Purpose The objective of this research is to provide an overview of emerging data collection
technologies and their impact on traffic management applications. Methods Several existing …

Traffic state estimation is a crucial elemental function in Intelligent Transportation Systems
(ITS). However, the collected traffic state data are often incomplete in the real world. In this …

We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …

Short‐term traffic speed prediction is one of the most critical components of an intelligent
transportation system (ITS). The accurate and real‐time prediction of traffic speeds can …

As an important task for the management of bike sharing systems, accurate forecast of travel
demand could facilitate dispatch and relocation of bicycles to improve user satisfaction. In …

Simultaneous perturbation stochastic approximation (SPSA) is an efficient and well
established optimization method that approximates gradients from successive objective …

The accurate prediction of travel times is desirable but frequently prone to error. This is
mainly attributable to both the underlying traffic processes and the data that are used to infer …

Nowadays, new mobility information can be derived from advanced traffic surveillance
systems that collect updated traffic measurements, both in fixed locations and over specific …

Agent-based microscopic traffic simulation models are gaining popularity over traditional trip-
based traffic models due to their superiority in modeling household member interaction, car …

Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented
with a particular focus on its adaptive features. The pursued general approach to the real …