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Do Alcohol and Other Drugs Significantly Affect Traffic Accident Types?. Trisha Muñoz, E.I.T Civil Engineering Department Cal Poly Pomona. Introduction. General safety background Description of the research method and crash data Illustration of the results Discussion and Conclusions.
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Do Alcohol and Other Drugs Significantly Affect Traffic Accident Types? Trisha Muñoz, E.I.TCivil Engineering DepartmentCal Poly Pomona
Introduction • General safety background • Description of the research method and crash data • Illustration of the results • Discussion and Conclusions
Road traffic crashes: Huge burden Pictures from: www.nhtsa.com and www.images.google.com
ROAD SAFETY STATUS 2005 } • Statistics (2005 – NHTSA Traffic Safety Facts) • Fatal 43,443 • Injury 2,699,000 • Property Damage Only 4,304,000 • Traffic Crash Victims Killed Injured • Occupants • Drivers 26,549 1,920,000 • Passengers 11,199 880,000 • Unknown 112 • Nonmotorists • Pedestrians 4,808 71,000 • Pedalcyclists 662 48,000 • Other/Unknown 113 7,000 7,046,443
NHTSA Facts of Impaired Driving • Impaired driving is often a symptom of a larger problem: alcohol misuse and abuse. • Alcohol-impaired motor vehicle crashes cost more than an estimated $37 billion annually. • In 2010, more than 10,000 people died in alcohol-impaired driving crashes - one every 51 minutes. Sources: http://www.nhtsa.gov/Impaired
Focus of the presentation • Numerous Past research studies : • driving performance is seriously impaired by alcohol and many other drugs. • However, very few research studies: • identifying the effects of alcohol and other drugs on traffic accident types • rear-end • head on • sideswipe • fixed object • others
Normal Linear Regression Requires Three strong assumptions • Normally distributed errors (i.e., residues) • Constant variance of errors • No relationships among the independent variables (i.e., regressor variables, or predictors)
In This Study • The dependent variable y has categorical nature (i.e., various accident types), which is not normally distributed • Therefore, the Normal Linear Regression is not appropriate herein. • Instead, we use Multinomial Logit Regression Model.
Arizona Crash Data • Road Sections from State Routes 77 and 83 in Tucson, AZ • Total mileage: 83 miles • Crash period: 6 years (Oct. 2003~ Sept. 2008) • Information: crash, driver, vehicle, environment, roadway, etc.
Crash Information • Date & time • Day of week • Crash location • Crash severity ( No Injury; Possible Injury; Non-incapacitating; Incapacitating; Fatal; unknown) • Collision type (rear-end, head-on, collision with fixed objects, etc.) • Hit-and-run (yes, no)
Driver(s) Information • Sex • Age • Conditions influencing drivers (use of illicit drugs; physical impairment, illness, etc.) • Violations (speed; made improper turn; ran stop sign, etc.) • ……
Vehicle Information • Number of vehicles • Vehicle condition: (No apparent defects; defective brakes; defective steering, etc.) • Vehicle type: (passenger cars, school bus, RVs, pick up trucks, etc.) • Vehicle action: (making left-turn, making U-turn, changing lanes, backing, etc.)
Roadway Information • Pavement material: ( concrete, asphalt, other) • Surface condition: (dry, wet, sand, ice, etc.) • Roadway defects • Roadway alignment-horizontal • Roadway alignment-vertical • Unusual roadway condition (no unusual conditions, under repair, under construction-traffic detoured, etc.) • Roadway characteristic (2-way striped median; 2-way painted median; 2-way raised median, etc.)
Environment Information • Location classification (recreational, farm, business, school, etc.) • Weather conditions (clear, not clear) • Light conditions (Daylight, others) • Traffic level (light, heavy& medium) • Speed limit
Some Notes of the Research Results • To improve modeling accuracy, 3 models were estimated separately for various accident types • single vehicle • car colliding with car • car colliding with trucks. • For the categorical accident types, level 1 (others) is used as the reference level. • For the categorical driver physical conditions, level 1( others and unknown) is used as the reference level.
Results of Single Vehicle Model Note: *- represents the parameters are statistically significant
Results of Car-Car Collision Model Note: *- represents the parameters are statistically significant
Results of Car-Truck Collision Model Note: *- represents the parameters are statistically significant
Discussion of Results • For all the three types of models (single vehicles, car-car collision, and car-truck collision), the use of alcohol significantly affects the accident types. • However, the use of illicit drug and other physical conditions has not shown an apparent influence to the types. • Since the research study uses only the accident data from the State of Arizona, the study findings need further confirmation.
Conclusion • General safety background • Description of the research method and crash data • Illustration of the results • Discussion