last glance
Short Headway at Start of Last Glance
Reaction depends on when the driver looks back and looming (invTTC)
0 8
1
1.2
1.4
1.6
river
reac
tion
(1/s
)
Crashes (n = 34)
0 8
1
1.2
1.4
1.6
river
reac
tion
(1/s
)
Near-crashes (n = 117)
-0.5 0 0.5 1 1.50
0.2
0.4
0.6
0.8
invTTC at end of last off-path glance (1/s)
invT
TC a
t dr
-0.5 0 0.5 1 1.50
0.2
0.4
0.6
0.8
invTTC at end of last off-path glance (1/s)
invT
TC a
t dr
Figure 9.13. InvTTC at end of last off-path glance (invTTCELG) versus invTTC at driver reaction (invTTCR), for crashes and near-crashes. In the right panel, four red rings show driver reactions in the four near-crashes where the driver talked or listened on cell phone.
Brake lights have a limited effect
• Seeing brake lights turn on does not have an effect on outcomes. Cry wolf effect.– Drivers who crashed were more likely to look ahead when brake
lights turned on. Example crashes:
What crash severity scale is best suited for analysis of risk?
• Use at least DeltaV for crashes, use minTTC for near crashes. • Model-estimated Injury Risk index (MIR) and Model-estimated Crash Risk index
(MCR) can be used in many new ways. More work needed.