scholarly journals Calibration of highway safety manual predictive models and validation of safety performance funtions for canadian urban/suburban intersections

2021 ◽  
Author(s):  
Shahzad Faisal
Keyword(s):  
Predictive Models ◽  
Safety Performance ◽  
Local Data ◽  
Performance Function ◽  
Safety Performance Function ◽  
Highway Safety Manual ◽  
Related Aspect ◽  
Crash Types ◽  
The City ◽  
Collision Models

In this research, the HSM predictive models for collisions on urban/suburban arterials are calibrated for collision data from the City of Toronto. It has been found that the use of calibration factors for applying HSM models to Toronto intersection data is not appropriate. New collision models are therefore developed by using local data. The HSM and Toronto models are then calibrated to City of Edmonton intersection collision data to determine whether it is better to calibrate HSM models for a Canadian jurisdiction or models from another Canadian jurisdiction. A related aspect of the research is the investigation of models for crash types. There is no safety performance function (SPF) available in the HSM to predict rear end collisions. Instead, rear end collisions are estimated as a proportion of predicted multivehicle collisions. To overcome this deficiency, Toronto data are used in the estimation of models for rear end collisions.

scholarly journals Calibration of highway safety manual predictive models and validation of safety performance funtions for canadian urban/suburban intersections

2021 ◽  
Author(s):  
Shahzad Faisal
Keyword(s):  
Predictive Models ◽  
Safety Performance ◽  
Local Data ◽  
Performance Function ◽  
Safety Performance Function ◽  
Highway Safety Manual ◽  
Related Aspect ◽  
Crash Types ◽  
The City ◽  
Collision Models

In this research, the HSM predictive models for collisions on urban/suburban arterials are calibrated for collision data from the City of Toronto. It has been found that the use of calibration factors for applying HSM models to Toronto intersection data is not appropriate. New collision models are therefore developed by using local data. The HSM and Toronto models are then calibrated to City of Edmonton intersection collision data to determine whether it is better to calibrate HSM models for a Canadian jurisdiction or models from another Canadian jurisdiction. A related aspect of the research is the investigation of models for crash types. There is no safety performance function (SPF) available in the HSM to predict rear end collisions. Instead, rear end collisions are estimated as a proportion of predicted multivehicle collisions. To overcome this deficiency, Toronto data are used in the estimation of models for rear end collisions.

How the choice of safety performance function affects the identification of important crash prediction variables

2016 ◽  
Vol 88 ◽  
pp. 1-8 ◽  
Author(s):  
Ketong Wang ◽  
Jenna K. Simandl ◽  
Michael D. Porter ◽  
Andrew J. Graettinger ◽  
Randy K. Smith
Keyword(s):  
Safety Performance ◽  
Performance Function ◽  
Crash Prediction ◽  
Safety Performance Function

scholarly journals Segmentation Effect on the Transferability of International Safety Performance Functions for Rural Roads in Egypt

Safety ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 43
Author(s):  
Sania Reyad Elagamy ◽  
Sherif M. El-Badawy ◽  
Sayed A. Shwaly ◽  
Zaki M. Zidan ◽  
Usama Elrawy Shahdah
Keyword(s):  
Constant Term ◽  
Safety Performance ◽  
Likelihood Method ◽  
Percentage Error ◽  
Segmentation Method ◽  
Local Data ◽  
Absolute Deviation ◽  
Rural Roads ◽  
Safety Performance Function ◽  
Segmentation Approach

This paper examines the transferability of the Safety Performance Function (SPF) of the Highway Safety Manual (HSM) and other 10 international SPFs for total crashes on rural multi-lane divided roads in Egypt. Four segmentation approaches are assessed in the transferability of the international SPFs, namely: (1) one-kilometer segments (S1); (2) homogenous sections (S2); (3) variable segments with respect to the presence of curvatures (S3); and (4) variable segments with respect to the presence of both curvatures and U-turns (S4). The Mean Absolute Deviation (MAD), Mean Prediction Bias (MPB), Mean Absolute Percentage Error (MAPE), Pearson χ2 statistic, and Z-score parameters are used to evaluate the performance of the transferred models. The overdispersion parameter (k) for each transferred model and each segmentation approach is recalibrated using the local data by the maximum likelihood method. Before estimating the transferability calibration factor (Cr), three methods were used to adjust the local crash prediction of the transferred models, namely: (1) the HSM default crash modification factors (CMFs); (2) local CMFs; and (3) recalibrating the constant term of the transferred model. The latter method is found to outperform the first two methods. Besides, the results show that the segmentation method would affect the performance of the transferability process. Moreover, the Italian SPFs based on the S1 segmentation method outperforms the HSM and all of the investigated international SPFs for transferring their models to the Egyptian rural roads.

scholarly journals Rural two-lane two-way three-leg and four-leg stop-controlled intersections: predicting road safety effects

2017 ◽  
Vol 12 (2) ◽  
pp. 117-126 ◽  
Author(s):  
Salvatore Antonio Biancardo ◽  
Francesca Russo ◽  
Daiva Žilionienė ◽  
Weibin Zhang
Keyword(s):  
Estimating Equation ◽  
Safety Performance ◽  
Crash Frequency ◽  
Performance Function ◽  
Left Turn ◽  
Explanatory Variables ◽  
Crash Data ◽  
Safety Performance Function ◽  
Lane Width ◽  
Residuals Analysis

The study focused on grade-level rural two-lane two-way three-leg and two-lane two-way four-leg stop-controlled intersections located in the flat area with a vertical grade of less than 5%. The goal is to calibrate one Safety Performance Function at these intersections by implementing a Generalized Estimating Equation with a binomial distribution and compare to the results with yearly expected crash frequencies by using models mainly refered to the scientific literature. The crash data involved 77 two-lane two-way intersections, of which 25 two-lane two-way three-leg intersections are without a left-turn lane (47 with left-turn lane), 5 two-lane two-way four-leg intersections without a left-turn lane (6 with a left-turn lane). No a right-turn lane is present on the major roads. Explanatory variables used in the Safety Performance Function are the presence or absence of a left-turn lane, mean lane width including approach lane and a left-turn lane width on the major road per travel direction, the number of legs, and the Total Annual Average Daily Traffic entering the intersection. The reliability of the Safety Performance Function was assessed using residuals analysis. A graphic outcome of the Safety Performance Function application has been plotted to easily assess a yearly expected crash frequency by varying the Average Annual Daily Traffic, the number of legs, and the presence or absence of a left-turn lane. The presence of a left-turn lane significantly reduces the yearly expected crash frequency values at intersections.

scholarly journals Prediction of motorcyclist traffic crashes in Cartagena (Colombia): development of a safety performance function

2021 ◽  
Author(s):  
Holman Ospina-Mateus ◽  
Leonardo Augusto Quintana Jiménez ◽  
Francisco J. Lopez-Valdes ◽  
Shib Sankar Sana
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Road Traffic ◽  
Negative Binomial Regression ◽  
Safety Performance ◽  
Traffic Crashes ◽  
Performance Function ◽  
Safety Performance Function ◽  
Significant Factors

Motorcyclists account for more than 380,000 deaths annually worldwide from road traffic accidents. Motorcyclists are the most vulnerable road users worldwide to road safety (28% of global fatalities), together with cyclists and pedestrians. Approximately 80% of deaths are from low- or middle-income countries. Colombia has a rate of 9.7 deaths per 100,000 inhabitants, which places it 10th in the world. Motorcycles in Colombia correspond to 57% of the fleet and generate an average of 51% of fatalities per year. This study aims to identify significant factors of the environment, traffic volume, and infrastructure to predict the number of accidents per year focused only on motorcyclists. The prediction model used a negative binomial regression for the definition of a Safety Performance Function (SPF) for motorcyclists. In the second stage, Bayes' empirical approach is implemented to identify motorcycle crash-prone road sections. The study is applied in Cartagena, one of the capital cities with more traffic crashes and motorcyclists dedicated to informal transportation (motorcycle taxi riders) in Colombia. The data of 2,884 motorcycle crashes between 2016 and 2017 are analyzed. The proposed model identifies that crashes of motorcyclists per kilometer have significant factors such as the average volume of daily motorcyclist traffic, the number of accesses (intersections) per kilometer, commercial areas, and the type of road and it identifies 55 critical accident-prone sections. The research evidences coherent and consistent results with previous studies and requires effective countermeasures for the benefit of road safety for motorcyclists.

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