Using Crash Modification Factors to Appraise the Safety Effects of Pedestrian Countdown Signals for Drivers

Kitali, Angela E.; Sando, Thobias; Castro, A.P. Werneck De; Kobelo, Doreen; Mwakalonge, Judith

doi:10.1061/jtepbs.0000130

Cited by 7 publications

(5 citation statements)

References 15 publications

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“…Crash modification factors (CMFs) are employed to adjust for the influences of sitespecific geometric design elements (e.g., lane width, shoulder width, horizontal curves) and traffic control features (e.g., automated speed enforcement). These adjustments are made to estimate accident frequencies for facilities that exhibit variations in design parameters from the baseline conditions upon which the safety performance functions (SPFs) were originally developed [20]. SPFs were established for roadway facilities based on fundamental criteria, including the number of lanes, lane widths, median widths, lighting conditions, and other relevant factors.…”

Section: Literature Reviewmentioning

confidence: 99%

Determination of Optimal Spatial Sample Sizes for Fitting Negative Binomial-Based Crash Prediction Models with Consideration of Statistical Modeling Assumptions

Koloushani,

Abazari,

Vanli

et al. 2023

Preprint

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Transportation authorities aim to boost road safety by identifying risky locations and applying suitable safety measures. The Highway Safety Manual (HSM) is a vital resource for US transportation professionals, aiding in the creation of Safety Performance Functions (SPFs), which are predictive models for crashes. These models rely on Negative Binomial distribution-based regression and misinterpreting them due to unmet statistical assumptions can lead to erroneous conclusions, including inaccurately assessing crash rates or missing high-risk sites. The Florida Department of Transportation (FDOT) has introduced context classifications to HSM SPFs, complicating assumption violation identification. This study, part of an FDOT-sponsored project, investigates established statistical diagnostic tests to identify model violations and proposes a novel approach to determine optimal spatial regions for Empirical Bayes adjustment. This adjustment aligns HSM-SPFs with regression assumptions. The study employs a case study involving Florida roads. Results indicate that a 20-mile radius offers an optimal spatial sample size for modeling crashes of all injury levels, ensuring accurate assumptions. For severe injury crashes, which are less frequent and harder to predict, a 60-mile radius is suggested to fulfill statistical modeling assumptions. This methodology guides FDOT practitioners in assessing the conformity of HSM-SPFs with intended assumptions and determining appropriate region sizes.

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Section: Literature Reviewmentioning

confidence: 99%

Determination of Optimal Spatial Sample Sizes for Fitting Negative Binomial-Based Crash Prediction Models with Consideration of Statistical Modeling Assumptions

Koloushani,

Abazari,

Vanli

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Crash frequencies were higher for commercial-type areas and intersections with higher speed limits (above 30 mph). The researchers found that PCSs associate with reductions of all type of crashes by between 4.6% and 8.8% ( 18 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The literature review found multiple applications that demonstrate the usefulness of both approaches of interest for this research. When large databases are available, the preference seems to be for disaggregating the data by crash severities and modeling the frequency of each subset of crashes separately ( 18 , 20 , 21 ). However, some researchers seem to prefer the development and use of SDFs even on larger datasets ( 2 , 3 , 16 ).…”

Section: Literature Reviewmentioning

confidence: 99%

A Comparative Analysis on Performance of Severe Crash Prediction Methods

Avelar

Dixon

Ashraf

2018

Transportation Research Record

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The objective of this paper is to compare the performance and tradeoffs between two alternative analysis methods for developing crash prediction models for severe crashes: a direct estimation of severe crashes using frequency models, and an indirect but popular approach of combining frequency of total crashes models and some form of severity distribution functions (SDFs). The researchers conducted a comprehensive comparison of these modeling methods to illustrate the strengths and weaknesses of each alternative, and to inform future research that intends to develop such models. An examination of the theoretical characteristics of the modeling approach is presented and discussed. The performance of the two modeling alternatives is compared using two different datasets. The results of those comparisons showed very similar performances by both techniques. Finally, a sensitivity analysis is presented to explore how the performance of these techniques vary by degree of dispersion and observed correlation levels of total and severe injury crashes (KAB; injury scale in which K = fatal [killed], A = incapacitating injury, B = nonincapacitating injury) with potential explanatory variables. The results from these analyses tended to favor the use of SDFs in combination with total crashes safety performance functions (SPFs), as the prediction tended to show reduced dispersion under most conditions. However, performance of the KAB SPF model outperformed the combination of SDF and SPF for total crashes when KAB and non-KAB crashes had a common predictor but with effects in opposite directions.

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“…In addition, studies have suggested that pedestrians prefer countdown timer information ''because it gives them more information and lets them make better crossing decisions (15).'' The pedestrian countdown timers were also found to improve driver safety (16,17). Drivers also use pedestrian countdown timers to make informed decisions when approaching the intersection (9,11,18,19).…”

Section: Introductionmentioning

confidence: 99%

“…Several studies have reported a reduction in pedestrian–motor vehicle conflicts and improved pedestrian safety as a result of the pedestrian countdown timer installation ( 7 – 14 ). In addition, studies have suggested that pedestrians prefer countdown timer information “because it gives them more information and lets them make better crossing decisions ( 15 ).” The pedestrian countdown timers were also found to improve driver safety ( 16 , 17 ). Drivers also use pedestrian countdown timers to make informed decisions when approaching the intersection ( 9 , 11 , 18 , 19 ).…”

Section: Introductionmentioning

confidence: 99%

User Comprehension of Bicycle Signal Countdown Timers

Cobb

Monsere

Hurwitz

et al. 2023

Transportation Research Record: Journal of the Transportation R

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For a person on a bicycle at signalized intersections, trail crossings, or midblock locations, knowing how long they must wait to receive a green indication is valuable information. In the international context, this information is often provided by small, nearside bicycle signal heads that contain a countdown display that visually conveys the amount of waiting time. This paper presents the results of research to investigate the comprehension of bicycle countdown timer displays in the U.S. context. The study conducted an online survey to analyze the understanding and preference of three alternative bicycle countdown timer displays. Respondents were recruited by two recruitment methods: mailed postcards (568 responses) and social media ads (772 responses). A countdown timer with circular disappearing dots was then installed at an intersection in Portland, OR, and an intercept survey was conducted of users (29 responses). For both surveys, comprehension rates were established by coding an open-ended response to a question about the display's intended meaning. The surveys found that the bicycle signal countdown displays were intuitive, and the intended meaning was fully understood by over 60% of online survey respondents and 52% of the intercepted bicyclists. Partial comprehension increased to over 70% and 97% of those intercepted, respectively, which would result in safe user interpretation. A countdown timer may also improve the waiting experience for stopped bicyclists, as 70% of respondents strongly or somewhat agreed that they would feel better about waiting at an intersection if a bicycle countdown timer was present.

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Using Crash Modification Factors to Appraise the Safety Effects of Pedestrian Countdown Signals for Drivers

Cited by 7 publications

References 15 publications

Determination of Optimal Spatial Sample Sizes for Fitting Negative Binomial-Based Crash Prediction Models with Consideration of Statistical Modeling Assumptions

Determination of Optimal Spatial Sample Sizes for Fitting Negative Binomial-Based Crash Prediction Models with Consideration of Statistical Modeling Assumptions

A Comparative Analysis on Performance of Severe Crash Prediction Methods

User Comprehension of Bicycle Signal Countdown Timers

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