1. A New Method to Identify Hot Spots in roadway Network BY Wen Cheng, Ph.D., PE Assistant Professor Civil Engineering Department Cal Poly Pomona

2. Presentation Outline Hotspot Identification (HSID) background Description of the new proposed HSID method Application of the new method Summary and Conclusions

3. Crashes in Real Life: Huge Burden

4. Crashes in the U.S. 42,116 fatalities (i.e., 115 persons killed/day) 1.51 fatalities/100M VMT 14.79 fatalities/100K Population 231 Billion Economic Cost 41% alcohol-related fatalities 29.7% Speed-related fatal crashes Source: 2005 NHTSA

5. Crashes in California Source: 2005 CA Statistical Abstract

6. How to address safety challenges ISTEA legislation (1991) and TEA-21(1998) required each state develop safety management systems. SAFETEA-LU (2005) establishes a new core Highway Safety Improvement Program structured and funded to make significant progress in reducing highway fatalities

7. Safety Management System Basic Components

8. Current Practice of HSID Rank a set of candidate locations in terms of the registered accident counts or expected long-term accident counts General assumptions accident process can be viewed as a sequence of Bernoulli trials Accident counts of the set of locations follow negative binomial distribution

9. State-of-the-art HSID Method: Bayesian Where: f (k)= prior pdf of k’s of reference population (similar sites ), it follows gamma distribution whose parameters are obtained based on empirical data. f (K|k)= pdf of accident counts on a specific site whose expected safety is k, it is Poisson distribution. f (K)= pdf of a group of collected accident counts. f ( k|K)= posterior pdf of λ of the site which has x counts.

10. General Process of Diagnosis

11. General Process of Countermeasure Selection

12. Problems of Current Safety Practice The safety management components are somewhat isolated Much less safety resources are allocated to the first step: HSID Much more resources are invested in the subsequent steps. Result: the substantial resources invested in the subsequent steps could be wasted on the sites that are wrongly identified in the first step

13. The New HSID Method Proposed Streamline the safety improvement process by incorporating the crash type and crash severity into HSID step. Crash type recognition: facilitate the crash diagnosis process. Crash Severity recognition: facilitate the economic evaluation of countermeasure alternatives. All information is incorporated under Bayesian framework.

14. Case Study: City of Corona Crossroads Collision Database software 298 Intersections: 141 signalized and 157 non-signalized Crash period: 10 years (2000~2009). A set of roadway factors: minor ADT, major ADT, speed limit, etc.

15. Method Evaluation Crash data divided into 2 groups: Before period (2000~2004), After (2005~2009) Use top 10% locations as crash hotspots Evaluation criteria: overall crash costs of future period for all crashes and crash types. Results: type-and-severity recognition method shows advantages over the typical one in terms of both criteria.

16. Discussion on Future Direction Crash data from other cities or counties are needed. Data sample size (298) is relatively small. Special statistical modeling techniques are required to address issues associated with crash type and severity.