Driver Inattention in Fatal and Injury Traffic Crashes

Janace A. Pierce, Research Data Systems, Dale Cooper, Leslie Upledger Ray, Patricia A. Murrin, County of San Diego Health and Human Services Agency, Division of Emergency Medical Services

Introduction:

Following the surge in the number of cell phones in use, many jurisdictions have considered banning their use while driving. The assumption has been that drivers are inattentive to driving while using the phone and therefore the phone use causes crashes.

In California, data has been collected on driver inattention, without reference to the cause of inattention, for a number of years. However, little attention has been paid to this data element.

Starting in January 2001, the cause of inattention is being recorded in 10 categories: Cell phone use, electronic equipment, radio/CD, smoking, eating, children, animals, personal hygiene, reading and other.

While it is not possible to draw any conclusions about cell phone use causing crashes using available data, we can look at and assess the role of inattention as a causal factor in crashes.

Methods

This study investigates crashes for which inattention of the driver-at-fault was reported as a factor in the crash. The following aspects of inattention crashes are examined:

- Trends in the number and percent of inattention crashes over a five-year period

- Violation categories with which inattention is associated

- Age and gender of drivers-at-fault in inattention crashes

- Road type

- Time of day/Time of week

- Interaction of age and gender with violation categories, road type and time of crash

- Subregional areas of the county

The SWITRS GIS Data System

The data used for the study are from the Statewide Integrated Traffic Records System (SWITRS) data system. The data set used consists of all fatal and injury crashes that occurred in the County of San Diego. These data are maintained by the County of San Diego Health and Human Services Agency, Division of Emergency Medical Services (EMS).

SWITRS data are collected by the CA Highway Patrol, City Police, and Sheriffs, depending on the type of roadway jurisdiction. Included in this extensive data set are variables describing the crash, the various parties in the crash (drivers, pedestrians, etc), and each of the victims injured or killed in the crash. The crash location is defined by a municipality designation and the intersection of two streets/roads with a directional offset. For crashes that occur on state highways, a postmile location and direction of travel are also reported.

A program, written in Avenue, is used to automatically locate each of the crashes in the data set. The program also provides a special interface to manually locate crashes that the automated system could not locate. When all of the crashes in a given data set have been located, zipcode and SRA (codes for subregional areas) are assigned, based on shape-files provided by SanGIS. These data fields are exported and later merged with the data analysis files that are maintained in SPSS (Statistical Package for the Social Sciences) format. This allows us to produce statistics about drivers and victims as well as about crashes according to any geographic region as long as the geographic region can be represented as an aggregate of either zipcode areas or subregional areas. The mapping versions of the crash files, augmented by variables calculated in the analysis databases, are used to create dot maps of crashes that, for example, show crashes in which inattention was reported for the driver-at-fault.

Results

Trends over 5 years: During the last decade, there has been an explosion of the use of cell phones and other electronic devices by drivers. The common assumption has been that the increase in use of these devices would be reflected in a comparable increase in inattention-related crashes. Therefore, it comes as a surprise that over the past five years, the number of fatal and injury inattention crashes has decreased, both in numbers and as a percent of all fatal and injury crashes. These trends can be seen in Table 1 and Figure 1.

Table 1 shows the number of fatal and injury crashes for which inattention was reported, for five years, from FY 95/96 (July 1, 1995 to June 30, 1996) to FY 99/00 (the last year for which geographic data is currently available). Inattention is considered a causal factor in a crash if inattention was reported for the driver-at-fault in the crash. The number of crashes with inattention as a causal factor dropped from 2698 in FY 95/96 to 2243 in FY 99/00. There was a similar drop in the number of crashes in which inattention was reported for any driver in the crash: 2890 in FY 95/96 to 2636 in FY 99/00. During the same period, there was an increase in all fatal and injury crashes from 14970 to 15651.

Figure 1 shows the percent of all fatal and injury crashes for which inattention was reported. “Inattention as a factor” and “Inattention as a causal factor” show similar drops over the 5-year period.

In summary, there has been a decrease in both the absolute numbers and the percentages of inattention crashes among those crashes where someone was injured or killed.

Violation Categories: The top ten violation categories associated with inattention crashes are essentially the same as for all fatal and injury crashes. Unsafe Speed, Auto Right-of-Way, Traffic Signals and Signs, Improper Turning, Following Too Closely, DUI Alcohol/Drugs, Unsafe Starting or Backing, Wrong Side of Road, Pedestrian Right-of-Way, and Unsafe Lane Change. In Figure 2, you can see that inattention is differentially

associated with these violation categories. Inattention is a causal factor in about 30% of

crashes where the violation categories are Following Too Closely, Unsafe Starting or Backing, and Pedestrian Right-of-Way. In contrast, inattention is a causal factor in only about 7% of DUI crashes and 9% for Unsafe Lane Change.

Inattention by male and female drivers is associated with the violation categories somewhat differently, as can be seen in Figure 3. The percent of inattention crashes for males is higher than for females when the violation category is Following Too Closely

(Males 30.5%, Females 27.3%) or Pedestrian Right-of-Way (Males 22.7%, Females 19.4%). The percent is higher for females when the violation category is Unsafe Starting or Backing (Males 24.8%, Females 31.5%) or Wrong Side of Road (Males 7.6%, Females 17.6%).

Gender and Age: In order to understand the role of gender more completely, it is useful to see how gender and age are represented among the drivers-at-fault in all fatal and injury crashes, and inattention crashes in particular.

Figure 4 shows crashes by gender and age of driver-at-fault: all fatal and injury crashes and inattention crashes. In all age categories, the number of crashes for males is higher than the number of crashes for females. Male inattention crashes total 1290, female 891.

In Figure 5 we see that for nearly all age groups, the percent of drivers-at-fault that are inattentive is larger for females than for males. The exception is the age group 35 to 44 where the percent is nearly the same for males and females. On average, male drivers-at -fault are inattentive in 15.8% of their crashes while the percent for female drivers-at-fault is 18.0% (FY 99/00).

Road Type. For an examination of crashes by road type, State highways (including Interstate highways) were divided into two classes: Major Freeways and Other State Highways. Major Freeways were defined as: I-5, I-8, I-15, I-805, 52, 94, 163, 905, and 78 (except in zipcodes 92027, 92070, 92036, and 92004). The other State highways are called “Other State Highways.” All roads not identified as State highways are called “Other Streets and Roads.” This latter group of roads contains all the surface streets in the cities and in the jurisdiction of the County. Figure 6 is a map showing inattention -caused crashes categorized by road type.

Table 2 shows the inattention of the driver-at-fault by road type. Inattention is reported as a causal factor for only 7.4% of crashes on major freeways. In contrast, inattention is reported as a causal factor for 17.0% of crashes on “Other Streets and Roads”. (Note that included in the “Not Reported” column are crashes in which fault was not assigned.)

Figure 7 shows that females have a higher percent of crashes on Other Streets and Roads. This occurs in all crashes as well as inattention crashes. This suggests that the higher rate for females in inattention-caused crashes results from women travelling and having their crashes more frequently in the complex environment of surface streets.

Time of Day/Week: It was hypothesized that rush hour traffic would create many conditions favoring inattention crashes. Therefore time categories were set up to explore this. Categories used were:

- Wee Hours, Tuesday to Friday (12:01 a.m. to 6:00 a.m.)

- Morning Rush Hour, Monday to Friday (6:01 a.m. to 9:00 a.m.)

- Daytime Monday to Friday (9:01 a.m. to 4:00 p.m.)

- Evening Rush Hour, Monday to Friday (4:01 p.m. to 7:00 p.m.)

- Evening, Monday to Thursday (7:01 p.m. to Midnight)

- Weekend Night, Friday to Sunday (7:01 p.m. to 6:00 a.m. the next day)

- Weekend Day, Saturday and Sunday (6:01 a.m. to 7:00 p.m.)

Figure 8 shows the location of inattention crashes that occur during the week in the daylight hours. Morning and evening rush hour crashes appear to be more clustered, especially the evening rush hour. (The appearance of differential clustering may result from the fact that the evening rush hour is the top layer of crashes.)

The number of crashes in each of the seven time periods and the crash rate per hour are shown in Figures 9 and 10. A number of things stand out from examination of these two charts.

- Inattention crashes are much more frequent on surface streets (Other Streets and Roads) than on any of the State highways.

- The time of day/week pattern is very different between surface streets and freeways.

- The largest number of inattention crashes on surface streets occur in the daytime hours (9:01 a.m. to 4:00 p.m.) during the week, but the highest hourly rate is during the evening rush hour.

- The largest number and hourly rate of inattention crashes on major freeways occur during daytime hours on the weekend.

- On the major freeways, the morning rush hour has a higher rate of inattention crashes than the evening rush hour.

Interpretation of these results is not straightforward because the number of miles of surface streets is large relative to the number of miles of freeways. Further, and perhaps most importantly, the number of vehicle miles traveled on the freeways and on surface streets is not a known quantity.

Subregional Areas: Subregional areas (SRA’s) are used widely throughout the County of San Diego for monitoring and planning activities. Many statistical measures are calculated and available to the public describing these areas; for example: demographic data, area, miles of road, etc. For this analysis, we examined the number of crashes, the crash rate per mile of road, and the relationship between crash rate and road density.

Figure 11 maps the number of crashes per mile of road by SRA. Table 3 shows the data for each of the SRAs: The number of crashes, the number of miles of road, the number of inattention crashes per mile of road and the road density (miles of road per 1000 acres of area). These data are sorted by the number of inattention crashes per mile of road.

The SRAs with the highest rate of inattention crashes per mile of road are:

- National City (0.512 inattention crashes per mile of road)

- Central San Diego (0.510 inattention crashes per mile of road)

- Santee (0.509 inattention crashes per mile of road)

- Mid-City (0.345 inattention crashes per mile of road)

- Oceanside (0.337 inattention crashes per mile of road)

- Lemon Grove (0.333 inattention crashes per mile of road).

The per mile rates for National City, Central San Diego and Santee are substantially higher than in any other part of the County.

The SRAs with the highest number of crashes are:

- Central San Diego (203 inattention crashes)

- Oceanside (185 inattention crashes)

- Kearny Mesa (157 inattention crashes)

- Escondido (134 inattention crashes)

- Mid-City (109 inattention crashes)

- Carlsbad (103 inattention crashes)

Central San Diego, Mid-City, and Oceanside SRAs are in the top 6 rank for both total number of inattention crashes and crashes per mile.

It seems logical that the number of crashes per mile of road might be correlated with the density of roads – miles of road per 1000 acres. A Pearson correlation coefficient was calculated: r = 0.725 which is statistically significant with p = .01. Figure 12 shows the scatter plot for these two variables.

Summary and Conclusions:

Trends. There has been a small, but consistent decrease in both the number and proportion of inattention crashes from FY 95/96 to FY 99/00. This suggests that the increase in cell phone use by drivers does not cause fatal or injury crashes. However, this does not preclude the possibility that property-damage only crashes might be caused by such cell phone use. Further, it’s possible that cell phone use does cause fatal or injury crashes, but that major improvements in controlling other distractions in vehicles counteracts the increase.

Gender. Overall, inattention was a causal factor in 14.5% of all fatal and injury crashes in FY 99/00. In those inattention crashes where fault was assigned, crashes caused by inattentive male drivers outnumber those caused by inattentive female drivers (males 1290, females 891). However, proportionately (relative to all crashes), females have a higher rate of inattention crashes (males 15.8%, females 18.0%).

Violation Category. High rates of inattention were reported for the following violation categories (FY 99/00):

- Following too closely (31%)

- Pedestrian Right-of-Way (30%)

- Unsafe Starting or Backing (30%)

- Traffic Signals and Signs (27%)

- Unsafe Speed (22%)

Male drivers were more likely to have had the violation categories Following Too Closely, or Pedestrian Right-of-Way. Females were more likely to have had the violation categorie Unsafe Safe Starting or Backing.

Road Type. An overwhelming percent of inattention crashes occurred on surface streets/roads – 82%. Only 13% occurred on major freeways. Females are more likely than males to have inattention crashes on surface streets.

Time of Day/Week. The rate per hour of inattention crashes varied by time of week and type of road. The highest rate of inattention crashes on surface streets/roads is the evening rush hour (4:01 p.m. to 7:00 p.m.), followed by the daytime hours during the week (9:01 a.m. to 4:00 p.m.). The highest rate for major freeways is on the weekend during the day (6:01 a.m. to 7:00 p.m.).

Subregional Areas. Central San Diego, Mid-City, and Oceanside are the worst areas in the County for inattention crashes—they rank in the top six for both the total number of inattention crashes and the number of inattention crashes per mile of road. There is a significant correlation between the rate per mile of inattention crashes and the road density of the SRA. (r = .725, p = .01)

Conclusions:

- Inattention has decreased as a causal factor in crashes in spite of more pressure on police to report inattention.

- Inattention is reported more frequently on surface streets than on freeways and other state routes.

- The frequency of inattention crashes varied by gender of party at fault relative to

- Type of Road

- Violation Category

- Time of Crash

- Central San Diego, Mid-City, and Oceanside SRAs are the worst areas in San Diego County for inattention crashes.