In intelligent traffic control systems, the features extracted by loop detectors are insufficient to
accurately impute missing data. Most of the existing imputation methods use only these …

The archived data from traffic sensors are used in a wide range of traffic management
applications. However, missing or invalid data are becoming an important concern. This …

Predicting crash probability in real time is a concept that has inspired studies into complex
modeling methods, exploring more sophisticated data collection methods, reducing …

For the last decades, congestion on highways has been a serious issue. Congestion causes
more air pollution, accidents and delays, resulting in late arrival for employment or meetings …

Road transport solutions depend on the quality of the measurements of the underlying traffic
state. This paper introduces quality indicators that aim at identify the presence of traffic …

One of the prominent problems in introducing autonomous and advanced transportation
technologies to existing traffic network systems is the lack of a framework that constantly …

In this study, we propose an anomaly detection algorithm on sensor traffic data. The
algorithm is composed of three distinct steps: temporal detection, spatial detection, and GPS …

Road transport solutions depend on the quality of the measurements of the underlying traffic
state. This paper introduces quality indicators that aim at identify the presence of traffic …

The inductive loop detectors (ILDs) have been used for many decades to monitor traffic on
highways. They have proven to be highly reliable in collecting traffic volumes, traffic speeds …

The European ITS Platform (EU EIP) has initiated a framework for the quality of Safety-
Related Traffic Information (SRTI) and Real-Time Traffic Information (RTTI) services, as well …