Investigation of National Highway System Roadways in the Highway Safety Information System States

Author(s):  
Charles V. Zegeer ◽  
Herman F. Huang ◽  
J. Richard Stewart ◽  
Carolyn Williams

Motor vehicle crash rates and roadway characteristics for National Highway System (NHS) and non-NHS roads in seven states—California, Illinois, Maine, Michigan, Minnesota, North Carolina, and Washington— are presented. Accident and roadway data were extracted from the Federal Highway Administration’s Highway Safety Information System. Overall, crash rates on NHS roads were approximately 10 percent lower than those on non-NHS roads, perhaps the result of higher design standards. Crash rates on urban roadways were considerably higher than on the corresponding rural roadways in each state. For rural roadways, fixed-object crash rates were higher on NHS roads than on non-NHS roads. The distribution of crashes by severity was quite similar on NHS and non-NHS roads. For urban freeways, NHS Interstates usually had lower crash rates than NHS non-Interstates. The majority of NHS roads had lane widths of 3.4 m (11 ft) or more, and many had shoulder widths of 1.5 m (5 ft) or more. Compared to NHS non-Interstate roads, NHS Interstate roads were more likely to have lane widths of 3.7 m (12 ft) or over, shoulder widths of 2.4 m (8 ft) or over, paved shoulders, and improved median design. Highway designers and safety officials can use this type of information about accident rates and roadway characteristics to enhance safety by upgrading existing highways and improving the design of NHS highways to some specified roadway design standards and guidelines.

2016 ◽  
Vol 22 (Suppl 2) ◽  
pp. A303.2-A303
Author(s):  
Allison E Curry ◽  
Kristina B Metzger ◽  
Melissa R Pfeiffer ◽  
Flaura K Winston ◽  
Michael R Elliott ◽  
...  

2021 ◽  
Author(s):  
Nina R Joyce ◽  
Marzan A Khan ◽  
Andrew R Zullo ◽  
Melissa R Pfieffer ◽  
Kristina B Metzger ◽  
...  

Background/Objectives: Thirty states allow licensing agencies to restrict the distance from home that medically–at–risk drivers are permitted to drive. However, there is little information on where older drivers crash relative to their home or how distance to crash varies by medical condition, and thus, what impact distance limits may have on motor vehicle crash rates for medically–at–risk drivers. Design: Observational study of crash-involved drivers. Setting: Medicare fee–for–service claims linked to geocoded crash locations and residential addresses from police crash reports in the state of New Jersey from 2007 through 2017. Participants: New Jersey Medicare fee–for–service beneficiaries aged 68 years and older involved in police–reported crashes. Measurements: The outcome was Euclidian distance from home to crash location. Covariates included driving-relevant medical conditions from Medicare claims, crash characteristics from police reports, and demographics from both sources. Results: There were 197,122 crash-involved older drivers for whom approximately 70% of crashes occurred within 5 miles and 95% within 25 miles of the drivers residence. The mean distance to crash was 6.0 miles. Although distance from home to the crash was generally lower among drivers with (versus without) each of the medical conditions studied, the differences were small (maximum mean difference of 2.1 miles). The largest difference in distance was by licensure status, where unlicensed/suspended drivers crashed significantly farther from home than validly licensed drivers (8.8 miles, 95% Confidence Interval [CI]: 8.4—9.1 vs 5.9 miles, 95% CI: 5.9 — 6.0). Conclusions: Findings suggest that the majority of older adults who crash do so within a few miles from home and that the distance to crash does not differ substantially by the presence of a driving–relevant medical condition. Thus, distance restrictions may not reduce crash rates among older adults and the tradeoff between safety and mobility warrants consideration.


Author(s):  
David K. Willis

In the U.S., 16 and 17 year-old drivers have horrendous motor vehicle crash rates. Young teen drivers are also vastly over-involved in fatal traffic crashes. In order to better understand the causes of this teen driver crash problem and then develop appropriate countermeasures, the AAA Foundation for Traffic Safety commissioned the first comprehensive re-examination in more than 20 years of what novice drivers need to learn and do in order to be safe drivers. The resultant research report (Lonero, et al., 1995) led to the creation of an innovative, computer-based risk management training program for teen drivers, released in February, 1998.


2016 ◽  
Vol 22 (Suppl 2) ◽  
pp. A302.2-A302
Author(s):  
Allison E Curry ◽  
Kristina B Metzger ◽  
Benjamin Yerys ◽  
Siobhan Gruschow ◽  
Melissa R Pfeiffer ◽  
...  

Author(s):  
Vernon S. Ellingstad ◽  
Daniel P. Westra

Determination of the impact of Traffic Safety Programs (TSPs) on motor vehicle crash rates forces the evaluator to utilize N of 1 quasi-experimental designs. A variety of procedures which take into account the serial dependency frequently observed in such data is described, and their application to assessment of change in crash time series is illustrated.


Safety ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 48 ◽  
Author(s):  
Adekunle Adebisi ◽  
Jiaqi Ma ◽  
Jaqueline Masaki ◽  
John Sobanjo

With ongoing changes in the age distribution of drivers in the United States, it is important to obtain insights on how to make the roadways equally safe for drivers across different age groups. In light of this, the objective of this study is to examine various crash characteristics and make recommendations on how to potentially improve roadway safety for all age groups. Using the Highway Safety Information System (HSIS) data, this study investigates the factors influencing motor-vehicle crash injury severity for young (aged 16–25), middle-aged (aged 26–64), and older drivers (above 64) in the state of California. A multinomial logit model was used to separately model crashes involving each age group and to evaluate the weight of different predictor variables on driver injury severity. The predictor variables were classified into four—driver, roadway, accident and environmental characteristics. Results suggest that there are close relationships between severity determinants for young and middle-aged drivers. However, older drivers tend to be most cautious among all age groups under all environmental and roadway conditions. Young drivers are more likely to explore their driving skills due to newness to driving. Middle-aged drivers are familiar with driving and tend to demonstrate less cautious behaviors, especially male drivers. Another insight obtained from this study is that older driver behavior is less dynamic compared to other age groups; their driving pattern is usually regular regardless of the surrounding conditions.


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