This paper proposes a Kalman Filter (KF) technique to predict the short-term flow at urban
arterials based on the information of connected and Bluetooth equipped vehicles. Online …

We develop a Kalman filter for predicting traffic flow at urban arterials based on data
obtained from connected vehicles. The proposed algorithm is computationally efficient and …

Frequent traffic congestion and gridlocks are causing global economies staggering cost in
terms of fuel consumption, time wastage, and public health. To rectify this problem, many …

Short‐term traffic flow forecasting is a fundamental and challenging task since it is required
for the successful deployment of intelligent transportation systems and the traffic flow is …

Traffic flow prediction is an important research problem in many of the Intelligent
Transportation Systems (ITS) applications. The use of Autoregressive Integrated Moving …

Time-dependent origin–destination (OD) matrices are essential input for dynamic traffic
models such as microscopic and mesoscopic traffic simulators. Dynamic traffic models also …

Connected and autonomous vehicles (CAVs) are on the way to the field application. In the
beginning stage, there will be a mixed traffic flow, containing the regular human‐driven …

The sustainable growth of cities created the need for better informed decisions based on
information and communication technologies to sense the city and quantify its pulse. An …

Traditional technologies, such as inductive loop detectors, do not usually produce
measurements of the quality required by real-time applications. Therefore, one wonders …

Traffic state estimation is a challenging problem for the transportation community due to the
limited deployment of sensing infrastructure. However, recent trends in the mobile phone …