A survey on urban traffic anomalies detection algorithms
This paper reviews the use of outlier detection approaches in urban traffic analysis. We
divide existing solutions into two main categories: flow outlier detection and trajectory outlier …
divide existing solutions into two main categories: flow outlier detection and trajectory outlier …
Bioinspired computational intelligence and transportation systems: a long road ahead
This paper capitalizes on the increasingly high relevance gained by data-intensive
technologies in the development of intelligent transportation system, which calls for the …
technologies in the development of intelligent transportation system, which calls for the …
Proactive safety monitoring: A functional approach to detect safety-related anomalies using unmanned aerial vehicle video data
The advent of smart cities has motivated the field of transportation safety to transition
towards a proactive approach that anticipates and mitigates risks before crashes occur. One …
towards a proactive approach that anticipates and mitigates risks before crashes occur. One …
A comparison of outlier detection algorithms for ITS data
S Chen, W Wang, H van Zuylen - Expert Systems with Applications, 2010 - Elsevier
In order to improve the veracity and reliability of a traffic model built, or to extract important
and valuable information from collected traffic data, the technique of outlier mining has been …
and valuable information from collected traffic data, the technique of outlier mining has been …
Estimating historical hourly traffic volumes via machine learning and vehicle probe data: A Maryland case study
This paper focuses on the problem of estimating historical traffic volumes between sparsely-
located traffic sensors, which transportation agencies need to accurately compute statewide …
located traffic sensors, which transportation agencies need to accurately compute statewide …
Outlier detection in urban traffic data
Y Djenouri, A Zimek - Proceedings of the 8th international conference on …, 2018 - dl.acm.org
This paper provides a summary of the tutorial on outlier detection in urban traffic data. We
present existing solutions in three main categories: statistical techniques, similarity-based …
present existing solutions in three main categories: statistical techniques, similarity-based …
[PDF][PDF] Study Estimating hourly traffic flow using Artificial Neural Network: A M25 motorway case
This paper examines the challenge of accurately computing highway performance
measures by estimating traffic-flow between traffic sensors that are geographically …
measures by estimating traffic-flow between traffic sensors that are geographically …
A framework of abnormal behavior detection and classification based on big trajectory data for mobile networks
H Zhang, Y Luo, Q Yu, L Sun, X Li… - Security and …, 2020 - Wiley Online Library
Big trajectory data feature analysis for mobile networks is a popular big data analysis task.
Due to the large coverage and complexity of the mobile networks, it is difficult to define and …
Due to the large coverage and complexity of the mobile networks, it is difficult to define and …
Development of statewide annual average daily traffic estimation model from short-term counts: A comparative study for South Carolina
Annual Average Daily Traffic (AADT) is an important parameter for traffic engineering
analysis. Departments of Transportation continually collect traffic count using both …
analysis. Departments of Transportation continually collect traffic count using both …
Efficient local AADT estimation via SCAD variable selection based on regression models
B Yang, SG Wang, Y Bao - 2011 Chinese Control and Decision …, 2011 - ieeexplore.ieee.org
In transportation networks, Annual Average Daily Traffic (AADT) estimation is very important
to decision making, planning, air quality analysis, etc. Regression method may be the most …
to decision making, planning, air quality analysis, etc. Regression method may be the most …