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DRIVING SIMULATOR VALIDATION AND REAR-END CRASH RISK ANALYSIS AT A SIGNALISED INTERSECTION
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TitleDRIVING SIMULATOR VALIDATION AND REAR-END CRASH RISK ANALYSIS AT A SIGNALISED INTERSECTION
AuthorChilakapati, Praveen
KeywordsDriving simulator validation
safety
speed
visual validation
rear-end crash risk
logistic regression model.
AbstractIn recent years the use of advanced driving simulators has increased in the transportation engineering field especially in evaluating safety countermeasures. The driving simulator at UCF is a high fidelity simulator with six degrees of freedom. This research aims at validating the simulator in terms of speed and safety with the intention of using it as a test bed for high risk locations and to use it in developing traffic safety countermeasures. The Simulator replicates a real world signalized intersection (Alafaya trail (SR-434) and Colonial Drive (SR-50)). A total of sixty one subjects of age ranging from sixteen to sixty years were recruited to drive the simulator for the experiment, which consists of eight scenarios. This research validates the driving simulator for speed, safety and visual aspects. Based on the overall comparisons of speed between the simulated results and the real world, it was concluded that the UCF driving simulator is a valid tool for traffic studies related to driving speed behavior. Based on statistical analysis conducted on the experiment results, it is concluded that SR-434 northbound right turn lane and SR-50 eastbound through lanes have a higher rear-end crash risk than that at SR-50 westbound right turn lane and SR-434 northbound through lanes, respectively. This conforms to the risk of rear-end crashes observed at the actual intersection. Therefore, the simulator is validated for using it as an effective tool for traffic safety studies to test high-risk intersection locations. The driving simulator is also validated for physical and visual aspects of the intersection as 87.10% of the subjects recognized the intersection and were of the opinion that the replicated intersection was good enough or realistic. A binary logistic regression model was estimated and was used to quantify the relative rear-end crash risk at through lanes. It was found that in terms of rear-end crash risk SR50 east- bound approach is 23.67% riskier than the SR434 north-bound approach.
AdviserAbdel-Aty, Mohamed
PublisherUniversity of Central Florida
DegreeM.S.
Degree DisciplineDepartment of Civil and Environmental Engineering
Degree GrantorEngineering and Computer Science
Degree ProgramCivil Engineering
Graduation Date2006-12-01
TypeMaster's thesis
Access LevelPublic - Allow Worldwide Access
Release Date2007-01-11
RepositoryUniversity Archives
Repository CollectionElectronic Theses and Dissertations
IdentifierCFE0001391
Access Linkhttp://purl.fcla.edu/fcla/etd/CFE0001391

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