Contributory Causes Related to Large Truck Crashes

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http://matc.unl.edu/research/research_projects.php?researchID=6

In order to improve the safety of the overall surface transportation system each of the critical areas needs to be addressed separately with more focused attention. Statistics clearly show that large truck crashes contribute significantly to an increased percentage of high severity crashes. It is therefore important for the highway safety community to identify the characteristics and contributory causes related to large truck involved crashes. During the first phase of this study fatal crash data from Fatality Analysis Reporting System database are studied to achieve that objective. In this second phase, it is proposed to analyze truck crashes of all severity levels with the intention of identifying the factors contributing to increased severities of truck crashes, which could not be achieved by analyzing fatal crashes alone.

Dr. Sunanda Dissanayake, Professor at Kansas State University, presented this research during the 2012 MATC Spring Webinar Series.

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Contributory Causes Related to Large Truck Crashes

  1. 1. Characteristics and Contributory Causes Related to Large Truck Crashes Sunanda Dissanayake, Ph.D., P.E. Associate Professor Kansas State University
  2. 2. Disclaimer• The Contents of this report reflect the view of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation University Transportation Center Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof.
  3. 3. Outline• Introduction• Objectives• Methodology• Data• Results• Conclusions
  4. 4. Introduction• One ninth of all traffic fatalities in US involved a large truck.• However, large trucks accounted for only 3% of registered vehicles and 7% of vehicle miles traveled.• Truck crashes tend to be more severe than other crashes.• Important to identify characteristics and what leads to increased severities.
  5. 5. Trucks?For the purpose of this study:Large trucks: Trucks with gross weight of10,000 pounds or more.
  6. 6. Objectives• To identify characteristics and contributory causes related to fatal truck crashes and all truck crashes.• To compare circumstances more common in fatal truck crashes as compared to fatal non- truck crashes.• To identify the factors that are contributing to/related with increased severity of truck crashes.
  7. 7. Methodology and Data• Objectives achieved by analyzing crash data related to large trucks.•Two phases of the study: –One focused on fatal truck crashes from the whole country –Second focused on all truck crashes from Kansas•Statistical Modeling techniques used.
  8. 8. Analysis of Fatal TruckCrashes• FARS database.• Includes all police-reported fatal crash data from the whole country.• Very detailed data with many coded variables.• Fatality occurred within 30 days of the incident.
  9. 9. Question………• How many fatal truck crashes in the United States each Year?
  10. 10. Analysis of Fatal Truck CrashesVehicle Occupants killed in Large Truck Crashes 6000 5000 4000 No. of fatalities No. of Fatalities in trucks No. of fatalities 3000 in Non-trucks Total 2000 1000 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Year Particularly devastating to the occupants of the other vehicle.
  11. 11. Source: DRIVECAM Website• Sad fact: Majority of the damage is to the occupants of the other vehicle.
  12. 12. Analysis of Fatal Truck Crashes Based on manner of collision – fewer single vehicle truck crashes
  13. 13. Analysis of Fatal Truck Crashes –Bayesian method – crash related Ex. Construction/work area  LR = 2.77 Fatal truck crashes are 2.77 more likely in construction/work areas
  14. 14. Analysis of Fatal Truck Crashes –Bayesian method –vehicle related Ex. Defective Brake Systems  LR = 8.22 Fatal truck crashes are 8.22 times more likely to have defective brake systems
  15. 15. Analysis of Fatal Truck Crashes –Bayesian method-driver related Ex. Following Improperly  LR = 3.7 Fatal truck crashes are 3.7 more likely to have a driver that was following improperly.
  16. 16. Phase II – All Crashes• Data from Kansas• KDOT’s Kansas Accident Reporting System database• Data related to truck crashes occurred between 2004 and 2008 considered.• 18,919 observations.• Characteristics and Contributory causes identified; severity modeling carried out.
  17. 17. BINARY LOGISTIC REGRESSION• Variables were redefined in binary form; 1 or 0.• Variables checked for multicollinearity.• Binary Logistic Regression model developed• Dependent Variable crash severity was redefined as: = 1, if the occupants involved in the truck crashsustained injury of any severity level; = 0, otherwise• Sign of the variable important, Odds Ratio used toquantify the level of importance
  18. 18. RESULTS AND DISCUSSIONCHARACTERISTICS OF TRUCK CRASHES Road Surface Type Dirt (1.1%) Brick Gravel (0.5%) (3.1%) Concrete (30.6%) Blacktop (64.4%) More truck crashes on Blacktop –makes sense !
  19. 19. Road Surface Condition Road Surface Character Ice, Snow Mud, Dirt Curved and packed or Sand Level Curved on (6.2%) (0.5%) (5.5%) Grade (5.3%) Snow and Slush Straight at (3.5%) hillcrest (1.7%) Wet (10.3%) Straight on Grade (19.3%) Straight and level Dry (67.3%) (79.2%) More Truck Crashes More Truck Crashes under Dry road on straight and level surface condition
  20. 20. Lane Class Eight Lane Two Lane Divided Divided (0.2%) (2.3%)Four LaneUndivided (9.3%) Two Lane Undivided (38.8%) Six Lane Divided (14.1%) Four Lane Divided (35.3%) 2-lane undivided very critical
  21. 21. Light Condition 80.0% 76.0% 70.0%Percentage of Truck Crashes 60.0% 50.0% 40.0% 30.0% 20.0% 12.5% 7.6% 10.0% 2.3% 1.5% 0.0% Daylight Dawn Dusk Dark-Street Lights Dark-No Street on Lights Light ConditionMajority under daylight conditions –exposure ?
  22. 22. Weather Condition Time of Day Strong Freezing Snow and 25.0% 22.5% 21.0% Percentage of Crashes Winds Rain Winds 18.8% (1.7%) (1.0%) (1.4%) 20.0% 15.3% Snow 15.0% (4.4%) 8.8% 10.0% 5.2% 5.0% 3.6% 4.8%Rain, Mistor Drizzle 0.0% (6.9%) No Adverse Condition (81.8%) Time of the Day 82% -Under no 78% - 6 am to 6 pm adverse weather
  23. 23. Age of the Truck Driver Gender of the Driver 60.0% 90.0% 78.7% Percentage of Total Truck Crashes 48.9% 80.0% 50.0% 70.0%Percentage of Crashes 40.0% 60.0% 31.5% 50.0% 30.0% 40.0% 20.0% 30.0% 20.0% 16.9% 9.3% 10.0% 5.7% 4.3% 10.0% 4.4% 0.1% 0.0% 0.0% 16-20 21-40 41-60 61-80 >80 Others Male Female Unknown Age of the Truck Driver (Years) Gender of the Truck Driver Majority – middle aged Majority - male
  24. 24. Truck Maneuver 60.0% 54.6% 50.0%Percentage of Crashes 40.0% 30.0% 19.1% 20.0% 10.0% 8.0% 7.7% 5.3% 5.3% 0.0% Straight-following Right turn Left turn Backing Changing lanes Others road Truck Maneuver Distribution of Truck Crashes based on Truck Maneuver
  25. 25. Manner of Collision 40.0% 35.2% 35.0% 30.0%Percentage of Crashes 25.0% 19.7% 20.0% 16.5% 15.3% 15.0% 10.0% 4.1% 3.3% 5.0% 1.4% 1.8% 0.0% Single Angle-Side Rear End Sideswipe Backed into Sideswipe Head On Unknown Vehicle Impact (Same (Opposite Direction) Direction) Manner of Collision More single vehicle crashes than in fatal truck crashes
  26. 26. Vehicle Body Type Accident Class Other non- Sport Utility Others collision Other Collision with Collisions Vehicle (1.6%) parked motor (3.6%) (12.5%) (1.4%) vehicle (3.8%) Collision with Pickup animal Truck (7.1%)(20.4%) Overturned (7.6%) Collision with other motor Collision with vehicle Van Automobile fixed object (63.2%) (8.6%) (56.0%) (13.3%) Distribution of Two- Distribution of TruckVehicle Truck Crashes Crashes based on Based on Body Type Accident Class
  27. 27. Road Function Class 30.0% 25.1% 25.0%Percentage of Crashes 21.9% 20.0% 15.8% 14.9% 15.0% 13.1% 10.0% 5.8% 5.0% 2.7% 0.6% 0.0% Road Function Class More in rural areas
  28. 28. Accident Location 60.0% 49.4%Percentage of Crashes 50.0% 40.0% 30.0% 20.0% 16.6% 12.4% 8.0% 6.9% 5.6% 10.0% 0.9% 0.0% Accident Location 50% - at non- intersection locations
  29. 29. Average Annual Daily Traffic 70.00% 63.74% 60.00% Percentage of Crashes 50.00% 40.00% 30.00% 20.00% 14.29% 10.00% 6.98% 4.95% 2.84% 3.33% 2.97% 0.90% 0.00% Average Annual Daily Traffic (AADT) Distribution of Truck Crashes based on Average Annual Daily Traffic
  30. 30. Contributory Causes of TruckCrashesQuestion:• What is the most common type of contributory cause? Driver related? Roadway? Environment related? Vehicle defects? Other?
  31. 31. Contributory Causes of TruckCrashesTruck Crashes Based on Type of Contributory Cause Type of % of Crashes Number of Contributory Involving Truck Crashes Cause Contributory Cause Driver Related 13,260 73% Environment 2,360 Related 13% Road Related 1,409 7.8% Vehicle Related 1,112 6.1% Pedestrian 30 Related 1.7%
  32. 32. Truck Crashes Based on DriverContributory Cause Number of Percentage of Crashes Involving Driver Related Contributory Cause Crashes Driver Related Cause Failed to give time and 6,458 35.50% attention Too fast for conditions 1,962 10.80% Failed to yield right of way 1,644 9.00% Improper lane change 1,196 6.60% Followed too closely 1,178 6.50% Made improper turn 1,016 5.60% Disregard traffic signs, signal 770 4.20% Avoidance or evasive action 742 4.10% Improper backing 726 4.00% Improper passing 487 2.70% Wrong side or wrong way 337 1.90% Distraction in or on the truck 327 1.80% Fell asleep 307 1.70% Under influence of alcohol 250 1.40% Reckless/careless driving 197 1.10% Ill or medical condition 105 0.60% Exceeded posted speed limit 101 0.60% Did not comply with license restriction 91 0.50% Improper or no signal 77 0.40% Impeding traffic, too slow 76 0.40% Under influence of drugs 66 0.40% Aggressive, antagonistic driving 46 0.30% Improper parking 46 0.30%
  33. 33. Truck Crashes Based onVehicle Contributory Causes Number of Percentage of Crashes Vehicle Related Contributory Cause Crashes Involving Vehicle Related Cause Falling Cargo 389 34.0% Defective Tires 220 19.2% Defective Brake System 175 15.3% Defective Wheel(s) 128 11.2% Trailer-coupling related 85 7.4% Other lights 48 4.2% Unattended or driverless (not in motion) 41 3.6% Unattended or driverless (in motion) 22 1.9% Defective Windows-windshield 18 1.6% Defective Exhaust System 12 1.0% Headlights 5 0.4%
  34. 34. Truck Crashes Based onEnvironment-Related ContributoryCauses Number of Environment Related Contributory Cause Percentage of Crashes Crashes Involving Environment Related Cause Animal Related 966 37.8% Rain, mist or drizzle 388 15.2% Falling snow 352 13.8% Strong winds 336 13.2% Sleet, hail, freezing rain 185 7.2% Vision obstruction - glare 93 3.6% Vision obstruction - cultural 77 3.0% Fog, smoke or smog 75 2.9% Blowing sand, soil, dirt 39 1.5% Vision obstruction - vegetation 26 1.0% Reduced visibility due to cloud cover 17 0.7%
  35. 35. Truck Crashes Based on Road-related Contributory Causes Photo credit: Iowa State University
  36. 36. Truck Crashes Based on Road-related Contributory Cause Number of Percentage of Crashes Road Related Contributory Cause Crashes Involving Road Related Cause Icy or Slushy 686 45.7% Wet 281 18.7% Snow-packed 239 15.9% Debris or Obstruction 113 7.5% Road Under Construction/Maintenance 79 5.3% Shoulders 69 4.6% Ruts, Holes, Bumps 20 1.3% Inoperative Traffic Control Device 14 0.9%
  37. 37. Binary Logistic RegressionExample of Variables Considered in the Model Variable Mean Standard Deviation Description =1 if the truck driver is under the influence of alcohol,ALCOHOL 0.01586 0.1249 =0 otherwiseBRAKES 0.03547 0.18496 =1 if the crash occurred due to brakes, exhaust, headlights, windows-windshield, cargo or tires, =0 otherwiseCARELESS 0.01813 0.13342 =1 if the truck driver is distracted or is too aggressive, =0 otherwiseCC_DR 0.69898 0.45871 =1 if the crash occurred has driver related contributory cause,CC_ENV 0.12464 0.33032 =1 if the crash occurred has environment related contributory cause,CC_RD 0.07448 0.26255 =1 if the crash occurred has road related contributory cause,CC_VEH 0.0583 0.23432 =1 if the crash occurred has truck related contributory cause,CLASS 0.63169 0.48236 =1 if the crash involves collision with a motor vehicle in transport, =0 otherwiseCOLLISION 0.17929 0.38361 =1 if the crash involved a head-on collision, =0 otherwiseCONSTR_MAINT 0.05872 0.23511 =1 if crash occurred in construction, maintenance or utility zone,CONTROL 0.81077 0.3917 =1 if the crash site has a traffic control device, =0 otherwiseDAMAGE 0.86432 0.34246 =1 if the truck had a damage, =0 otherwiseDAY 0.87774 0.32759 =1 if crash occurred during weekdays, =0 otherwiseDRUGS_ALCOHOL 0.01617 0.12615 =1 if the truck driver is influenced with drugs or alcohol, =0 otherwiseTRAPPED 0.0195 0.13829 =1 if truck driver was trapped, =0 otherwiseEVASIVE 0.0481 0.21398 =1 if the truck driver took evasive action or is too slow, =0 otherwiseGENDR 0.78699 0.40945 =1 if the driver of the truck was a male, =0 otherwiseIMP_MAN 0.1313 0.33773 =1 if the truck driver made improper maneuver, =0 otherwiseINOPERATIVE 0.00476 0.06881 =1 if the crash occurred at construction site or has inoperative traffic control device, =0 otherwiseLIGHT 0.75961 0.42733 =1 if the light condition is daylight, =0 otherwise
  38. 38. Parameter Estimates and Odds Ratio of Large truckCrashes in the Model 95% Wald Estimat Standard Odds Confidence Variable e Error Pr > Chi-Sq Ratio Limits For Odds Ratio Intercept* -1.522 0.163 <0.0001 ALCOHOL 2.04,3.4 0.979 0.135 <0.0001 2.66 * 7 CARELESS* 0.334 0.126 0.0078 1.40 1.09, 1.79 CC_DR* 0.6 0.054 <0.0001 1.82 1.64, 2.02 CC_RD* -0.332 0.084 <0.0001 0.72 0.61, 0.85 CC_VEH -0.09 0.093 0.3329 0.91 0.76, 1.10 CLASS 0.102 0.052 0.0509 1.11 1.00, 1.23 COLLISION* 0.471 0.052 <0.0001 1.60 1.45, 1.77 CONSTR_MAINT* -0.267 0.083 0.0013 0.77 0.65, 0.90 Examples CONTROL* DAMAGE* DAY 0.308 1.116 -0.003 0.057 0.083 0.058 <0.0001 <0.0001 0.9661 1.36 3.05 1.00 1.22, 1.52 2.60, 3.59 0.89, 1.12 EVASIVE* 0.427 0.079 <0.0001 1.53 1.31, 1.79 GENDR* -0.129 0.049 0.0079 0.88 0.80, 0.97 IMP_MAN* -0.453 0.068 <0.0001 0.64 0.56, 0.73 INOPERATIVE -0.247 0.328 0.4508 0.78 0.41, 1.48 LIGHT 0.06 0.049 0.2209 1.06 0.96,1.17 MANEUVER* 0.321 0.041 <0.0001 1.38 1.27, 1.49 MIDDLE_AGED* 0.102 0.043 0.0166 1.11 1.02, 1.20 OLD 0.092 0.14 0.5141 1.10 0.83, 1.44 ONAT_TC* -0.521 0.054 <0.0001 0.60 0.53, 0.66 1.07, RAIN* 0.33 0.132 0.0124 1.39 1.80 RUTS -0.148 0.224 0.5091 0.86 0.56, 1.34 S_CHAR* -0.114 0.041 0.0051 0.89 0.82, 0.97 S_COND* 0.256 0.056 <0.0001 1.29 1.16, 1.44 S_TYPE* 0.132 0.04 0.0011 1.14 1.05, 1.24 SAFETY_EQUIPT* -1.378 0.075 <0.0001 0.25 0.22, 0.29 SMOG_SAND 0.355 0.218 0.1037 1.43 0.93, 2.19 SNOW 0.151 0.099 0.1261 1.16 0.96, 1.41 SPEED* 0.442 0.054 <0.0001 1.56 1.40, 1.73 SPEED_LIMIT_1* -0.801 0.051 <0.0001 0.45 0.41, 0.50 SPEED_LIMIT_2* -0.39 0.077 <0.0001 0.68 0.58, 0.79 SPEED_LIMIT_3*0.05 level *- Significant at 0.116 0.052 0.0252 1.12 1.01, 1.24 TRAPPED* 4.417 0.344 <0.0001 82.81 42.21, 162.44 UNATTND 0.483 0.329 0.142 1.62 0.85, 3.09 VSN_OBSTRUCT* -1.326 0.132 <0.0001 0.27 0.21, 0.34 WRONG 0.014 0.058 0.8034 1.01 0.91, 1.14
  39. 39. Findings and Conclusions• More than 80% of fatalities in large truck crashes are occupants of the “other” vehicles.• Relatively smaller % of single vehicle fatal truck crashes, as compared to SV fatal non-truck crashes.• Many more…….• Majority of all truck crashes in KS occurred on blacktops, in daylight conditions, under no adverse weather conditions.• Contributory cause for most truck crashes- driver related. 73%• Most common: Failing to give time and attention, driving too fast for conditions.
  40. 40. Findings and Conclusions• Animal related causes and rain/mist/drizzle more common among environment related causes.• Falling cargo, defective tires more common among vehicle related causes.• Binary logistic regression provided a good means to identify the factors leading to increased severity of truck crashes.
  41. 41. • Odds Ratio shows the level of importance.• Highest odds ratio of 83 - when driver is trapped – most likely to contribute to increased severity.• 2.7 times higher odds when driven by person under the influence of alcohol.• Many more…• More focused and targeted countermeasure ideas/programs developed based on the critical factors.
  42. 42. CREDITS MATCNishitha Bezwada and Siddhartha Kotikalapudi Mr. Steven Buckley @ KDOT KDOT and NHTSA Associate Director at KSU – Dr. Hossain Slide design © 2009, Mid-America Transportation Center. All rights reserved.
  43. 43. You can copy any of these graphics and paste them on other slides.

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