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In the state of Florida, work-zone related crashes and their resulting injury severities have been increasing recently, particularly over the 2015 to 2017 time period. In the current study, we seek to provide insights into the factors that have been influencing this trend. Using work zone data from the 2012 to 2017 time period, resulting driver-injury severities in single-vehicle work zone crashes were studied using random parameters logit models that allow for possible heterogeneity in the means and variances of parameter estimates. The available data included a wide variety of factors known to influence driver injury severity including data related to the crash characteristics, vehicle characteristics, roadway attributes, prevailing traffic volume, driver characteristics, and spatial and temporal characteristics. The model estimates produced significantly different parameters for each of the year from 2012 to 2017, and a fundamental shift in unobserved heterogeneity, suggesting statistically significant temporal instability. In addition, in several key instances, the marginal effects of individual parameter estimates show marked differences between one year and the next. However, these findings may not be the sole result of variations in driver behavior over time as has been argued in past research that has found temporal instability. This is because each work zone has a unique set of characteristics and, with the sample of work zones changing from one year to the next as highway maintenance and construction is undertaken in different locations, this work-zone sample variation could be a substantial source of the observed temporal instability.

This study explores the temporal instability of factors affecting motorcyclist-injury severities in single-vehicle motorcycle crashes in Florida. Two data sources are used; one covers the 2012 to 2016 crash histories of Florida motorcyclists who were newly licensed in 2012, and the second covers motorcycle crashes that occur on horizontal curves in Florida from 2005 to 2015. In the first dataset (2012 new riders), temporal changes may result from riders gaining experience as well as general temporal shifts. In the second dataset, rider experience is unknown (thus becoming a source of potential unobserved heterogeneity) but the temporal changes will be largely from general temporal shifts. With three possible motorcyclist injury severity outcomes (no visible injury, minor injury, and severe injury), random parameters multinomial logit models, that allow for heterogeneity in means and variances, were estimated for all possible annual time periods in each dataset. Likelihood ratio tests were conducted to examine the overall stability of model estimates across time periods, and marginal effects of each explanatory variable were also considered to investigate the temporal instability of the effect of individual parameter estimates on motorcyclist injury-severity probabilities. A wide range of variables was considered including motorcyclists’ attributes (such as ethnicity and age), roadway and environmental conditions (such as light and road surface conditions), motorcycle characteristics (such as motorcycle make and type of motorcycle), rider actions (such as speeding and improper driving actions), and roadway conditions (such as obstacles on the road and speed limits). The results show significant temporal instability in motorcyclist-injury severity models, which likely result from changes in motorcycle technology and performance, changes in macroeconomic conditions, changes induced by how riders respond to the changing behavior of other road users (whose behavior may be changing as a result of technology changes in their vehicles, evolving use of personal technologies in their vehicle, such as cell phones, etc.), and the changes in riders’ behavior and skills over time.