Crash hot spot identification and prediction using spatial statistics and random forest
methods on the interstate of Michigan are evaluated. The Getis-Ord statistics are adopted to …

In current urban regeneration, the conservation and reuse of traditional village space are
significant measures to activate urban-rural development. Traditional villages in the …

Blackspot identification is a global concern in road safety. The accident-based method has
been widely employed over the past few decades but remains reactive, as it depends on …

In the current data-driven era, large volumes of data of different dimensions are generated
and collected at a rapid rate. Examples of these big data include transportation data (eg …

The Yellow River Basin (YRB) is China's substantial energy consumption base. The issue of
carbon emission efficiency directly affects the ecological protection and high-quality …

Identifying the locations of pedestrian crashes in cities contributes to the full implementation
of sustainable transportation for all road users. This study examines the pedestrian crash …

The transport of freight involves numerous intermediate steps, such as freight consolidation,
truck allocation, and routing, all of which exhibit high day-to-day variability. On the delivery …

Traditional hot spot and cluster analysis techniques based on the Euclidean distance may
not be adequate for assessing high-risk locations related to crashes. This is because …

As car ownership and urbanization continue to rise worldwide, traffic crashes have become
growing concerns globally. Measuring crash risk provides insight into understanding crash …

Road accidents are a major source of trauma worldwide due to increasing numbers of
vehicles and drivers. Considerable data has been collected on road accidents and this is …