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/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study presents a method for the identification of hazardous situations on the freeways. The hazard identification is done using a crash risk probability model. For this study, about 18 km long section of Eastern Freeway in Melbourne (Australia) is selected as a test bed. Two categories of data i.e. traffic and accident record data are used for the analysis and modelling. In developing the crash risk probability model, Hazard Prediction Index is formulated in this study by the differences of traffic parameters with threshold values. Seven different prediction indices are examined and the best one is selected as crash risk probability model based on prediction error minimisation.

DEVELOPMENT OF A CRASH RISK PROBABILITY MODEL FOR FREEWAYS BASED ON HAZARD PREDICTION INDEX