MPC
Research Projects (2008-09)

Identifying Number

MPC-309

Project Title

Rural Road Signage: Simulated Driving to Evaluate Low-Cost Safety Improvements for Older Drivers

University

North Dakota State University

Project Investigator

Kurt Johnson, Kimberly Vachal, Mark McCourt, Rob Gordon, Linda Langley and Mark Brady

Description of Project Abstract

Road safety is a major emphasis for the North Dakota Department of Transportation (NDDOT). The NDDOT promotes driver safety through engineering and education. According to the NDDOT crash data, almost 10% of all crashes between 2001 and 2007 involved drivers aged 75 and older. These drivers account for only about 8% of the driver population. This overrepresentation is especially concerning given population trends in the state. U.S. Census Bureau projects the population aged 65 and older in North Dakota to be 15% in 2010 and 25% in 2030. While age per se may not cause driving problems, physical and mental changes that occur with aging may create challenges for drivers (Dulisse 1997, Carr et al. 1994, Korteling 1994). Declining driving competency is associated with medical conditions that are more likely occur with advanced age (Hashim et al., 2002), such as impairments in vision, functional abilities and cognition, all of which have been linked to increased crash risk (Owsley et al. 1998, Mandel 2007).

Simulators offer a controlled yet reality-based environment for conducting driver research. Measures such as reaction time, pulse rate, stopping time, vehicle handling skills, and head motion provide important information about driver reaction to alternative driving scenarios. The simulator makes it possible to test reactions to situations that may be potentially hazardous if attempted in an on-road evaluation. Many studies have concluded that driving simulators can provide accurate observations on drivers’ behaviors and functions in comparison to actual driving experiences (Alicandri 1994, Fraser et al., 1994, Van der Winsum 1996, Desmond and Matthews 1997, Ellingrod et al. 1997, and Van der Winsum and Brouwer 1997). Driving simulation has been used to test visual attention and processing (Ball 2005, Wood 2002), cognitive ability (Freund et al. 2002, Cox et al 1998), and driving performance (Lee et al. 2002 and 2003).

The driving simulator is a well-established research too,l but application to rural road problems and situations is limited. About 97 percent of the lane miles and 75 percent of the AVMT in North Dakota are rural. This endeavor into rural simulator applications may be especially beneficial given data limitations associated with episodic nature of traffic crashes in the state. The simulator research can supplement often sporadic and geographically dispersed traffic crash data that is currently used for safety investment decisions.

Project Objective

This objective of this study is to use driving simulation to analyze the driving behavior of older (and mid-age) drivers on rural roads as it varies with road geometry (e.g., frequency and severity of turns; presence and size of shoulder), traffic, ambient light (day versus night driving), and the presence and location of road signage. We seek to determine the rural road conditions under which older drivers are most at risk for driving errors accidents and to assess the effectiveness of low-cost signage improvements for reducing such risks.

Project Approach/Methods

A driving simulator (Drive Safety DS 600c) will be used to implement driving scenarios. Stretches of rural roads in North Dakota which are problematic, based on available accident data, will be accurately modeled. Based on the accurate roadway model a number of versions will be created in which several parameters can be systematically varied. These parameters include the turning radius of roadway curves, the frequency of turns and (regulated or unregulated) intersections per unit driving distance, the presence and size of roadway shoulders, the ambient light level (day versus night), the presence and number of other vehicles, and the presence, location and type of roadway signage. Initially, two groups of drivers will be tested, a mid-age (30-50 years) control group, and an older adult (60-75 years) group. We anticipate including a cognitive challenge condition in which drivers will engage in hands-free cellular telephone communication, since distraction of this type has been shown to degrade driver performance (Strayer et al., 2003; Strayer & Drews, 2007), and may therefore increase the effect size of our other manipulations.

Each driver will undergo extensive pre-testing, including health status assessment and a battery of tests of attention, cognition and vision (simple- and choice-reaction time, vocabulary, useful field of view, contrast sensitivity, visual acuity, color vision, and depth perception from binocular disparity and motion parallax). The research protocols will be reviewed and approved by the NDSU Institutional Review Board, and informed consent will be obtained from each participant prior to their participation. Participants will be compensated at the rate of $10/hour.

In addition to catastrophic driver mistakes such as road run-offs and crashes, driving behavior will be indexed by analyzing speed, braking and acceleration patterns, road lane position, reaction times to inserted events (which can be ecologically valid – for example, a deer crossing the road, or can consist of arbitrary visual or auditory stimuli that drivers are instructed to monitor and respond to with steering wheel key presses). Eye gaze will also be monitored using video eyetracking.

Examples:

There are numerous potential independent variables and the design of various specific experiments will require careful consideration of time and resource-constraints. Below we outline several examples of how the team might conceptualize specific sub-experiments of the entire project.

The proposed experiments will determine what factors contribute to failure to stop at an intersection, respond to crossing traffic at an intersection, or to properly navigate a curve.

Reaction to intersections
Rural intersections may be marked by various signage (such as a stop sign) or they may be unmarked. Driver performance at intersections can be defined according to how appropriately the driver decelerates at intersections, or if they decelerate at all.

Factors which may influence driver reaction to the appearance of an intersection include: presence or absence of a warning sign, sign size and design, presence of a flashing light, clutter (including other signage, vegetation, or manmade structures), crossing traffic, oncoming traffic, following traffic, sudden appearance of the intersection (say after a hill) and time since the last intersection.

Reaction to crossing traffic at intersections
Once at a stop sign, performance can also be measured according to how soon (and whether) drivers respond to the appearance of crossing traffic.

The difficulty of responding to crossing traffic may be modulated by the suddenness of traffic appearance, as when the crossing road traverses a hill or curve. Whereas North Dakota does have long stretches of straight level roads, these roads also traverse highways and train tracks by means of raised bridges (essentially hills) and they involve curves to circumvent various natural and manmade obstacles.

Reaction to crossing traffic may depend on whether the intersection is regulated (by a four-way or a two-way stop) and whether the intersection is marked as such. Oncoming traffic, coincident with crossing traffic is a potential distraction.

Navigating curves
Curve navigation performance can be measured according to deviation from the centerline and how soon drivers begin deceleration prior to entering the curve.

Factors, which may affect performance in curves include warning sign presence and location, sign type (e.g., a series of small signs delimiting the curve vs. a single sign which depicts the curve), radius of the curve, time since last curve, shoulder width, sudden appearance of the curve, and oncoming traffic.

MPC Critical Issues Addressed by the Research

1. High-Risk Rural Roads.
2. Effective Safety Management.
3. Human Factors.
4. Low-Cost Safety Improvements.

Contributions/Potential Applications of Research

It will create a control group for testing other driver group’s response to alternative sign design and placement scenarios. Initiates a research partnership to couple transportation and psychology/human factors expertise at the NDSU Center for Visual Neuroscience. The research is designed to benefit safety professionals in understanding rural roads safety aspects such as roadways engineering (eg. shoulder width, lane width, pavement markings, signage) in relation to driver behavior (eg. capacities and decision processes).

Technology Transfer Activities

Findings will provide valuable information for understanding which low-cost safety improvements are most beneficial to older drivers.

Time Duration

July 1, 2008 – June 30, 2010

Total Project Cost

$62,900

MPC Funds Requested

$30,000

TRB Keywords

Safety, rural transportation, safe travel, safe driving, simulator, human behavior, older driver

References

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2. Carr, T.W., Jaskson, Madden D.J., and Cohen, H.J. (1994). The effect of age on driving skills. Am. Geriatr. Soc. Vol. (40) pp. 567–573.
3. Dulisse, B. (1997). Older drivers and risk to other road users. Accid Anal Prev Vol. (29), pp. 573–582.
4. Ellingrod, V.L., Perry, P.J., Yates, R.W., Maclnodoe, J.H., Watson, G. ,Arnalt, S., and Holman, T.L. (1997). The effects of anabolic steroids on driving performance as assessed by the Iowa driver simulator. Am. J. Drug Alcohol Abuse Vol. (23) 4, pp. 623–637.
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12. NDDOT. North Dakota Department of Transportation. 2006 crash summary. Accessed on 04/29/2008 http://www.dot.nd.gov/divisions/dlts/docs/crash-summary.pdf
13. U.S. Census Bureau. State Interim Population Projections by Age and Sex: 2004 – 2030. Accessed on 04/29/2008 http://www.census.gov/population/www/projections/projectionsagesex.html
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