Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...

The performance of many traffic control strategies depends on how much the traffic flow models have been accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive ...

A method is developed to determine how crash characteristics are related to traffic flow conditions at the time of occurrence. Crashes are described in terms of the type and location of the collision, the number of vehicles involved, movements of these vehicles prior to collision, and severity. Traffic flow is characterized by central tendencies and variations of traffic flow and flow/occupancy...

Vehicle automation and communication technologies are considered promising approaches to improve operational driving behavior. The expected gradual implementation of autonomous vehicles (AVs) shortly will cause unique impacts on the traffic flow characteristics. This paper focuses reviewing under a mixed environment AVs regular (RVs) considering different AV includes policy implication discussi...

the performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. one of the most applicable traffic flow model in traffic control and management is lwr or metanet model. practically, key parameters in lwr model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...

This paper presents the confounding socket, a mechanism that makes real-time flow classification computationally infeasible by masking the protocol structure of any application’s network traffic. Current commercial QoS systems rely on well-known application characteristics such as port ranges and protocol characteristics to provide admission control. The confounding socket invalidates these cri...

The performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...

This paper discusses the application of space–time autoregressive integrated moving average (STARIMA) methodology for representing traffic flow patterns. Traffic flow data are in the form of spatial time series and are collected at specific locations at constant intervals of time. Important spatial characteristics of the space–time process are incorporated in the STARIMA model through the use o...

A promising way to capture the characteristics of changing traffic is to extract significant flow clusters in traffic. However, clustering flows by 5-tuple requires flow matching in huge flow attribute spaces, and thus, is difficult to perform on the fly. We propose an efficient yet flexible flow aggregation technique for monitoring the dynamics of network traffic. Our scheme employs twostage f...