There has been an increasing interest in recent years in using clustering analysis for the
identification of traffic patterns that are representative of traffic conditions in support of …

Traffic volume estimation at the city scale is an important problem useful to many
transportation operations and urban applications. This paper proposes a hybrid framework …

There is a large amount of literature about the traffic flow forecasting and most existing
studies focus on prediction algorithm itself. However, how to select the appropriate historical …

Forecasting short-term traffic flow is one critical component in traffic management to improve
operational efficiency. Data driven method, which trains the predictor with historical data …

Abstract Developed by the United States Green Building Council, Leadership in Energy and
Environmental Design (LEED) is a credit-based rating system that provides third-party …

The millimeter‐wave radar sensor is widely used for urban traffic surveillance because of its
weather resistance and high detection accuracy. Methods such as fuzzy theory, pattern …

Three pattern recognition methods were applied to classify freeway traffic flow conditions on
the basis of flow characteristics. The methods are K-means, fuzzy C-means, and CLARA …

Short-term traffic flow forecasting is crucial for proactive traffic management and control. One
key issue associated with the task is how to properly define and capture the temporal …

Rapid advancements in traffic monitoring and sensing technologies have permitted the
multiplex and democratized gathering of numerous traffic data (eg speed, volume), depicting …

Forecasting daily traffic flow in the future is one of the most critical components in traffic
management to improve operational efficiency. This article aims to address the daily traffic …