MACROSCOPIC BICYCLE CRASH ANALYSIS: FOCUSING ON CRASH LOCATIONS AND RESIDENCE

摘要

Recent bicycle crash analyzes have been focused on the macroscopic level but have leftrnmultiple unanswered research questions. (1) What are the contributing factors for thernnumber of bicycle crashes per crash location zone? What are factors for the number ofrncrash-involved bicyclists per residence zone? (2) Do the two targets have commonrnunobserved factors and spatial autocorrelations? (3) Is there a way to analyze the hotrnzones for the two targets simultaneously? Therefore, the main objectives of this study arernto answer these questions. This study aims to identify the contributing factors both forrn‘Bicycle crashes per crash location ZIP code’ and ‘Crash-involved bicyclists per residencernZIP code area.’ Bayesian Poisson Lognormal Simultaneous Equation Spatial Error Modelrn(BPLSESEM) was employed and revealed significant factors for the two target variables.rnSubsequently, a novel hot zone identification method was suggested to combine both hotrnzones from where vulnerable bicyclists originated with hot zones where many bicyclerncrashes occur. For the former zones, targeted safety education and awareness campaignsrncan be provided as countermeasures whereas area-wide engineering treatments andrnenforcement may be effective safety treatments for the latter ones. It is expected thatrnpractitioners can provide appropriate safety treatments for bicycle crashes using thernmethod and results from this study. This is important because although there have beenrnmedical advancements for roadway trauma, prevention has remained the best solution forrnavoidance of fatalities.