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Florida’s Road Rangers (RRs) are the state’s safety service patrol. Over 60% of RR responses are for disabled vehicles. This paper investigates the impact RRs have on disabled vehicle events and identifies roads with potential for expansion of RR patrol hours by analyzing 2019 incident and crash data. Over 213,000 disabled vehicle incidents occurred on roadways with partial RR coverage, with 20% occurring during RR inactive periods. The average incident duration more than doubled during inactive periods from 49 min to 100 min. After analyzing several factors, such as incident duration differences and percentage of inactive events, I-10 in Florida’s panhandle was identified as the roadway which would most benefit from increased patrol hours. Ninety-five disabled vehicle crashes occurred on roadways with partial RR coverage, with 56% occurring during inactive patrol hours; these inactive period crashes resulted in 70% of the injuries and 67% of the fatalities. The Tampa area had many crashes (especially during inactive periods), so roadways in this area would benefit from increased patrol hours. A significant relationship between RR presence and response activity duration was found, with an average response activity duration of 106 min during inactive periods and 71 min during active periods. These results show the importance of increasing the periods of RR coverage and how RRs assist law enforcement by responding to disabled vehicle events and their associated crashes, allowing law enforcement to focus their efforts on more severe crashes or other traffic-impacting events.

Wrong-way driving (WWD) crashes can have significant impacts on freeway safety and operations. Deploying intelligent transportation systems (ITS) WWD countermeasures at freeway exit ramps can effectively reduce WWD crash risk (WWCR), but these countermeasures are expensive. In this paper, a WWCR segment model and WWD countermeasures optimization algorithm are developed for all Florida limited access facilities (56 roadways with 1,375 exits) to identify the optimal locations for ITS countermeasure deployment. These were previously developed for specific toll-road networks within Florida, but never for a statewide network. Multiple WWCR models were investigated, with the final Poisson model using four-exit segments and 5 years of WWD event data. This model showed that more WWD events and higher crossing road traffic volumes increased WWCR, while certain interchange designs increased or decreased WWCR. Sixty-three segments containing 169 exit ramps without ITS WWD countermeasures were identified as WWD hotspots; these ramps were compared with the 169 ramps with the highest WWCR selected by the optimization algorithm. The algorithm selected 96 ramps not in the hotspots (improved resource utilization of 56.8%) and provided a 38.6% increase in WWCR reduction. Comparing WWD detection and turnaround data from 31 sites with rectangular flashing beacon ITS countermeasures to the optimization indicated a significant positive association between WWCR and turnaround percentage (higher WWCR at sites with lower turnaround percentage), verifying the accuracy of the optimization. By showing the transferability, scalability, accuracy, and benefits of this approach, this paper can help agencies reduce WWD and improve freeway safety and operations.

Safety performance functions (SPFs) are essential tools to help agencies predict crashes and understand influential factors. Florida Department of Transportation (FDOT) has implemented a context classification system which classifies intersections into eight context categories rather than the three classifications used in the Highway Safety Manual (HSM). Using this system, regional SPFs could be developed for 32 intersection types (unsignalized and signalized 3-leg and 4-leg for each category) rather than the 10 HSM intersection types. In this paper, eight individual intersection group SPFs were developed for the C3R-Suburban Residential and C4-Urban General categories and compared with full SPFs for these categories. These comparisons illustrate the unique and regional insights that agencies can gain by developing these individual SPFs. Poisson, negative binomial, zero-inflated, and boosted regression tree models were developed for each studied group as appropriate, with the best model selected for each group based on model interpretability and five performance measures. Additionally, a linear regression model was built to predict minor roadway traffic volumes for intersections which were missing these volumes. The full C3R and C4 SPFs contained four and six significant variables, respectively, while the individual intersection group SPFs in these categories contained six and nine variables. Factors such as major median, intersection angle, and FDOT District 7 regional variable were absent from the full SPFs. By developing individual intersection group SPFs with regional factors, agencies can better understand the factors and regional differences which affect crashes in their jurisdictions and identify effective treatments.

Previous research has studied wrong-way driving (WWD) crashes, citations, and 911 calls to understand WWD characteristics, but no research has utilized WWD detection data. In this paper, WWD detection data from 48 toll road exit ramps were modeled to identify the factors that affect WWD frequency. The developed negative binomial model showed that exit ramps with more lanes, a toll booth, and higher crossing street volumes were predicted to have more WWD, whereas having more lanes on the opposing approach to the exit ramp was predicted to reduce WWD. Examination of 726 WWD detections showed that 23% were initiated by left-turning vehicles and 18% were initiated by right-turning vehicles, with significantly more left-turn entries occurring at night than right-turn entries (at α = 0.05). A case study of five ramps showed that exits with an extended median on the crossing road had fewer left-turn entries and exits with right-turn lanes on the crossing road had fewer right-turn entries. Lastly, radar, laser, and thermal WWD detection technologies were compared based on their WWD detections and false alarms. The laser sites had significantly more detections and false alarms than the radar sites (at α = 0.05), with the radar sites having a significantly higher WWD detection rate than false alarm rate. Radar false alarms were mainly caused by large trucks, whereas the laser sites had issues with equipment damage and traffic queues. The results of this paper can help agencies better understand WWD behavior and identify the most appropriate WWD detection technologies.