An Examination of the Endogeneity of Speed Limits and Accident Counts in Crash Models

1. An Examination of the Endogeneity of Speed Limits and Accident Counts in Crash Models ITE Presentation June 27, 2012 Presenter:Jung-Han Wang

2. 1. Introduction 2. Literature Review 5. Result 4. Data Description 7. Q&A Contents 3. Methodology 6. Conclusion

3. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results Speed limit should be set realistically for the majority of drivers on the road Previous researches have treated the predictor variable for a certain speed limit as exogenous Single equation modeling techniques used by previous researches have resulted in widely variable data Research was delivered by running single equation models individually involving crash counts, speed limits and then comparing them with a simultaneous equation model (SEM)

4. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results W/O Endogeneity With Endogeneity It is anticipated to obtain less biased estimators by using simultaneous equation models. Single equation modeling techniques will result in widely Variable data Single equation modeling techniques used by previous researches have resulted in widely variable data

5. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results National Maximum Speed Law 1.NMSL speed limit is 55 mph, but actual speed limit varied from state to state. 1973 2.Congress permitted states to raise speed limits to 65 mph (105 km/h) on rural Interstate highways 1987 3. Repeal of federal limits. Federal returns all speed limit determination authority to the states. 1995

6. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results Speed Limit Increment and Accidents California North Carolina Utah 55-65 mph not significantly change 65-70 not significantly change urban interstate highway increase in acc counts Rural interstate highway not significantly change 55–65 mph increase in collision 65-70 mph not significantly change

7. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results • AZ Department of Transportation • Speed zoning in Arizona is based • on 85 percentile of the drivers are • traveling. • This speed is subject to downward revision based upon such factors as: accident experience, roadway geometrics, and adjacent development

8. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results • Model Selection • Poisson distribution restricts the mean and the variance to be equal: • (E[yi] = VAR[yi]). When this equality does not hold, the data are said to be under dispersed (E[yi] > VAR[yi]) or over dispersed (E[yi] < VAR[yi]). • So Negative Binomial Model was chosen

9. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results where λi = Accident Counts xi = Speed Limit εi= Error Term β = coefficient of xi Traditional Model for Crash Counts Negative Binomial Model λi = EXP (βxi +εi= EXP (βxi) * EXP (εi)

10. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results where λi = Accident Counts xi = Speed Limit ε1i, ε2i = Error Term Simultaneous Equation Model Negative Binomial Model λi = EXP (β1xi +ε1i = EXP (β1xi) * EXP (ε1i) Multiple Linear Regression Model xi= β2λi+ε2i

11. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results Research Procedure Collect Data Set up Model In R Model for Major Road Model for Minor Road Single Equation Model (NB) Simultaneous Equation Model (NB+MLR) Simultaneous Equation Model (NB+MLR) Single Equation Model (NB) Compare Results Compare Results Summary

12. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results Data Retrieved • Crash Type • City of Corona Locations: 298 intersections Duration: 2000 to 2009 Crash types: Rear end, head on, side swipe, broad side, hit object, over turn, vehicle vs. pedestrian, etc. 10 different types total. Crash severities: fatal, severe injury, other visible injury, complaint of pain, and non-injury • Severity

13. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results • Comparison Coefficient for Major Road Approach

14. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results • Comparison Coefficient for Minor Road Approach

15. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results • Comparison Coefficient for Major Road Approach

16. 2.Literature Review 3. Methodology 6. Conclusions 7. Q & A 1.Introduction 4. Data Description 5. Results • 1. From all the 298 intersections that were analyzed, there was no significant difference in the results accounting and not accounting for endogeneity since all the signs associated with different coefficients remain the same. • 2.The differences illustrated in the magnitude of the coefficientsalso suggest one might make erroneous judgment if the endogeneity between speed limit and accidents are totally ignored. • 3.The study indicates crashes are endogenously related with a speed limit on major approach • 4.Re-estimate the predictor variables by running the models with only the most significant variables

17. 2.Literature Review 3. Methodology 6. Recommen- dation 7. Q & A 1.Introduction 4. Data Description 5. Conclusion Thank You ! Q & A