Exploring the Determinants of Vulnerable Road Users’ Crash Severity in State Roads
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Transcript of Exploring the Determinants of Vulnerable Road Users’ Crash Severity in State Roads
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DETERMINANTS OF VULNERABLE ROAD USERS’ CRASH SEVERITY IN STATE ROADS
Álvaro CaviedesMiguel Figliozzi
January 19th
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TABLEOF CONTENTS 1. BACKGROUND
2. PROBLEM STATEMENT3. DATA AND METHODS4. RESULTS5. CONCLUSIONS
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BACKGROUND
1. Department of Transportation’s (DOT) interest in increasing non-motorized transportation
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BACKGROUND
1. Focus on driver safety2. Crash frequency vs crash severity
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BACKGROUND
1. Urban environments2. Risk factors:• Location,• Environmental, • Crash, • Road,
• Demographic, and • Traffic characteristics.
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PROBLEM STATEMENTExplore risk factors of crash severity for pedestrians and bicyclists in the Oregon Highway Network System
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DATA AND METHODS
1. Oregon statewide crash database (2007-2014)2. ODOT’s TransGIS database3. Neighborhood concepts (Currans et al. 2015)
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INJURY SEVERITYLEVELS A (INCAPACITATED)- ALMOST KILLED
K (FATAL) - KILLED
B (VISIBLE INJURY) – BRUISE
C – COMPLAIN OF PAIN
0 – ONLY PROPERTY DAMAGE
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CRASHES IN THE OREGON HIGHWAY STATE NETWORK
VARIABLE
PEDESTRIANCRASHESIN OREGON
ONLY STATE HIGHWAYS
BICYCLISTCRASHESIN OREGON
ONLY STATE HIGHWAYS
TOTAL CRASHES
6,162 1,840(30%)
7,147 1,584(22%)
CRASHES AT INTERSECTIONS
3,629 1,088 4,702 1,045
CRASHES AT SEGMENTS
1,822 561 864 169
OTHERS 711 191 1481 370
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DESCRIPTIVE ANALYSIS
1. Location characteristics2. Environmental conditions3. Crash characteristics4. Traffic characteristics5. Road characteristics
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LOCA
TION
CHAR
ACTE
RISTIC
SDE
SCRI
PTIV
E AN
ALYS
ISLOCATION LAND USE
PEDESTRIANBICYCLIST
0% 5%
10% 15% 20% 25%
Intersection Segment
K A
0% 5%
10% 15% 20%
Intersection Segment
K A
0% 5%
10% 15% 20% 25%
Urban Suburban Rural
K A
0% 5%
10% 15% 20%
Urban Suburban Rural
K A
(n=496) (n=1039)
(n=133) (n=867)
(n=602) (n=724) (n=209)
(n=372) (n=487) (n=141)
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ENVIR
ONME
NTAL
COND
ITION
SDE
SCRI
PTIV
E AN
ALYS
IS LIGHT CONDITIONS WEATHER
PEDESTRIANBICYCLIST
0%
10%
20%
30%
Daylight Dark + streetlight
Dark Twilight
K A
0%
10%
20%
30%
Daylight Dark + streetlight
Dark Twilight
K A
0%
10%
20%
30%
Clear day Bad conditions
K A
0%
10%
20%
30%
Clear day Bad conditions
K A
(n=775) (n=410) (n=228) (n=122)
(n=786) (n=113) (n=42) (n=59)
(n=856) (n=679)
(n=749) (n=251)
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CRAS
H CH
ARAC
TERIS
TICS
DESC
RIPT
IVE
ANAL
YSIS ALCOHOL INTOXICATION USER LOCATION
PEDESTRIANBICYCLIST
0%
10%
20%
30%
No alcohol Yes alcohol
K A
0%
10%
20%
30%
No alcohol Yes alcohol
K A
0%
10%
20%
30%
Crosswalk Roadway Midblock
K A
0%
10%
20%
30%
Crosswalk Roadway Bike lane
K A
(n=1292) (n=243)
(n=961) (n=39)
(n=1042) (n=452) (n=41)
(n=423) (n=541) (n=36)
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CRAS
H CH
ARAC
TERIS
TICS
DESC
RIPT
IVE
ANAL
YSIS VEHICLE TYPE VEHICLE MOVEMENT
PEDESTRIANBICYCLIST
0%
10%
20%
30%
40%
Passenger car Heavy vehicle
K A
0% 10% 20% 30% 40%
Passenger car Heavy vehicle
K A
0% 10% 20% 30% 40%
Straight Turning
K A
0% 10% 20% 30% 40%
Straight Turning
K A
(n=1496) (n=39)
(n=989) (n=11)
(n=893) (n=642)
(n=393) (n=607)
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TRAF
FIC CO
NDITI
ONS
DESC
RIPT
IVE
ANAL
YSIS
AADT (ONLY TRUCKS)
PEDESTRIAN BICYCLIST
0% 5%
10% 15% 20% 25% 30%
<1.5k 1.5k-5k 5k-7.5k >7.5k
K A
0% 5%
10% 15% 20% 25% 30%
<1.5k 1.5k-5k 5k-7.5k >7.5k
K A(n=1107) (n=418) (n=9) (n=1) (n=716) (n=271) (n=8) (n=5)
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ROAD
CHAR
ACTE
RISTIC
SDE
SCRI
PTIV
E AN
ALYS
ISROAD SURFACE POSTED SPEED LIMIT
PEDESTRIANBICYCLIST
0% 20% 40% 60% 80%
100%
<20 20-35 35-50 50-65 >65
K A
0% 20% 40% 60% 80%
100%
<20 20-35 35-50 50-65 >65
K A
0% 5%
10% 15% 20%
Dry Wet
K A
0% 5%
10% 15% 20%
Dry Wet
K A
(n=55) (n=1032) (n=316) (n=131) (n=1)
(n=26) (n=616) (n=239) (n=114) (n=5)
(n=1075) (n=460)
(n=862) (n=138)
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ROAD CHARACTERISTICS –EXPOSURE ANALYSISDESCRIPTIVE ANALYSIS
- Crash risk under various road characteristics- Likelihood of crash involvement - Depends on exposure- Risk ratio ~ concentration of crashes (number of lanes, road width, and road
classification)- Exposure controlled by estimating the proportion of VMT
Example: 𝑅𝑖𝑠𝑘𝑟𝑎𝑡𝑖𝑜 = +,-.,/012,34.-156,57/-31859706:;1/,+,-.,/012,34<=>7/-31859706:;1/,
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EXPO
SURE
ANAL
YSIS
-ROA
D CH
ARAC
.DE
SCRI
PTIV
E AN
ALYS
IS
0
1
2
3
4
5
6
7
8
9
10
1 2 3 4
0
1
2
3
4
5
6
7
8
9
10
1 2 3 4
0
1
2
3
4
5
6
7
8
9
10
Local Collector Arterial
0
1
2
3
4
5
6
7
8
9
10
Local Collector Arterial
0
1
2
3
4
5
6
7
8
9
10
10 - 20 20 - 30 30 - 40 40 - 50
0
1
2
3
4
5
6
7
8
9
10
10 - 20 20 - 30 30 - 40 40 - 50
NUMBER OF LANES ROAD WIDTH ROAD CLASSIFICATIONRIS
K RAT
IORIS
K RAT
IO
RISK R
ATIO
RISK R
ATIO
RISK R
ATIO
RISK R
ATIO
K A B C O
1 2 3 4
1 2 3 4
10-20 20-30 30-40 40-50
10-20 20-30 30-40 40-50
Local Collector Arterial
Local Collector Arterial
PEDESTRIANBICYCLIST
10 10 10
101010
00 0
000
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RESULTS
1. METHODOLOGY2. INDIVIDUAL MODEL3. POOLED MODELS4. SENSITIVITY ANALYSIS
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POOLEDMODELS
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POOLEDMODELS
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POOLEDMODELS
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POOLEDMODELS
Other significant variables:- Land use- Segment vs Inters.- Time of the day
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POOLEDMODELSOnly road and traffic characteristics
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POOLEDMODELSOnly road and traffic characteristics
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POOLEDMODELSOnly road and traffic characteristics
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SENSITIVITY ANALYSISPEDESTRIAN MODEL
CRASH SEVERITY ~ Light conditions +Road classification +Posted speed limit +Pedestrian location+AADT(Only truck)
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SENSITIVITY ANALYSISPEDESTRIAN MODEL
CRASH SEVERITY ~ BASELINE SCENARIO
Prob. (K+A)=7.4%
Light conditions (DAYLIGHT) +Road classification (LOCAL STREET) +Posted speed limit (<50 MPH) +Pedestrian location (CROSSWALK) +AADT(Only truck) (<700)
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SENSITIVITY ANALYSISPEDESTRIAN MODEL
CRASH SEVERITY ~ Light conditions (DARKNESS) +Road classification (LOCAL STREET) +Posted speed limit (<50 MPH) +Pedestrian location (CROSSWALK) +AADT(Only truck) (<700)
Prob. (K+A)=7.4%Prob. (K+A)=16.1% Change = +8.6%
BAD LIGHTING SCENARIO VS BASELINE SCENARIO
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% CH
ANGE
PEDESTRIAN MODELSENSITIVITY ANALYSIS
59%
9% 7% 7% 4% 3% 0%
20% 40% 60% 80%
100%
K+A
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SENSITIVITY ANALYSISBICYCLIST MODEL
CRASH SEVERITY ~ Bicyclist location+AADT
% CH
ANGE
13%
8%
3%
0%
5%
10%
15%
20%
Worst case scenario Location: Segment AADT: >10.000
K+A
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CONCLUSIONS
1. TAKEAWAYS- Age- Alcohol intoxication- Vehicle size- Vehicle movement
- Posted speed limit- Light conditions- Road classification- Road surface- Location of the user- Land use and AADT
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CONCLUSIONS
2. MITIGATION- Educational campaigns- Training courses- More strict enforcement- Protection vulnerable users
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CONCLUSIONS
3. LIMITATIONS and FUTURE RESEARCH- Underreporting- Speed- Bike facilities- Special pedestrian signals
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QUESTIONS?ACKNOWLEDMENTS
DISSERTATION COMMITTEE:- Miguel Figliozzi- Chris Monsere- Avinash Unnikrishnan
TTP LABTransportation engineering and planningMaster students