Safety management software for state and local highway agencies: –Improves identification and programming of site- specific highway safety improvements.

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Presentation transcript:

Safety management software for state and local highway agencies: –Improves identification and programming of site- specific highway safety improvements –Incorporates state-of-the-art safety management approaches with computerized analytical tools

Who is Developing SafetyAnalyst? Federal Highway Administration Technical Working Group 19 participating (pooled-fund) States 1 local highway agency 2 MPOs

Participating States

SafetyAnalyst Modules Module 1 – Network Screening Module 2 – Diagnosis and Countermeasure Selection Module 3 – Economic Appraisal and Priority Ranking Module 4 – Countermeasure Evaluation

Status of Development Module 1 - Network Screening –Beta testing of interim version underway Module 2 - Diagnosis and Countermeasure Selection –Interim version available for testing Dec 2006 Module 3 - Economic Appraisal and Priority Ranking –Interim version available for testing Dec 2006 Module 4 – Countermeasure Evaluation –Beta testing of interim version underway

Advantages of SafetyAnalyst over Existing Techniques Integrates/automates all parts of safety management process Applies state-of-the-art analytical procedures Strong cost-effectiveness component …Enables engineers to make more informed decisions more efficiently

Module 1: Network Screening

Module 1 - Objectives Screen entire roadway network, or portion of network, and to identify sites with potential for safety improvement Rank sites with potential for safety improvement Select sites for further investigation within Module 2 - Diagnosis and Countermeasure Selection

Types of Network Screening Basic network screening –With Peak Searching on roadway segments –With Sliding Window on roadway segments High proportion of specific accident type Sudden increase in mean accident frequency Steady increase in mean accident frequency Corridors with promise

Basic Network Screening Uses Empirical Bayes methodology –Combine observed and predicted accidents Expected accident values expressed as: –Expected accident frequency –Excess accident frequency Two screening approaches for roadway segments –Peak searching –Sliding window

Basic Network Screening: (with Peak Searching on Roadway Segments) For roadway segments, individual sites are divided into windows of size 0.1 mi –Accident frequencies are calculated for each window within a site Windows are flagged when: –Expected value greater than user-specified limit –Expected value is statistically reliable If no windows are flagged, incrementally increase window size by 0.1 mi and test again More than one window pertaining to a site can be flagged Rank order site based upon expected or excess accident frequencies

0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Win # 2 Win # 3 Win # 4 Win # 5 Win # mi 0.07 mi Roadway Segment Win # 6 Note: Window length = 0.1 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5 Peak Searching Concepts

0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Win # 2 Win # 3 Win # 4 Win # mi Roadway Segment Win # mi Note: Window length = 0.2 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5 Peak Searching Concepts

0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Win # 2 Win # 3 Win # 4 Win # 5 Roadway Segment Note: Window length = 0.3 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5 Peak Searching Concepts

0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Win # 2 Win # 3 Win # 4 Roadway Segment Note: Window length = 0.4 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5

Peak Searching Concepts 0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Win # 2 Win # 3 Roadway Segment Note: Window length = 0.5 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5

Peak Searching Concepts 0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Win # 2 Roadway Segment Note: Window length = 0.6 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5

Peak Searching Concepts 0.0 mi0.1 mi0.2 mi0.3 mi0.4 mi0.5 mi0.6 mi0.67 mi Win # 1 Roadway Segment Note: Window length = Segment length Expected accidents = (acc/mi) Limiting Value = 5 acc/mi CV Limit = 0.5

Basic Network Screening: (with Sliding Window on Roadway Segments) Users specifies: –Window size (e.g., 0.3 mi) –Increment length (e.g., 0.1 mi) For each window position, determine: –Expected or excess accident frequency Windows allowed to bridge sites More than one window pertaining to a site can be flagged Rank order site based upon expected or excess accident frequencies

Site No. 1 MP 1.0MP 2.6 First Sliding Window W = 0.3 mi 1.1 mi1.2 mi1.3 mi1.4 mi1.5 mi Sliding Window Concepts

Site No. 1 MP 1.0MP 2.6 First Sliding Window W = 0.3 mi 1.1 mi1.2 mi1.3 mi1.4 mi1.5 mi Second Sliding Window W = 0.3 mi Sliding window is moved incrementally by 0.1 mi along the roadway segment. Sliding Window Concepts

Site No. 23Site No. 24 MP 35.4MP 36.2MP 36.7 X = 3.1 Note: Window length = 0.3 mi Increment length = 0.1 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi X = 4.3X = 5.6X = 7.8 X = 9.8 X = 7.5 X = 6.0 X = 4.5 X = 3.5 X = 3.0 X = 4.0X = 5.1 X = 5.5

Site No. 23Site No. 24 MP 35.4MP 36.2MP 36.7 Note: Window length = 0.3 mi Increment length = 0.1 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi X = 5.6X = 7.8 X = 9.8 X = 7.5 X = 6.0X = 5.1 X = 5.5

Site No. 23Site No. 24 MP 35.4MP 36.2MP 36.7 Note: Window length = 0.3 mi Increment length = 0.1 mi Expected accidents = (acc/mi) Limiting Value = 5 acc/mi X = 5.6X = 7.8 X = 9.8 X = 7.5 X = 6.0X = 5.1 X = 5.5

High Proportions of Specific Accident Type Objective: –Identify sites having higher than expected proportions of specific target accidents –Rank sites based on difference observed proportion and expected proportion of target accident Methodology –Calculate observed proportion (TOT only) –Calculate the probability that observed proportion is greater than limiting proportion (i.e., avg for site & accident type) –Site flagged when probability is greater than some user-specified significance level

Roadway segments –Similar to sliding window approach –Longer windows are needed to reduce variance (e.g., 1.0 mi) –More than one window pertaining to a site can be flagged Site ranked based upon maximum difference between observed proportion and expected proportion High Proportions of Specific Accident Type (cont.)

Sudden Increase in Mean Accident Frequency Screening for safety deterioration –Calculate differences in mean yearly accident frequencies –For the time period with the largest difference: If the percentage increase is greater than a user-specified limiting value Then perform test of significance Based on observed accidents Based on total accidents Flagged sites are not rank ordered

Steady Increase in Mean Accident Frequency Screening for safety deterioration –Fit regression model to data of accident frequency versus year If value of slope is greater than a user- specified limiting slope Then perform test of significance Based on observed accidents Based on total accidents Flagged sites are not rank ordered

Screening for Corridors with Promise Analysis of extended corridors (e.g., 10 mi or more) –Roadway segments, intersections, and ramps grouped together Rank order corridors based upon: –Accidents/mi/yr –Accidents/million veh-mi/yr Based on observed accidents

Demonstration of Module 1: Network Screening

SafetyAnalyst Modules Module 1 – Network Screening Module 2 – Diagnosis and Countermeasure Selection Module 3 – Economic Appraisal and Priority Ranking Module 4 – Countermeasure Evaluation

Module 2 – Diagnosis and Countermeasure Selection Display collision diagram (links to third- party software) Identify collision patterns Conduct diagnostic investigations Suggest countermeasures that address identified collision patterns Select appropriate countermeasures

Module 3 – Economic Appraisal and Priority Ranking Perform economic analysis of alternative countermeasures for a specific site Perform economic analysis of improvements across selected sites Select mix of sites and countermeasures to get maximum benefits within a specified budget Develop priority ranking of alternative improvements

Module 4: Countermeasure Evaluation Tool

Objective Determine safety effectiveness (percent reduction in crashes) for specific implemented countermeasures Conduct before-after evaluation of crash frequencies using the Empirical Bayes (EB) approach Conduct before-after evaluation of shifts in crash severity or crash type proportion

Why the Evaluation Tool? The goal of SafetyAnalyst is to help highway agencies determine how funds can be spent in the most cost-effective manner to improve safety. The results of Module 4 can be used to update the accident modification factors (AMFs) that are used within Module 3 for economic appraisal and priority ranking of countermeasures to be implemented at sites.

When to Use the Evaluation Tool A countermeasure has been implemented at a number of sites The agency wants to assess how effectively the countermeasure performed: –Did it improve the safety performance at a site? –Did it reduce a specific target accident type?

What Information Is Needed Locations of improved sites Countermeasure(s) to evaluate for each site –Year of implementation –Countermeasure name(s) Site characteristics ADTs (before and after improvement) Yearly accident counts (before and after) Safety Performance Functions (SPFs)

Types of Analyses Conducted The safety effectiveness of countermeasures is quantified through the use of before-after statistical evaluations. Two types of before-after evaluations can be conducted: –Percent change in accident frequencies, due to the implemented countermeasure, is evaluated by an Empirical Bayes (EB) technique. –Shift in proportion of specific collision types is evaluated using the Wilcoxon signed rank test

Demonstration of Module 4: Countermeasure Evaluation Tool