Rapid economic development has brought with it an increase in traffic demand and, as a
result, serious traffic problems (eg, congestion, air pollution, and road accidents). Intelligent …

The complexity of traffic scenarios, the spatial-temporal feature correlations pose higher
challenges for traffic prediction research. Traffic spatial-temporal model is an essential …

Sensing network-wide traffic information is fundamental for the sustainable development of
urban planning and traffic management. However, owing to the limited budgets or device …

Connected and automated vehicles (CAVs) are expected to reshape traffic flow dynamics
and present new challenges and opportunities for traffic flow modeling. While numerous …

Compared to the heterogeneous traffic flow on roads, the heterogeneous characteristics of
maritime traffic flow are more pronounced, due to disparities in the manoeuvrability, size …

Capacity drop (CD) at overloaded bottlenecks is a puzzling traffic flow phenomenon with
some internal and complicated mechanisms at the microscopic level. Capacity drop is not …

The study of road traffic flow theory utilizes physics and applied mathematics to analyze
relevant parameters and their relationships quanlitatively and quantitatively, in order to …

Estimating traffic flow models, such as speed-density relationships, using data from multiple
sources with different temporal resolutions is a prevalent challenge encountered in real …

Overloading of network structures is a problem that we encounter every day in many areas
of life. The most associative structure is the transport graph. In many megacities around the …

In normal car-following (CF) states, the minimum safe braking distance (MSBD) is virtually
an unmeasurable variable, mainly due to the diversity of drivers' reaction times and vehicles' …