Safety Effects of Horizontal Curve Design on Motorcycle Crash Frequency on Rural, Two-Lane, Undivided Highways in Florida

2017 ◽  
Vol 2637 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Chunfu Xin ◽  
Zhenyu Wang ◽  
Pei-Sung Lin ◽  
Chanyoung Lee ◽  
Rui Guo
Keyword(s):  
Negative Binomial ◽  
Design Parameters ◽  
Negative Binomial Regression Model ◽  
Horizontal Curve ◽  
Random Parameters ◽  
Crash Frequency ◽  
Curve Design ◽  
Time Space ◽  
Curve Radius ◽  
Motorcycle Crashes

The association between horizontal curve design (e.g., radius and type) on rural, two-lane, undivided highways and motorcycle crash frequency is not well documented in existing reports and publications. This study aimed to investigate the effects of design parameters and associated factors on the occurrence of motorcycle crashes with consideration of the issue of unobserved heterogeneity. A random-parameters negative binomial regression model was developed on the basis of data on 431 motorcycle crashes, which were collected on 2,179 horizontal curves along two-lane, undivided highways in Florida for 11 years (2005 to 2015). Four normally distributed random parameters (i.e., logarithm of curve radius, reverse curves, pavement condition, and rough pavement indicator) were identified to represent their heterogeneity caused by unobserved factors over time, space, individuals, or some combination thereof. The major conclusions are the following: ( a) an increase in curve radius, on average, significantly and near-logarithmically reduced motorcycle crash frequency on rural, two-lane, undivided highways (this effect was more significant when the curve radius was less than 2,000 ft); ( b) 74.8% of reverse curves tended to reduce motorcycle crash frequency on rural, two-lane, undivided highways (for the remaining 25.2%, the effect had an opposite effect; on average, the likelihood of motorcycle crashes on reverse curves decreased by 39%); ( c) the crash modification function (CMF) for curve radius on rural, two-lane, undivided highways was established, given the radius of 5,000 ft as the baseline, as a power formula, CMF = (radius/5,000)-0.208.

Modeling Safety Effects of Horizontal Curve Design on Injury Severity of Single-Motorcycle Crashes with Mixed-Effects Logistic Model

2017 ◽  
Vol 2637 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Chunfu Xin ◽  
Zhenyu Wang ◽  
Chanyoung Lee ◽  
Pei-Sung Lin
Keyword(s):  
Logistic Model ◽  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Mixed Effects ◽  
Severe Injury ◽  
Horizontal Curve ◽  
Random Parameters ◽  
Horizontal Curves ◽  
Curve Design ◽  
Motorcycle Crashes

Horizontal curves have been of great interest to transportation researchers because of expected safety hazards for motorcyclists. The impacts of horizontal curve design on motorcycle crash injuries are not well documented in previous studies. The current study aimed to investigate and to quantify the effects of horizontal curve design and associated factors on the injury severity of single-motorcycle crashes with consideration of the issue of unobserved heterogeneity. A mixed-effects logistic model was developed on the basis of 2,168 single-motorcycle crashes, which were collected on 8,597 horizontal curves in Florida for a period of 11 years (2005 to 2015). Four normally distributed random parameters (moderate curves, reverse curves, older riders, and male riders) were identified. The modeling results showed that sharp curves (radius <1,500 ft) compared with flat curves (radius ≥4,000 ft) tended to increase significantly the probability of severe injury (fatal or incapacitating injury) by 7.7%. In total, 63.8% of single-motorcycle crashes occurring on reverse curves are more likely to result in severe injury, and the remaining 26.2% are less likely to result in severe injury. Motorcyclist safety compensation behaviors (psychologically feeling safe, and then riding aggressively, or vice versa) may result in counterintuitive effects (e.g., vegetation and paved medians, full-access-controlled roads, and pavement conditions) or random parameters (e.g., moderate curve and reverse curve). Other significant factors include lighting conditions (darkness and darkness with lights), weekends, speed or speeding, collision type, alcohol or drug impairment, rider age, and helmet use.

Development and Adoption of Early AASHO Design Criteria

1998 ◽  
Vol 1612 (1) ◽  
pp. 26-33 ◽  
Author(s):  
Jerome Hall ◽  
Daniel Turner
Keyword(s):  
Design Parameters ◽  
Design Criteria ◽  
Adoption Process ◽  
Horizontal Curve ◽  
Highway Design ◽  
Initial Development ◽  
Design Processes ◽  
Blue Book ◽  
Curve Design ◽  
Independent Design

The conception, development, and adoption of early AASHO highway design criteria are documented. Examining the early efforts states used to select a design vehicle and develop horizontal curve design criteria illustrates why AASHO’s leadership was necessary. AASHO’s slow and somewhat haphazard criteria development, and the disparity from state to state, demonstrated the need for a national consensus in highway design parameters. AASHO’s role in providing these criteria is outlined through its initial development of policy booklets, followed by its 1954 publication of the landmark Blue Book. The processes by which nine states adopted the AASHO guidance are briefly reviewed. In several cases, the AASHO policy was embraced immediately, and in others it was accepted slowly as states clung to their independent design processes and only gradually updated their design criteria. A few simple conclusions are drawn about the development and adoption process, particularly as it may relate to tomorrow’s highway design criteria.

scholarly journals Collision prediction on combined horizontal and vertical alignments of two-lane rural highways.

2021 ◽  
Author(s):  
Qing Chong You
Keyword(s):  
Associated Factors ◽  
Negative Binomial ◽  
Horizontal Curve ◽  
Rural Highways ◽  
Vehicle Accidents ◽  
Horizontal Curves ◽  
Curve Radius ◽  
Grade Increase ◽  
Minimum Ratio ◽  
Successful Predictor

This study investigates the safety effects of combined horizontal and vertical alignments using accident occurrences on two-lane rural highways in Washington. Eight statistical models were developed to establish the relationships between vehicle accidents and their associated factors for eight combinations of alignments by the Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. Three selected models were validated. The findings show that degree of curvature is the most successful predictor for horizontal curves combined with vertical alignments. A minimum ratio of 25 of vertical curve radius to horizontal curve radius is recommended for a curve with radius of smaller than 6000 ft (or 1830 m). Vertical curves have relatively little influence on accident occurrences at horizontal tangents. The grade value and length of a grade increase accident occurrences when a horizontal curve or tangent is on a grade. A smaller curve should be avoided introducing at a steep grade.

scholarly journals Collision prediction on combined horizontal and vertical alignments of two-lane rural highways.

2021 ◽  
Author(s):  
Qing Chong You
Keyword(s):  
Associated Factors ◽  
Negative Binomial ◽  
Horizontal Curve ◽  
Rural Highways ◽  
Vehicle Accidents ◽  
Horizontal Curves ◽  
Curve Radius ◽  
Grade Increase ◽  
Minimum Ratio ◽  
Successful Predictor

This study investigates the safety effects of combined horizontal and vertical alignments using accident occurrences on two-lane rural highways in Washington. Eight statistical models were developed to establish the relationships between vehicle accidents and their associated factors for eight combinations of alignments by the Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. Three selected models were validated. The findings show that degree of curvature is the most successful predictor for horizontal curves combined with vertical alignments. A minimum ratio of 25 of vertical curve radius to horizontal curve radius is recommended for a curve with radius of smaller than 6000 ft (or 1830 m). Vertical curves have relatively little influence on accident occurrences at horizontal tangents. The grade value and length of a grade increase accident occurrences when a horizontal curve or tangent is on a grade. A smaller curve should be avoided introducing at a steep grade.

scholarly journals Applying a Correlated Random Parameters Negative Binomial Lindley Model to Examine Crash Frequency Along Highway Tunnels in China

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 213473-213488
Author(s):  
Feng Tang ◽  
Xinsha Fu ◽  
Mingmao Cai ◽  
Yue Lu ◽  
Shiyu Zhong ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Random Parameters ◽  
Crash Frequency

Safety Evaluation of Geometric Design Criteria: Horizontal Curve Radius and Side Friction Demand on Rural, Two-Lane Highways

2019 ◽  
Vol 2673 (3) ◽  
pp. 516-525
Author(s):  
Scott Himes ◽  
Richard J. Porter ◽  
Ian Hamilton ◽  
Eric Donnell
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Geometric Design ◽  
Design Criteria ◽  
Speed Limit ◽  
Horizontal Curve ◽  
Mass Model ◽  
Design Speed ◽  
Side Friction ◽  
Curve Radius

AASHTO’s A Policy on Geometric Design of Highways and Streets, 6th Edition, provides design criteria for horizontal curve elements based on the point-mass model. The model equates the centripetal force needed to navigate a horizontal curve of a specific radius traveling at the design speed to the combination of superelevation rate and side friction needed to achieve that force. Few researchers have examined the safety impacts of horizontal curve radius, superelevation rate, and design speed through crash-based research. None of the research reviewed included the effects of design speed or superelevation rate in the crash modification factors (CMFs) or functions. This research explored these factors using a negative binomial regression modeling approach based on data collected from the SHRP 2 RID 2.0 for 889 horizontal curves on rural two-lane highways in Indiana and Pennsylvania, which resulted in roadway departure crash modification functions for horizontal curve radius and side friction demand. The crash modification function for side friction demand includes an interactive component of horizontal curve radius and speed and a direct effect of superelevation rate on roadway departure crashes. The results showed that roadway departure crashes are expected to increase for decreasing curve radius, increasing posted speed limit, and decreased superelevation rate. Furthermore, curve-related CMFs were sensitive to the curve radii used in their development. CMFs developed from curves with larger radii tended to result in larger CMFs. Sample applications are provided for computing the effects of changing the horizontal curve radius, posted speed limit, or both on proposed alternatives.

A Correlated Random Parameters Model with Heterogeneity in Means to Account for Unobserved Heterogeneity in Crash Frequency Analysis

2020 ◽  
Vol 2674 (7) ◽  
pp. 312-322
Author(s):  
Xiaoyan Huo ◽  
Junqiang Leng ◽  
Qinzhong Hou ◽  
Hao Yang
Keyword(s):  
Frequency Analysis ◽  
Negative Binomial ◽  
Unobserved Heterogeneity ◽  
Good Alternative ◽  
Omitted Variables ◽  
Random Parameters ◽  
Safety Factors ◽  
Crash Frequency ◽  
Study Results ◽  
Different Sources

Unobserved heterogeneity induced by omitted variables is a major challenge in developing reliable road safety models. In recent years, the random parameters negative binomial (RPNB) model has been used frequently in crash frequency analysis to account for unobserved heterogeneity. However, the majority of past studies of the RPNB model assumed that there was no correlation between different sources of unobserved heterogeneity, which is not always true given the complex interactions of safety factors. Compared with the RPNB model, a more flexible random parameters model that is the correlated random parameters negative binomial with heterogeneity in means (CRPNBHM) model was proposed in this study. Results indicate that the CRPNBHM model could not only capture the otherwise unobserved heterogeneity, but also track the underlying correlation among different sources of unobserved heterogeneity, thus outperforming the RPNB model. In addition, new insights into the interactions of safety factors (e.g., the joint safety effects of heavy trucks and pavement rutting depth) were obtained from the CRPNBHM model and these are expected to be beneficial in developing effective safety countermeasures. Results from this study demonstrated the CRPNBHM model to be a good alternative for crash frequency analysis, particularly when unobserved heterogeneity was detected.

Sign in / Sign up

Export Citation Format

Share Document