Short-term prediction is one of the essential elements of intelligent transportation systems
(ITS). Although fine prediction methodologies have been reported, most prediction methods …

Predictions of fundamental traffic variables in the short-term or near-term future are vital for
any successful dynamic traffic management application. Univariate short-term traffic flow …

Short-term traffic prediction can be defined as the process of estimating the anticipated traffic
conditions in the short-term future given historical and current traffic information (Vlahogianni …

Short-term traffic prediction provides tools for improved road management by allowing the
reduction of delays, incidents and other unexpected events. Different real-time approaches …

The ability to timely and accurately forecast the evolution of traffic is very important in traffic
management and control applications. This paper proposes a non-parametric and data …

In the last two decades, the growing need for short‐term prediction of traffic parameters
embedded in a real‐time intelligent transportation systems environment has led to the …

The k-nearest neighbor (KNN) model is an effective statistical model applied in short-term
traffic forecasting that can provide reliable data to guide travelers. This study proposes an …

Short‐term traffic flow prediction is fundamental for the intelligent transportation system and
is proved to be a challenge. This paper proposed a hybrid strategy that is general and can …

The literature on short-term traffic flow forecasting has undergone great development
recently. Many works, describing a wide variety of different approaches, which very often …

Short-term traffic flow forecasting is a key step to achieve the performance of intelligent
transportation system (ITS). Timely and accurate traffic information prediction is also the …