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Safety effects of speed limit changes: Use of panel models, including speed, use, and design variables. Transportation Research Record No
 Proceedings of Transportation Research Board Annual Meeting, Washington D.C. (January 2005), and forthcoming in Transportation Research Record.Lee, J., and Mannering, F.L
, 2005
"... This work estimates the total safety effects of speed limit changes on highspeed roadways using traffic detector data and Highway Safety Information System (HSIS) data from 1993 to 1996. In order to gauge the total effects, this study applies a sequential modeling approach in which average speed an ..."
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Cited by 7 (5 self)
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This work estimates the total safety effects of speed limit changes on highspeed roadways using traffic detector data and Highway Safety Information System (HSIS) data from 1993 to 1996. In order to gauge the total effects, this study applies a sequential modeling approach in which average speed and speed variance models are first estimated, based on roadway design, use and speed limit information. Then, crash counts (of varying severity) are estimated, based on the speed estimates, design, and use variables. The four years of data come from 63,937 “homogeneous ” roadway segments along 7 interstates and 143 state highways in Washington State. A randomeffects negative binomial model was selected among several alternative panel and nonpanel models for count data. Results indicate that the average road segment in the data set can be expected to exhibit lower nonfatal crash rates up to a 55 mph speed limit. By contrast, fatality rates appear unresponsive to speed limit changes. Fatal and nonfatal rates fall for design reasons, including wider shoulders and more gradual curves, which appear to be key design variables. However, fatal and nonfatal rates move differently when traffic levels rise, with nonfatal rates remaining unchanged and fatal rates falling.
Crash modeling using clustered data from Washington State: Prediction of optimal speed limits
 Proceedings of the IEEE Intelligent Transportation Systems Conference
, 2006
"... This study investigates the relationship between crash frequencies, roadway design and use features by utilizing the benefits of clustered panel data. Homogeneous highspeed roadway segments across the State of Washington were grouped using TwoStep Cluster Analysis technique, resulting in grouped ob ..."
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Cited by 1 (1 self)
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This study investigates the relationship between crash frequencies, roadway design and use features by utilizing the benefits of clustered panel data. Homogeneous highspeed roadway segments across the State of Washington were grouped using TwoStep Cluster Analysis technique, resulting in grouped observations with reasonably continuous crash count values. This permitted application of both fixed and randomeffects linear regression models for the total number of crashes per million vehicle miles traveled (VMT). A crash severity model also was estimated, using an ordered logistic regression, allowing transformation of total crash counts into counts by severity. Speed limit information is found to be very valuable in predicting crash rates, and the models are seemingly able to predict “optimal ” speed limits in order to minimize crash rates and crash costs. However, speed limits may have biased coefficients, most likely attributable to unobserved safetyrelated effects. For the “average ” highspeed segment in the data set, a minimum expected crash cost is achieved at a speed limit of 70 mi/h, while the maximum crash rate is predicted to occur at a speed limit of 43.5 mi/h. While these calculations may not be realistic, the models appear to accurately predict crash rates (R 2 of 0.90 for total crash count) and the results provide useful information for a variety of design and use effects. For example, crashes are more frequent on shorter horizontal curves, while uphill segments with wider medians are found to experience less severe crashes.
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"... Abstract—This study investigates the relationship between crash frequencies, roadway design and use features by utilizing the benefits of clustered panel data. Homogeneous highspeed roadway segments across the State of Washington were grouped using cluster analysis technique, resulting in grouped o ..."
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Abstract—This study investigates the relationship between crash frequencies, roadway design and use features by utilizing the benefits of clustered panel data. Homogeneous highspeed roadway segments across the State of Washington were grouped using cluster analysis technique, resulting in grouped observations with reasonably continuous crash count values. This permitted application of both fixed and randomeffects linear regression models for the total number of crashes 100 per million vehicle miles traveled (VMT). A crash severity model also was estimated, using an ordered probit regression, allowing transformation of total crash counts into counts by severity. Speed limit information is found to be very valuable in predicting crash occurrence. For roadways with average design and use attributes, a 10 mi/h increase speed limit from 55 mi/h results in 3.29 % more crashes expected for the average roadway section at a speed limit of 55 mi/h. However, speed limits may have biased coefficients, most likely attributable to unobserved safetyrelated effects. In addition, the authors also conducted a cost/benefit analysis of raising speed limit. An increase in speed limit from 55 mi/h to 65 mi/h would save 106,879 hours per 100 million VMT, which is equivalent to $1,607,455. The additional crash counts due to the increase in speed limit only cause $437,964 loss. The results suggest that raising speed limits can offer some considerable time savings benefits.