TIME OF DAY MODELS OF MOTOR CARRIER ACCIDENT RISK

A time-dependent logistic regression model has been formulated to assess the safety of motor carrier operations. The model estimates the probability of having an accident at time interval t, subject to surviving (i.e., not having an accident) until that time. Three logistic regression models are estimated, which include time main effects (the driving time), time-independent effects (experience), time-dependent effects (time of day), and a series of time-related interactions. Driving time has the strongest direct effect on accident risk. The first 4 hr consistently have the lowest accident risk and are indistinguishable from each other. Accident risk increases significantly after the 4th hr, by approximately 50% or more, until the 7th hour. The 8th and 9th hr show a further increase, approximately 80% and 130% higher than the first 4 hr. Drivers with more than 10 years of driving experience retain a consistently low accident risk; all other categories of driving experience have a significantly higher risk. Daytime driving, particularly at the noon time (10:00 a.m. to 12:00 noon), results in a significantly lower risk of an accident. Drivers at one time of day (4:00 to 6:00 p.m.) have an accident risk about 60% higher than those driving during the baseline; drivers during the other three significant times of day also experience accident risks about 40% higher than drivers during the baseline. All three times of day involve night or dawn driving; two are associated with circadian rhythms. Rest breaks, particularly those taken before the 6th or 7th hr of driving, appear to lower accident risk significantly for many times of day.

[1]  R. P. Hertz,et al.  Tractor-trailer driver fatality: the role of nonconsecutive rest in a sleeper berth. , 1988, Accident; analysis and prevention.

[2]  C. Brown On the use of indicator variables for studying the time-dependence of parameters in a response-time model. , 1975, Biometrics.

[3]  R. Abbott Logistic regression in survival analysis. , 1985, American journal of epidemiology.

[4]  R B D'Agostino,et al.  Comparison of baseline and repeated measure covariate techniques in the Framingham Heart Study. , 1988, Statistics in medicine.

[5]  R. Pyke,et al.  Logistic disease incidence models and case-control studies , 1979 .

[6]  B. Efron Logistic Regression, Survival Analysis, and the Kaplan-Meier Curve , 1988 .

[7]  P. Goodyear Medical aspects of fitness to drive , 1987 .

[8]  E D Sussman,et al.  Driver inattention and highway safety , 1985 .

[9]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[10]  Tetsuya Kaneko,et al.  Exploratory Analysis of Motor Carrier Accident Risk And Daily Driving Patterns , 1991 .

[11]  M. Brenner,et al.  Fatigue and drug interaction in fatal to the driver heavy truck crashes , 1990 .

[12]  Tzuoo-Ding Lin,et al.  MODELING THE SAFETY OF TRUCK DRIVER SERVICE HOURS USING TIME-DEPENDENT LOGISTIC REGRESSION , 1993 .

[13]  J. Ware,et al.  On the use of repeated measurements in regression analysis with dichotomous responses. , 1979, Biometrics.

[14]  R. R. Mackie,et al.  EFFECTS OF HOURS OF SERVICE REGULARITY OF SCHEDULES, AND CARGO LOADING ON TRUCK AND BUS DRIVER FATIGUE , 1978 .

[15]  R P Hertz,et al.  Hours of service violations among tractor-trailer drivers. , 1991, Accident; analysis and prevention.

[16]  P P Jovanis,et al.  Multiday driving patterns and motor carrier accident risk: a disaggregate analysis. , 1991, Accident; analysis and prevention.

[17]  Michael E. McCauley,et al.  A STUDY OF HEAT, NOISE, AND VIBRATION IN RELATION TO DRIVER PERFORMANCE AND PHYSIOLOGICAL STATUS , 1974 .

[18]  Tzuoo-Ding Lin,et al.  ASSESSING MOTOR CARRIER DRIVING RISK USING COX'S SEMI-PARAMETRIC MODEL WITH MULTIPLE STOP EFFECTS. , 1992 .

[19]  R R Mackie,et al.  A study of the relationships among fatigue, hours of service, and safety of operations of truck and bus drivers , 1972 .

[20]  Nick McDonald,et al.  Fatigue, safety, and the truck driver , 1984 .

[21]  P. Hamelin,et al.  Lorry driver's time habits in work and their involvement in traffic accidents. , 1987, Ergonomics.

[22]  K D Hackman,et al.  ANALYSIS OF ACCIDENT DATA AND HOURS OF SERVICE OF INTERSTATE COMMERCIAL MOTOR VEHICLE DRIVERS , 1978 .

[23]  T J Triggs,et al.  DRIVER FATIGUE: CONCEPTS, MEASUREMENT AND CRASH COUNTERMEASURES , 1988 .