Older Driver Crash Analysis (2019 Update)

Demographic Trend Scripps Gerontology Center 2015

Current Population Statistics When Ohio census data is reviewed by county to identify older driver populations, the high density urban areas rise to the top including Hamilton, Montgomery, Franklin and Cuyahoga County, with Cuyahoga County having significantly greater older population that all others. It is also noted that areas to the east including Trumbull and Mahoning counties also have elevated older populations. County Population ≥65 Percentage of County Population ≥ 65

Older Driver Crash Distributions Moving from population to examining crash frequency, as expected, crash frequency involving older drivers follows population distributions in general terms, but it is noted that there is a greater separation between high concentrations and the low concentrations, than was evident in the population distribution. To state it another way there are less middle areas of older driver crashes than there are older driver populations. # of Crashes Crash Rate Per Capita

Crash Analysis 3 year crash analysis of older driver population (2016-2018) Updated from original analysis (2013-2015) Applied use of Relative Crash Rate The relative crash rate is a method that allows for estimation of driving exposure similar to the use of vehicle miles of travel to correct for lower driving rates of older drivers.

Crash Severity Serious Injury Crashes Fatal Crashes All Crashes : 25.1% (31.7%) Older Driver Involved : 27.4% (33.3%) Older Driver At Fault: 27.1% (37.8%) Fatal Crashes 1.45 times greater chance of fatality with older driver involvement (2013-2015 data) When evaluating serious injury rates of all crashes compared to injury rates of older drivers it is demonstrated that older driver crashes have a higher overall injury rate and a fatality rate of 1.45 times the average fatality rate. This may be attributed to the increased fragility of older drivers leaving them more susceptible to injury. However, when examining crashes where the older drivers are at fault, i.e., causing the crash, there is an even higher injury rate. When crash types of older drivers are then further evaluated this is shown to be attributable to the higher incidence rate of high severity crash types as shown in the following slides.

Relative Crash Rate (Expanded Age Groups) One thing to note within this analysis, is that even though older drivers greater than 65 years of age are often grouped together, crash involvement changes significantly as the population ages within the grouping. These figures show the relative accident involvement ratios for crashes at stop signs and traffic signal for 10 year cohorts with 65-75in blue, 76-85 in brown and 86-95 in grey. The younger cohort 66-75 has a ratio of approximately 1, lower than the younger drivers with a 1.5. However, exponential increase is seen in the following cohorts far exceeding even the high crash experience of new drivers.

Relative Crash Rate by Crash Type When evaluating crash rates by crash rates older drivers are seen to perform as poorly or even worse as young driving populations for angle, left turn and pedestrian crashes. It is noted however, the rear end, fixed object and overturning crash patterns are significantly different with the older driving population having the lowest rate of the three groups evaluated for fixed object and overturning crashes. The disparity in the distribution of these crash types may assist in evaluating the behaviors that lead to the high crash patterns themselves. For instance, the high frequency of fixed object and overturning crashes may be representative of higher risk taking behavior, i.e. higher speeds in younger driver populations that may also carry over into angle and left turn type crashes, i.e., accepting smaller than desirable gaps. The absence of these risk taking behaviors for older drivers may speak to different contributing problems, such as visualization and/or decision making in performing complex maneuvers.

Relative Crash Rate by Contributing Factor DUPLICATE OF PREVIOUS SLIDE WITH REDUCED CONTRIBUTING FACTORS These types of behaviors are reinforced when evaluating crash contributing factors as shown here. Where older drivers have low incidences of following too close, excessive speed or failure to control, but have the highest rates of failure to yield, improper lane changes and improper turning. It is also noted that running red lights and stops signs are also highly represented within the data set.

Relative Crash Rate by Location Based on the drive action analysis and contributing factors identified above identifying maneuvers, which older drivers may have difficulty with, this is reinforced when evaluating crash location. As can be seen in the graph, driveway access and intersections have high rates of incidence, while non-intersections and even railroad crossing, which do not require complex maneuvers by drivers have significantly lower involvement rates.

Relative Crash Rate by Traffic Control When evaluating the type of traffic control in place, it is noted that the older driver population has the highest rate of involvement when construction barricades are present, exceeding even the younger driver population. All other intersection control types including stop signs, flashers, signals and yield signs also demonstrate higher involvement of older drivers.

Additional Analysis Crashes by Light Condition Crashes by Road Condition Due to known degradation in visual acuity, especially in low light conditions for older drivers, analysis was done to identify crash involvement based on varying light conditions. Shown are dark, daylight and dusk involvement ratios. As can be seen from the graphs, the older driver population has a lower involvement during dark and daylight hours than during daylight conditions which may be considered optimal conditions for older drivers. Under conditions older drivers are thought to perform poorly, crash rates are lower This may demonstrate the likelihood of older drivers to self-regulate exposure risks.

N. Bend Road at W. Fork Road 40% Older Driver Crashes 17% County Population I-74 Adjacent Intersection Skew When identifying older driver crash clusters, they are shown to typically match high crash areas of older drivers. Especially in the urban environment, difficulties of older drivers may not create new high crash locations, but may exacerbate problem locations. Typical engineering solutions to address similar crash problems, such as access control, protected turn movements, and improved signing/markings have the potential to address ALL crashes, not just older driver problems.

Main Street at Court St. Woodfield 6 of 8 Backing Crashes involve older drivers. 4/6 Older Driver is not-at-fault 20 percent older driver county population Even though older drivers are cited most frequently as not-at-fault, this distinct pattern indicates a failure of older drivers to recognize or process backing maneuvers when approaching an intersection. Potential solutions may include reverse angle parking so that the onus of stopping is placed on the parked vehicles, as opposed to the circulating driver. It is noted that this solution would likely be identified regardless of driver age.

Key Points The older driver population is increasing (significant portion of the population within 15 years). Serious injury crash percentages for older drivers have decreased since 2015. Older driver crashes have a higher rate of serious injury and fatal crashes

Key Points Increased crash severity is likely due to Increased fragility of older drivers Increased frequency of high severity crash types more common to older drivers Higher crash rates at intersections and under complex traffic control maneuvers, e.g., left turns.

Key Points Crash rates increase substantially after age 75 Older drivers show a willingness to self regulate

Recommendations Engineering May not require additional countermeasures Older drivers may exacerbate existing problems creased older driver populations

Recommendations Engineering Focus on safety versus operations in highly concentrated areas creased older driver populations

Recommendations Engineering Increase traffic control visibility: Redundant/near side signal heads Duplicate/oversized stop signs More reflective pavement markings Protect complex maneuvers: Protected only left turn phasing Access management creased older driver populations

Recommendations Planning Provide alternate transportation options As evidenced by the variable rates of driver exposure and per capita crash involvement in major urban areas

Recommendations Education/ Outreach Education of “safe routes” may be successful for older drivers. (i.e., avoid left turn maneuvers, congested roadways). As evidenced by the willingness of older drivers to self mitigate hazardous conditions (i.e., avoid low light conditions)

Questions. Kevin Miller, P. E. , PTOE CMT, Inc. kmiller@cmtengr Questions? Kevin Miller, P.E., PTOE CMT, Inc. kmiller@cmtengr.com (937) 701-6581 The relative crash rate is a method that allows for estimation of driving exposure similar to the use of vehicle miles of travel to correct for lower driving rates of older drivers.

Relative Crash Rate by Crash Type When evaluating crash rates by crash rates older drivers are seen to perform as poorly or even worse as young driving populations for angle, left turn and pedestrian crashes. It is noted however, the rear end, fixed object and overturning crash patterns are significantly different with the older driving population having the lowest rate of the three groups evaluated for fixed object and overturning crashes. The disparity in the distribution of these crash types may assist in evaluating the behaviors that lead to the high crash patterns themselves. For instance, the high frequency of fixed object and overturning crashes may be representative of higher risk taking behavior, i.e. higher speeds in younger driver populations that may also carry over into angle and left turn type crashes, i.e., accepting smaller than desirable gaps. The absence of these risk taking behaviors for older drivers may speak to different contributing problems, such as visualization and/or decision making in performing complex maneuvers.

Relative Crash Rate by Contributing Factor These types of behaviors are reinforced when evaluating crash contributing factors as shown here. Where older drivers have low incidences of following too close, excessive speed or failure to control, but have the highest rates of failure to yield, improper lane changes and improper turning. It is also noted that running red lights and stops signs are also highly represented within the data set.

Relative Crash Rate by Contributing Factor DUPLICATE OF PREVIOUS SLIDE WITH REDUCED CONTRIBUTING FACTORS These types of behaviors are reinforced when evaluating crash contributing factors as shown here. Where older drivers have low incidences of following too close, excessive speed or failure to control, but have the highest rates of failure to yield, improper lane changes and improper turning. It is also noted that running red lights and stops signs are also highly represented within the data set.

Relative Crash Rate by Location Based on the drive action analysis and contributing factors identified above identifying maneuvers, which older drivers may have difficulty with, this is reinforced when evaluating crash location. As can be seen in the graph, driveway access and intersections have high rates of incidence, while non-intersections and even railroad crossing, which do not require complex maneuvers by drivers have significantly lower involvement rates.

Older Driver Relative Crash Rate Location by Urban/Rural Based on the drive action analysis and contributing factors identified above identifying maneuvers, which older drivers may have difficulty with, this is reinforced when evaluating crash location. As can be seen in the graph, driveway access and intersections have high rates of incidence, while non-intersections and even railroad crossing, which do not require complex maneuvers by drivers have significantly lower involvement rates.

Relative Crash Rate by Traffic Control When evaluating the type of traffic control in place, it is noted that the older driver population has the highest rate of involvement when construction barricades are present, exceeding even the younger driver population. All other intersection control types including stop signs, flashers, signals and yield signs also demonstrate higher involvement of older drivers.

Older Driver Crash Rate Traffic Control by Urban/Rural When evaluating the type of traffic control in place, it is noted that the older driver population has the highest rate of involvement when construction barricades are present, exceeding even the younger driver population. All other intersection control types including stop signs, flashers, signals and yield signs also demonstrate higher involvement of older drivers.

Relative Crash Rate by Traffic Control (Expanded Age Groups) One thing to note within this analysis, is that even though older drivers greater than 65 years of age are often grouped together, crash involvement changes significantly as the population ages within the grouping. These figures show the relative accident involvement ratios for crashes at stop signs and traffic signal for 10 year cohorts with 65-75in blue, 76-85 in brown and 86-95 in grey. The younger cohort 66-75 has a ratio of approximately 1, lower than the younger drivers with a 1.5. However, exponential increase is seen in the following cohorts far exceeding even the high crash experience of new drivers.

Additional Analysis Crashes by Light Condition Crashes by Road Condition Due to known degradation in visual acuity, especially in low light conditions for older drivers, analysis was done to identify crash involvement based on varying light conditions. Shown are dark, daylight and dusk involvement ratios. As can be seen from the graphs, the older driver population has a lower involvement during dark and daylight hours than during daylight conditions which may be considered optimal conditions for older drivers. Under conditions older drivers are thought to perform poorly, crash rates are lower This may demonstrate the likelihood of older drivers to self-regulate exposure risks.