Safety performance functions for low-volume rural minor collector two-lane roadways

Das, Subasish; Tsapakis, Ioannis; Khodadadi, Ali

doi:10.1016/j.iatssr.2021.02.004

Cited by 14 publications

(2 citation statements)

References 12 publications

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“…The most common approach for safety performance measurement of crashes and detecting high-risk crash sites is analyzing historical crash data. Crash data analyses can be categorized into two types: crash frequency analysis and crash severity analysis [14]. The general approach of crash modeling is to associate the historical crash events with other variables, such as roadway geometric properties, traffic characteristics, environmental variables, crash-associated vehicle attributes, and motorist characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring Crowdsourced Hard—Acceleration and Braking Event Data for Evaluating Safety Performance of Low-Volume Rural Highways in Iowa

Mahmud¹,

Day²

2023

JTTs

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There are over four million miles of two-lane roadways across the United States, of which a substantial portion is low-volume roads (LVR). Traditionally, most traffic safety efforts and countermeasures focus on high-volume high-crash urban locations. This is because LVRs cover an extensive area, and the rarity of crashes makes it challenging to use crash data to monitor the safety performance of LVRs regularly. In addition, obtaining up-to-date roadway information, such as pavement or shoulder conditions of an extensive LVR network, can be exceptionally difficult. In recent times, crowdsourced hard-acceleration and braking event data have become commercially available, which can provide precise geolocation information and can be readily acquired from different vendors. The present paper examines the potential use of this data to identify opportunities to monitor the safety of LVRs. This research examined approximately 12 million hard-acceleration and hardbraking events over a 3-months period and 26,743 crashes, including 9373 fatal injuries over the past 5-year period. The study found a moderate correlation between hard acceleration/hard-braking events with historical crash events. This study conducted a hot spot analysis using hard-acceleration/ hard-braking and crash datasets. Hotspot analysis detected spatial clusters of high-risk crash locations and detected 848 common high-risk sites. Finally, this paper proposes a combined ranking scheme that simultaneously considers historical crash events and hard-acceleration/hard-braking events. The research concludes by suggesting that agencies can potentially use the hardacceleration and hard-braking event dataset along with the historical crash dataset to effectively supervise the safety performance of the vast network of LVRs more frequently.

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Section: Literature Reviewmentioning

confidence: 99%

Exploring Crowdsourced Hard—Acceleration and Braking Event Data for Evaluating Safety Performance of Low-Volume Rural Highways in Iowa

Mahmud¹,

Day²

2023

JTTs

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“…In the current approach to the EB adjustment of SPFs, the study region from which the data are collected is assumed to be known, which is typically an entire state or a district. Das et al developed new rules-based SPFs for low-volume rural local roadways on the basis of segment length and AADT as the most contributing factors and proposed a method to improve the model accuracy in terms of R-square and a cumulative residual (CURE) plot [33]. However, choosing a study region too large or too small can cause issues with the validity of the HSM-specified model form (goodness of fit) or the overdispersion parameter.…”

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

Sustainability

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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 the assumption of violation identification. This study, part of an FDOT-sponsored project, investigates the established statistical diagnostic tests to identify model violations and proposes a novel approach to determine the optimal spatial regions for empirical Bayes adjustment. This adjustment aligns HSM SPFs with regression assumptions. This 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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Evaluating Geometric Design Characteristics of Two-Lane Two-Way Rural Roads on Crash Frequencies Occurrences

Mirzahossein

Adibi

Khishdari

et al. 2023

Iran J Sci Technol Trans Civ Eng

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Safety performance functions for low-volume rural minor collector two-lane roadways

Cited by 14 publications

References 12 publications

Exploring Crowdsourced Hard—Acceleration and Braking Event Data for Evaluating Safety Performance of Low-Volume Rural Highways in Iowa

Exploring Crowdsourced Hard—Acceleration and Braking Event Data for Evaluating Safety Performance of Low-Volume Rural Highways in Iowa

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

Evaluating Geometric Design Characteristics of Two-Lane Two-Way Rural Roads on Crash Frequencies Occurrences

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