This research investigates the main reasons leading the State of Florida to be ranked among the worst states in terms of pedestrian safety with four metro areas considered the most dangerous for pedestrians among all the United States as reported in the Dangerous by Design report. The study analyzes the characteristics and contributing causes of pedestrian crashes that occurred in Central Florida over a 5 year-period (2011-2015) at intersections and along roadway segments at mid-block locations using the data obtained from the Signal 4 Analytics database. All pedestrian related crashes were compiled and all the 6,789 crash reports were studied thoroughly. Intersection and roadway pedestrian related crashes were identified along with all the parameters and conditions related to the high crash risk of pedestrians. However, due to inconsistencies in the police report inputs such as miscoding and misinterpretation, a screening criteria was developed to exclude or disqualify crashes that do not meet the research requirements. Preliminary descriptive statistics revealed the most common types of crashes at each location. For intersection-related crashes, it was found that left turn, right turn and through moving vehicles struck crossing pedestrians. At mid-block locations, major crash types were through moving vehicles hitting pedestrians crossing and walking along the roadway. The evaluated factors affecting pedestrian crashes were classified into four main categories; location characteristics (e.g. intersection, midblock, type of control, presence of crosswalk, presence of sidewalk), pedestrian factors (e.g. pedestrian under influence, failure to yield to the right of way), driver/vehicle characteristics (e.g. driving under influence, failed to yield to traffic control device, aggressive driving), and environmental-related factors (e.g. weather conditions, road surface conditions and time of day) were among the factors studied. Three different models were utilized in the analysis using the SPSS statistical software package. A multinomial logit model was developed to predict the likelihood that a pedestrian will be involved into one of the common crash types. A binary regression model was developed to understand the significant factors contributing to the main causes at each intersection type whether at signalized or un-signalized intersections. Lastly, an ordinal regression model was developed to identify the significant factors affecting the level of injury severity sustained by pedestrians. The results of the multinomial logit model for intersection crashes revealed a high probability of right turn crashes associated with drivers at fault with no aggressive driving related crashes compared to left turn crashes. The results also showed that the probability of through moving vehicle crashes with no traffic control device was 2.437 times higher than left turn crashes. These results confirmed the results of the binary model that a lower likelihood of left or right turn crashes was associated with un-signalized intersections when compared to through crashes. Lastly, a greater probability of through crashes was associated with running the red light when compared to left turn crashes. The results of the binary model revealed that the majority of the un-signalized intersection crashes were attributed to drivers at fault. Among other contributing factors was crossing at un-signalized intersections not equipped with the crosswalks. The chance of crashes at un-signalized intersections is 15.657 times higher in the absence of crosswalks compared to un-signalized intersections in which crosswalks are present. Conversely, signalized intersections related crashes were attributed to running the red light and pedestrians failing to obey traffic control devices. For the ordinal models for crashes at either intersections or mid-block locations, the results revealed that a reduction in the likelihood of severe injuries was associated with drivers being at fault, daytime, no aggressive driving related crashes and sober pedestrians. However, red light running related to intersection crashes, as well as pedestrians failing to yield to the right of way, and drivers under influence related to mid-block crashes were associated with high injury severity and an increase in the likelihood of severe injuries. The findings of this research and examination of the factors affecting pedestrians' crash likelihood and injury severity can lead to better crash mitigation strategies, countermeasures and policies that would alleviate this growing problem in Central Florida.
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Master of Science in Civil Engineering (M.S.C.E.)
College of Engineering and Computer Science
Civil, Environmental and Construction Engineering
Length of Campus-only Access
Masters Thesis (Open Access)
Bianco, Zainb, "Analysis of Pedestrian Crash Characteristics and Contributing Causes in Central Florida" (2017). Electronic Theses and Dissertations. 5362.