Evaluation of accident prediction for rural highways

2008 ◽  
Vol 35 (6) ◽  
pp. 647-651 ◽  
Author(s):  
Eric Hildebrand ◽  
Karen Robichaud ◽  
Hong Ye
Keyword(s):  
New Brunswick ◽  
Prediction Models ◽  
Retrospective Evaluation ◽  
Rural Highways ◽  
Accident Prediction ◽  
Predictive Variables ◽  
Accident Rates ◽  
Historical Accident

This paper evaluates the accuracy of three commonly used models that predict accidents on two-lane, rural, arterial highways. The retrospective evaluation compared model outputs with empirical collision results for a sample of highway sections in the Province of New Brunswick. The analysis determined historical accident rates, identified key predictive variables, and compared the observed results with estimates from each safety model. All three models were found to significantly overestimate accident frequencies on the highway sections under study. The model generally employed in New Brunswick, MicroBENCOST, was found to yield the highest errors in estimated collisions. These findings suggest that the benefits from accident reduction are generally overestimated on highway improvement projects analyzed with these accident prediction models.

Effect of geometric design consistency on road safety

2004 ◽  
Vol 31 (2) ◽  
pp. 218-227 ◽  
Author(s):  
Joanne C.W Ng ◽  
Tarek Sayed
Keyword(s):  
Road Safety ◽  
Prediction Models ◽  
Model Development ◽  
Geometric Design ◽  
Highway Design ◽  
Rural Highways ◽  
Accident Prediction ◽  
Design Characteristics ◽  
Design Consistency ◽  
The Impact

Geometric design consistency is emerging as an important rule in highway design. Identifying and treating any inconsistency on a highway can significantly improve its safety performance. Considerable research has been undertaken to explore this concept including identifying potential consistency measures and developing models to estimate them. However, little work has been carried out to quantify the safety benefits of geometric design consistency. The objectives of this study are to investigate and quantify the relationship between design consistency and road safety. A comprehensive accident and geometric design database of two-lane rural highways is used to investigate the effect of several design consistency measures on road safety. Several accident prediction models that incorporate design consistency measures are developed. The generalized linear regression approach is used for model development. The models can be used as a quantitative tool for the evaluation of the impact of design consistency on road safety. An application is presented where the ability of accident prediction models that incorporate design consistency measures is compared with those that rely on geometric design characteristics. It is found that models that explicitly consider design consistency may identify the inconsistencies more effectively and reflect the resulting impacts on safety more accurately than those that do not.Key words: geometric design consistency, road safety, quantification, accident prediction models.

Accident prediction models with random corridor parameters

2009 ◽  
Vol 41 (5) ◽  
pp. 1118-1123 ◽  
Author(s):  
Karim El-Basyouny ◽  
Tarek Sayed
Keyword(s):  
Prediction Models ◽  
Accident Prediction

scholarly journals Studying the effect of spiral curves and intersection angle, on the accident ratios in two-lane rural highways in Iran

2013 ◽  
Vol 25 (4) ◽  
pp. 343-348 ◽  
Author(s):  
Mohammad Hossain Jalal Kamali ◽  
Mohammad Saeed Monajjem ◽  
Mohammad Sadegh Ayubirad
Keyword(s):  
Transportation Engineering ◽  
Intersection Angle ◽  
Highway Design ◽  
Rural Highways ◽  
Horizontal Curves ◽  
Accident Rates

Safety in highways is one of the most important subjects in Transportation Engineering. Increasing rate of vehicles and the needs to design or geometrically modifying the highways, emphasized on the safe-designing of the roadways more than before. Between the constructive components of the highway, horizontal curves due to the more occurrences of accidents are of great importance. The American ministry of highway and transportation introduced the software IHSDM, with variant capabilities, to predict accidents. In this research, five types of curves (simple circle curve and clothoid-circle-clothoid) at different intersection angles were designed, and accident rates based on the standard specifications on each curve was predicted by using the IHSDM, and the results are compared with each other. Finally, by processing the curves of accident rates versus the curves types and intersection angle, and comparing them with each other, the necessity of using spiral curves in the highway design is emphasized.

Calibration and Transferability of Accident Prediction Models for Urban Intersections

2002 ◽  
Vol 1784 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Bhagwant Persaud ◽  
Dominique Lord ◽  
Joseph Palmisano
Keyword(s):  
Functional Form ◽  
Prediction Models ◽  
Research Effort ◽  
Safety Performance ◽  
Accident Prediction ◽  
Unsignalized Intersections ◽  
Safety Performance Functions ◽  
Safety Design ◽  
Accident Data ◽  
Single Calibration

Accident prediction models, also known as safety performance functions, have several important uses in modern-day safety analysis. Unfortunately, calibration of these models is not straightforward. A research effort was undertaken that demonstrates the complexity of calibrating these models for urban intersections. These complexities relate to the specification of the functional form, the accommodation of the peculiarities of accident data, and the transferability of models to other jurisdictions. Toronto data were used to estimate models for three- and four-legged signalized and unsignalized intersections. Then the performance of these models was compared with that of models for Vancouver and California that were recalibrated for Toronto using a procedure recently proposed for the application in the Interactive Highway Safety Design Model (IHSDM). The results of this transferability test are mixed, suggesting that a single calibration factor as is currently specified in the IHSDM procedure may be inappropriate and that a disaggregation by traffic volume might be preferable.

Traffic accident modeling: some statistical issues

2006 ◽  
Vol 33 (9) ◽  
pp. 1115-1124 ◽  
Author(s):  
Z Sawalha ◽  
T Sayed
Keyword(s):  
Road Safety ◽  
Regression Models ◽  
Model Building ◽  
Negative Binomial ◽  
Prediction Models ◽  
Negative Binomial Regression ◽  
Outlier Analysis ◽  
Accident Prediction ◽  
Binomial Regression ◽  
Statistical Issues

Accident prediction models are invaluable tools that have many applications in road safety analysis. However, there are certain statistical issues related to accident modeling that either deserve further attention or have not been dealt with adequately in the road safety literature. This paper discusses and illustrates how to deal with two statistical issues related to modeling accidents using Poisson and negative binomial regression. The first issue is that of model building or deciding which explanatory variables to include in an accident prediction model. The study differentiates between applications for which it is advisable to avoid model over-fitting and other applications for which it is desirable to fit the model to the data as closely as possible. It then suggests procedures for developing parsimonious models, i.e., models that are not over-fitted, and best-fit models. The second issue discussed in the paper is that of outlier analysis. The study suggests a procedure for the identification and exclusion of extremely influential outliers from the development of Poisson and negative binomial regression models. The procedures suggested for model building and conducting outlier analysis are more straightforward to apply in the case of Poisson regression models because of an added complexity presented by the shape parameter of the negative binomial distribution. The paper, therefore, presents flowcharts detailing the application of the procedures when modeling is carried out using negative binomial regression. The described procedures are then applied in the development of negative binomial accident prediction models for the urban arterials of the cities of Vancouver and Richmond located in the province of British Columbia, Canada. Key words: accident prediction models, overfitting, parsimony, outlier analysis, Poisson regression, negative binomial regression.

Accident prediction models for roads with minor junctions

1996 ◽  
Vol 28 (6) ◽  
pp. 695-707 ◽  
Author(s):  
Linda Mountain ◽  
Bachir Fawaz ◽  
David Jarrett
Keyword(s):  
Prediction Models ◽  
Accident Prediction

Comprehensive Safety Assessment Model of Highway Section Based on the Accident Rate Prediction

2014 ◽  
Vol 1065-1069 ◽  
pp. 3372-3376
Author(s):  
E Lu ◽  
Jing Liang Xu
Keyword(s):  
Prediction Model ◽  
Safety Assessment ◽  
Prediction Models ◽  
Influence Factors ◽  
Assessment Model ◽  
Accident Rate ◽  
Analytic Hierarchy ◽  
Accident Prediction ◽  
Rate Prediction ◽  
Hierarchy Process

At home and abroad research, accident rate prediction model for highway safety assessment contains various influence factors, so it is difficult to find a comprehensive accident prediction model considering so much of them. In this article, we select appropriate accident prediction models through comprehensive literature research respectively about the highway alignment conditions, traffic conditions, interchange spacing conditions, then determine the weights of three accident prediction models using the analytic hierarchy process (AHP), finally obtain the comprehensive safety assessment model after the consistency check. Its’ feasibility is proved by a practical example.

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