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Lec 11, Ch.8: Accident Studies (objectives)

Lec 11, Ch.8: Accident Studies (objectives). Be able to explain different approaches to traffic safety Be familiar with typical data items that are collected and stored (through reading) Know types of accident analysis typically conducted Know how to conduct site analyses

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Lec 11, Ch.8: Accident Studies (objectives)

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  1. Lec 11, Ch.8: Accident Studies (objectives) • Be able to explain different approaches to traffic safety • Be familiar with typical data items that are collected and stored (through reading) • Know types of accident analysis typically conducted • Know how to conduct site analyses • Be familiar with different safety countermeasures and their cost effectiveness (through reading)

  2. What we cover in class today… • Approaches to highway safety • Accident data collection and record systems (quick review) • Accident statistics • Analysis of site-specific accident data

  3. Approaches to highway safety

  4. Accident data collection and record systems (discussed in the inventory discussion in ch4) • One of the most basic functions of traffic engineering is keeping track of the physical inventory. Collision diagram Accident spot map Example: AIMS (Accident Info Mgmt System) by JMW Engineering

  5. Accident statistics • Types of accidents • Numbers of accidents Occurrence • No. of deaths • No. of injuries • Categories of vehicles • Categories of drivers Types of statistics Involvement Severity For accident stats, visit www.nhtsa.dot.gov

  6. Typical accident rates used “Bases” are needed to compare the occurrence of accidents at different sites. • Population based: • Area population (25 deaths per 100,000 pop) • No. of registered vehicles (7.5 deaths per 10,000 registered vehicles) • No. of licensed drivers (5.0 deaths per 10,000 licensed drivers) • Highway mileage (5.0 deaths per 1,000 miles) • Exposure based: • VMT (5.0 deaths per 100 million VMT) • VHT (5.0 deaths per 100 million VHT) Severity index: No. of deaths/accident (0.0285 accidents per accident) No. of injuries/accident • Typical basic accident rates: • general accident rates describing total accident occurrence • fatality rates describing accident severity • involvement rates describing the types of vehicles and drivers involved in accidents

  7. Types of statistical displays The purpose of the display dictates the type of display – temporal, spatial, accident type, etc.

  8. Site analysis • Purposes: • Identify contributing causes • Develop site specific improvements • Two types of info: • Accident data • Environment & physical condition data The first thing you do is visit the site and prepare a condition diagram of the site. (Table 8-4 is useful.)

  9. Site analysis (cont) Then we prepare a collision diagram.

  10. Site analysis (cont) Group accidents by type and answer the following 3 questions, which will lead you to possible countermeasures. • What drivers actions lead to the occurrence of such an accident? • What conditions existing at the location could contribute toward drivers taking such actions • What changes can be made to reduce the chance of such actions occurring in the future? Rear-end collisions: Driver: Sudden stop & Tailgating Environment: Too many accesses and interactions with vehicles in/out of the accesses, bad sight distance, short/long yellow interval, inappropriate location of stop lines, etc.

  11. 5% z = 1.645 Determining high-accident locations H0: Accident rate at the location under consideration in the group is equal to the average rate of the group. H1: Accident rate at the location under consideration in the group is higher than the average rate of the group. This is a one-tailed test. Why? Locations with a higher accident rate than this value would normally be selected for specific study. Example: Highway Section 33 has 210 accident/100MVMT. The mean accident rate for the similar classification group = 89 accident/100MVMT, SD = 64 accident/100MVMT. Should an analyst flag Section 33 as hazardous? With 95% confidence level?

  12. Determining high-accident locations: Expected value analysis (from Garber & Hoel) • Note this method is used only to compare sites with similar characteristics. H0: Accident rate at the location under consideration in the group is equal to the average rate of the group. H1: Accident rate at the location under consideration in the group is not equal to the average rate of the group (In another words, we are trying to find whether the site under study is “unusual” or not. We are not specifically proving it is “over-represented” or not.) z = 1.96 for the 95% confidence level Locations with a higher accident rate than this value would normally be selected for specific study. Not over-represented or under-represented “Under-represented” “Over-represented”

  13. Example 5-3 (modified): An intersection with 14 rear-end, 10 LT, and 2 right-angle collisions for 3 consecutive years • Check about rear-end collisions Rear-end collisions are over-represented at the study site at 95% confidence level, since 14 > 10.34. • Check about LT collisions LT collisions are not over-represented or under-represented at the study site at 95% confidence level, since 0.88<10 < 12.92. • Check about right-angle collisions Right-angle collisions are under-represented at the study site at 95% confidence level, since 2 < 2.4.

  14. Statistical analysis of before-after accident data Method 1: Use the Normal Approximation method: z1 = test statistic, 1.96 at the 95% confidence level for a “change”, 1.645 for a “reduction.” fA = No. of accidents in the “after” study fB = No. of accidents in the “before” study This method is however not recommended by the current Manual of Transportation Engineering Studies.

  15. Statistical analysis of before-after accident data (cont) Method 2: The Modified Binomial Test Example: Before 14 conflicts were observed at a stop-sign controlled intersection. After the installation of a signal, they observed 7 conflicts. Were the signal effective? Solution: Figure on the right shows that for 14 before conflicts you need a 60% reduction to be significant at the 95% CL. 7/14=50% reduction. So, you cannot reject the null hypothesis.

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