English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Real-time safety analysis has become a hot research topic as it can moreaccurately reveal the relationships between real-time traffic characteristicsand crash occurrence, and these results could be applied to improve activetraffic management systems and enhance safety performance. Most of the previousstudies have been applied to freeways and seldom to arterials. This studyattempts to examine the relationship between crash occurrence and real-timetraffic and weather characteristics based on four urban arterials in CentralFlorida. Considering the substantial difference between the interrupted urbanarterials and the access controlled freeways, the adaptive signal phasing datawas introduced in addition to the traditional traffic data. Bayesianconditional logistic models were developed by incorporating the Bluetooth,adaptive signal control, and weather data, which were extracted for a period of20 minutes (four 5-minute intervals) before the time of crash occurrence. Modelcomparison results indicated that the model based on 5-10 minute intervaldataset performs the best. It revealed that the average speed, upstreamleft-turn volume, downstream green ratio, and rainy indicator were found tohave significant effects on crash occurrence. Furthermore, both Bayesian randomparameters logistic and Bayesian random parameters conditional logistic modelswere developed to compare with the Bayesian conditional logistic model, and theBayesian random parameters conditional logistic model was found to have thebest model performance in terms of the AUC and DIC values. These results areimportant in real-time safety applications in the context of Integrated ActiveTraffic Management.

Utilizing Bluetooth and Adaptive Signal Control Data for Urban Arterials Safety Analysis