Identifying Pedestrian High-Crash Locations as Part of Florida’s Highway Safety Improvement Program: A Systematic Approach

2003 ◽  
Vol 1828 (1) ◽  
pp. 83-88 ◽  
Author(s):  
Elio R. Espino ◽  
Javier S. Gonzalez ◽  
Albert Gan
Keyword(s):  
Goodness Of Fit ◽  
Highway Safety ◽  
Dade County ◽  
Goodness Of Fit Test ◽  
Improvement Program ◽  
Crash Data ◽  
Safety Improvement ◽  
Florida Department ◽  
Pedestrian Crashes ◽  
High Crash Locations

From 1997 to 2001, pedestrian fatalities represented 25.9% (2,065 fatalities) of all traffic fatalities in Florida. The latest available statewide crash data from the Florida Department of Highway Safety and Motor Vehicles reveals 8,487 pedestrian crashes, resulting in 510 deaths and 7,894 injuries, in 2001. However, a methodology is not currently available to identify pedestrian high-crash locations in Florida as part of the Highway Safety Improvement Program (HSIP). A study was conducted to provide the framework for the systematic identification of pedestrian high-crash locations on the state highway system as part of the HSIP. The study methodology uses the Poisson distribution to determine abnormally high pedestrian crash frequencies in a year for 1-mi roadway segments. Four-lane and six-lane divided roadways with continuous sidewalks on both sides of the road in Miami-Dade County were included. The crash data, the latest available from the crash database of the Florida Department of Transportation, correspond to the years 1997, 1998, and 1999. A χ2 goodness-of-fit test was performed to determine how well the data could be modeled by a Poisson process. The goodness-of-fit test was significant at the 2.5% level for the 1999 data, at the 10% level for the 1998 data, and less than 1% for the 1997 data. With a confidence level of at least 90%, a pedestrian crash frequency of three crashes in a 1-mi segment was found to be abnormally high for the fourlane divided facilities. For the six-lane divided facilities, four pedestrian crashes per 1-mi segment were established as the threshold value. From these threshold values, 22 1-mi segments were identified as pedestrian high-crash locations in Miami-Dade County for 1999.

Tools to Identify Safety Issues for a Corridor Safety-Improvement Program

2000 ◽  
Vol 1717 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Jerome P. Breyer
Keyword(s):  
Relational Databases ◽  
Safety Evaluation ◽  
Highway Safety ◽  
New Paradigm ◽  
Safety Hazards ◽  
Improvement Program ◽  
Satellite Systems ◽  
Safety Issues ◽  
Advanced Technologies ◽  
Safety Improvement

The Arizona Department of Transportation (ADOT) recognizes that a new paradigm in highway safety evaluation was brought about by the advent of advanced technologies such as photo log, geographic information systems (GIS), and global-positioning satellite systems. Whereas these technologies are known to serve distinct singular purposes in a highway agency, ADOT has endeavored to explore the possibilities of integrating these technologies for the purpose of providing an all-encompassing perspective of crash history and roadside characteristics in a multimedia display of GIS maps and related photo imagery. The research provides the account of an analytic tool-development process aimed at improving the recognition of highway safety hazards. These hazards might otherwise be apparent if not for the relative complexity of existing relational databases and spatial GIS infrastructure at ADOT. Previous methods of mining data from the ADOT crash databases were limited in functionality as well as in reliability. By promoting the “visualization” of highway safety conditions, the advanced technologies open a wealth of new opportunities in identifying problematic roadside conditions and crash histories. This is expected to lead to an improved economy of implementing safety improvements that are designed properly to mitigate the “real” conditions that can be identified. The research is a companion to the larger, FHWA-sponsored research into establishing a corridor safety-improvement program for Arizona (FHWA Report FHWA-AZ 98-458).

A Novel Technique to Identify Hot Zones for Active Commuters’ Crashes

2018 ◽  
Vol 2672 (38) ◽  
pp. 266-276 ◽  
Author(s):  
Ahmed Osama ◽  
Tarek Sayed ◽  
Emanuele Sacchi
Keyword(s):  
Mahalanobis Distance ◽  
Empirical Bayes ◽  
Negative Binomial ◽  
Active Transportation ◽  
Spatial Effects ◽  
Distance Method ◽  
Crash Data ◽  
Safety Improvement ◽  
Pedestrian Crashes ◽  
Psi Method

This paper presents an approach to identify and rank accident-prone (hot) zones for active transportation modes. The approach aims to extend the well-known empirical Bayes (EB) potential for safety improvement (PSI) method to cases where multiple crash modes are modeled jointly (multivariate modeling). In this study, crash modeling was pursued with a multivariate model, incorporating spatial effects, using the full Bayes (FB) technique. Cyclist and pedestrian crash data for the City of Vancouver (British Columbia, Canada) were analyzed for 134 traffic analysis zones (TAZs) to detect active transportation hot zones. The hot zones identification (HZID) process was based on the estimation of the Mahalanobis distance, which can be considered an extension to the PSI method in the context of multivariate analysis. In addition, a negative binomial model was developed for cyclist and pedestrian crashes, where the EB PSI for each mode crash was quantified. The cyclist and pedestrian PSIs were combined to detect active transportation hot zones. Overall, the Mahalanobis distance method is found to outperform the PSI method in terms of consistency of results; and discrepancy is observed between the hot zones identified using both approaches.

Indian Reservation Safety Improvement Program

2013 ◽  
Vol 2364 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Debbie S. Shinstine ◽  
Khaled Ksaibati
Keyword(s):  
Technical Assistance ◽  
The United States ◽  
Improvement Program ◽  
Indian Reservation ◽  
Assistance Program ◽  
Crash Data ◽  
Fatal Crashes ◽  
Safety Improvement ◽  
Technical Assistance Program ◽  
Tribal Lands

The need to reduce fatal and injury crashes on tribal lands has been recognized for years. The United States has realized a decline in fatal crashes over the past several years, but fatal crashes continue to increase on tribal lands. Little progress has been made in improving safety on tribal lands. Limited resources, lack of coordination across jurisdictions, the rural nature of many of the roadways, and lack of crash data have made it difficult for tribes to implement an effective safety improvement program. A methodology that can address these challenges is presented in this paper. The proposed methodology has been implemented successfully in the Wind River Indian Reservation in Wyoming. Collaboration among safety stakeholders—state departments of transportation, tribal leadership, the Local Technical Assistance Program, the Tribal Technical Assistance Program, the Bureau of Indian Affairs, and local and tribal law enforcement—is key to the success of such a process.

Examining Fatal Crash Reductions by First Harmful Events since the Introduction of the Federal Highway Safety Improvement Program

2013 ◽  
Vol 2364 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Kun-Feng Wu ◽  
Scott C. Himes ◽  
Martin T. Pietrucha
Keyword(s):  
Fixed Effects ◽  
Motor Vehicle ◽  
Spillover Effects ◽  
Highway Safety ◽  
Motor Vehicles ◽  
Improvement Program ◽  
Fatal Crash ◽  
Fatal Crashes ◽  
Safety Improvement ◽  
Federal Highway

The federal Highway Safety Improvement Program (HSIP) has been associated with the reduction in fatal crashes since 2006, but the reasons for the reduction remain largely unknown. This paper examines the reduction in fatal crashes in terms of different types of first harmful events that can provide insight into crash causes and prevention strategies. In this study, fatal crashes were categorized into four types: overturn, collision with motor vehicle in transport, collision with fixed object, and collision with nonmotorist. Fixed-effects and mixed-effects Poisson models were used to estimate the magnitudes of fatal crash reduction by first harmful events for each state. Fatal crashes due to collisions with nonmotorists and motor vehicles in transport have been reduced by 10% and 5.3%, respectively, compared with the 2001 to 2005 period. Fatal crashes due to overturn and collision with a fixed object decreased in some states but remained unchanged or increased in other states. Nevertheless, the numbers of national fixed-object and overturn fatal crashes have been reduced by 3% and 0.7%, respectively, as a whole. This study also investigated possibilities that could be associated with the magnitudes of the reductions, for example, the different traffic laws among states. It was found that although different safety improvement projects were implemented to target the various types of crashes, the improvements were also likely to be beneficial to other crash types. These are referred to as spillover effects. Nationally, fatal crashes have decreased since the introduction of the HSIP partly because of the reduction in fatal crashes due to collisions with nonmotorists and motor vehicles in transport and partly because of spillover effects.

scholarly journals Safety on Heavily Trafficked Urban Motorways in Relation to Traffic State

2020 ◽  
Vol 31 (1) ◽  
pp. 51-65 ◽  
Author(s):  
Elizabeth Hovenden ◽  
Hendrik Zurlinden ◽  
John Gaffney
Keyword(s):  
Goodness Of Fit ◽  
Intelligent Transport System ◽  
Vehicle Speed ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Crash Data ◽  
Traffic State ◽  
Arterial Road ◽  
Depth Analysis ◽  
Urban Arterial

Motorways represent seven per cent of the urban arterial road network in Melbourne yet carry 40 per cent of the urban arterial road travel in terms of vehicle kilometres travelled and this percentage is growing. The number of casualty crashes on metropolitan Melbourne motorways has increased over the decade at a faster rate than on other urban roads in metropolitan Melbourne. Police crash reports more often attribute crash cause to traffic conditions and vehicle interactions rather than infrastructure. As urban motorways are generally built to the highest standards, a new way of looking at motorway safety is needed. This led to the formulation of a hypothesis that the dynamics of the traffic flow are a significant contributor to casualty crashes on urban motorways. To test this hypothesis, in-depth analysis was undertaken on metropolitan Melbourne motorways. Crash data was linked to traffic data including vehicle occupancy (a proxy measure for density), vehicle speed and flow. Occupancy was used to categorise the ‘traffic states’ ranging from free flow to flow breakdown (congestion). Applying a Chi Square Goodness of Fit Test to the linked showed a statistically significant association between traffic state and crashes, with a higher than expected crashes in the traffic states where flow breakdown is relatively certain or has occurred. The results of this analysis can be used to improve safety on urban motorways through the development of Intelligent Transport System strategies to keep the motorway operating at conditions that minimise flow breakdown risk.

scholarly journals PENENTUAN SIMPANG BERSINYAL RAWAN KECELAKAAN UNTUK IDENTIFIKASI AWAL TERHADAP POTENSI RED LIGHT RUNNING (RLR) DI BANDA ACEH

2019 ◽  
Vol 2 (1) ◽  
pp. 21
Author(s):  
Sofyan M. Saleh ◽  
Sugiarto Sugiarto ◽  
Endang Handayani
Keyword(s):  
Traffic Accidents ◽  
Red Light ◽  
Highway Safety ◽  
Improvement Program ◽  
Red Light Running ◽  
Highway Safety Manual ◽  
Safety Improvement ◽  
Depth Study ◽  
Accident Data ◽  
Equivalent Property

Red Light Running (RLR) is the leading cause of traffic accidents at signal intersections in various countries, including Indonesia. The main reason is the existence of conflicts caused by drivers' behavioral factors who are not obedient or understand about signaling operations. RLR is the most dangerous driver's behavior in a signal intersection, where the driver fails to comply with signaling rules at the intersection so that the conflict occurs. To assess the behavior of the RLR, the first step is to identify the signaled intersections that are most prone to accidents. This is needed to eliminate the location of study or handling due to limited time and costs. The methodology used to determine accident-prone locations is based on the Highway Safety Improvement Program in the Highway Safety Manual (HSM, 2010), namely the planning component consisting of data collection and identification of accident-prone areas in signal intersections. Using accident data of 2013-2015, and by combining three methods of analysis such as frequency, accident rate, and equivalent property damage only methods, then three most accident-prone signal intersections are determined and prioritized for in-depth study of RLR behavior analysis. Red Light Running (RLR) adalah penyebab utama kecelakaan lalu lintas pada simpang bersinyal di berbagai negara termasuk Indonesia. Penyebab utamanya adalah adanya konflik yang diakibatkan oleh faktor perilaku pengemudi yang tidak patuh atau paham tentang pengoperasian persinyalan. RLR merupakan perilaku pengemudi yang paling berbahaya pada simpang bersinyal, dimana pengemudi gagal mematuhi peraturan persinyalan pada simpang sehingga konflik terjadi. Untuk mengkaji perilaku pada RLR perlu dilakukan langkah awal yaitu identifikasi simpang bersinyal yang paling rawan terhadap kecelakaan. Hal ini diperlukan untuk mengeliminasi lokasi kajian atau penanganan akibat keterbatasan waktu dan biaya. Metodologi yang digunakan untuk penentuan lokasi rawan kecelakaan dilakukan mengacu pada Highway Safety Improvement Program di dalam Highway Safety Manual (HSM, 2010), yaitu planning component yang terdiri dari pengumpulan data dan identifikasi daerah rawan kecelakaan pada simpang bersinyal. Menggunakan data kecelakaan tahun 2013-2015 dengan mengombinasikan tiga metode analisis yaitu metode frekuensi, tingkat kecelakaan dan ekuivalensi kerugian harta benda (EPDO) ditentukan tiga simpang bersinyal yang paling rawan kecelakaan dan diprioritaskan untuk dilakukan kajian mendalam terhadap perilaku pelanggaran RLR.

scholarly journals Detecting Risk Factors of Road Work Zone Crashes from the Information Provided in Police Crash Reports: The Case Study of Portugal

Safety ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 12
Author(s):  
Bertha Santos ◽  
Valdemiro Trindade ◽  
Cláudia Polónia ◽  
Luís Picado-Santos
Keyword(s):  
Risk Factors ◽  
Statistical Analysis ◽  
Police Officers ◽  
Goodness Of Fit ◽  
Significant Risk ◽  
Work Zone ◽  
Probit Regression ◽  
Goodness Of Fit Test ◽  
Crash Data ◽  
Road Work

Several studies have shown that European police crash reports provide different detail degrees of work zone crash-related data. In this sense, the present study aims to verify the possibility of identifying significant risk factors involved in the occurrence of road work zone crashes with casualties, based on the official data usually available, through a descriptive, binary logistic, and probit regression statistical analysis. To accomplish the analysis, a total of 2597 police-reports related to 1767 Portuguese work zone crashes that occurred during the 2013–2015 period were considered and binary logistic and probit regression models were estimated by the main type of crash, contributing factor, and driver age group. Fifteen explanatory variables, selected based on the literature review and crash data provided in police crash reports, were considered in the analysis. The results obtained for the estimated coefficients and goodness-of-fit test values were found very similar for both link functions (logit and probit) and it was possible to identify risk factors. The modeling results pointed to excessive speed, disregard for vertical signs, luminosity, intersections, and motorcycle and heavy vehicle involvement as the most significant risk factors. Given the results, it is possible to conclude that binary logistic regression can be used in the statistical analysis of the available police official work zone crash data to identify and get some insight into the risk factors involved in work zone crashes. Data analysis also revealed the need to promote adequate and complete crash report filling by police officers. While police crash reports are not revised and standardized to incorporate more detailed work zone crash information, this approach can be used to support a more efficient road operation decision making and the review of some aspects related to work zone layout design.

Safety Performance Functions of Low-Volume Roadways

2019 ◽  
Vol 2673 (12) ◽  
pp. 798-810 ◽  
Author(s):  
Subasish Das ◽  
Ioannis Tsapakis ◽  
Songjukta Datta
Keyword(s):  
High Volume ◽  
Highway Safety ◽  
Safety Performance ◽  
Improvement Program ◽  
Crash Data ◽  
Safety Issues ◽  
Safety Performance Functions ◽  
Traffic Volumes ◽  
Low Volume ◽  
State And Local

The Fixing America’s Surface Transportation Act (FAST Act) mandates a Highway Safety Improvement Program (HSIP) for all states that “emphasizes a data-driven, strategic approach to improving highway safety on all public roads that focuses on performance.” To determine the predicted crashes on a specific roadway facility, the most convenient and widely used tool is the first edition of Highway Safety Manual (HSM), which provides predictive models [known as safety performance functions (SPFs)] of crash frequencies for different roadways. Low-volume roads (LVRs) are defined as roads located in rural or suburban areas with daily traffic volumes of less than or equal to 400 vehicles per day (vpd). LVRs cover a significant portion of the roadways in the U.S. While much work has been done to develop SPFs for high-volume roads, less effort has been devoted to LVR safety issues. This study used 2013–2017 traffic count, and roadway network and crash data from North Carolina to develop six SPFs for three LVRs, which can be used to predict total crashes, as well as fatal and injury crashes. This study also performed a sensitivity analysis to show the influence of traffic volumes on expected crash frequencies. The SPFs developed in this study can provide guidance to state and local agencies with the means to quantify safety impacts on LVR networks.

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