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Road Anomaly Detection with Group Intelligence Perception
2019 International Conference on Communications, Information System and Computer Engineering (CISCE), 2019we consider a collection of the actual combat training of the troops that continues to deepen, and the use of training vehicles is becoming more frequent. We study the problem of detecting abnormal road surface, which may lead to traffic safety accidents and damage to the troops and officers and soldiers.
WenChen Wang +4 more
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Road anomaly estimation: Model based pothole detection
2015 American Control Conference (ACC), 2015This paper describes a model-based pothole detection algorithm that exploits a multi-phase dynamic model. The responses of hitting potholes are empirically broken down into three phases governed by three simpler dynamic system sub-models. Each sub-model is based on a rigid-ring tire and quarter-car suspension model.
Zhaojian Li +4 more
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A crowdsourcing-based road anomaly classification system
2016 18th Asia-Pacific Network Operations and Management Symposium (APNOMS), 2016Road networks are the most important facility to the public transportation in modern cities. Governments around the world allocate large amounts of budgets for the pavement maintenance every year. In this paper, we proposed a crowdsourcing solution to categorize road anomalies into safety related anomalies such as speed bumps and rumble strips, and ...
Ru-Yu Wang, Yi-Ta Chuang, Chih-Wei Yi
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Recognizing Driving Behavior and Road Anomaly using Smartphone Sensors
International Journal of Ambient Computing and Intelligence, 2017Road traffic accidents are caused 1.25 million deaths per year worldwide. To improve road safety and reducing road accidents, a recognition method for driving events is introduced in this paper. The proposed method detected and classified both driving behaviors and road anomalies patterns based on smartphone sensors (accelerometer and gyroscope).
Aya Hamdy Ali +2 more
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Road Anomaly Classification for Low-Cost Road Maintenance and Route Quality Maps
2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2019Traditional road maintenance methods are costly; requiring expensive equipment and manpower. Road quality categorization based on machine learning techniques, using real-time opportunistic data gathered from inexpensive open-source inertial systems, is a promising alternative.
Naufil Hassan +3 more
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Monitoring road surface anomalies towards dynamic road mapping for future smart cities
2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2017The development of Smart Cities aims to transform city infrastructures and services through the use of information and communication technologies. One aspect of Smart City applications is the demand for more efficient and safe transportation systems.
Amr S. El-Wakeel +4 more
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Anomaly detection in driving behaviour by road profiling
2013 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 2013This paper presents a statistical method for detecting anomalous driving behavior by analyzing cross-sectional profiles of the road. A profile captures the way vehicles normally traverse the road; a statistical hypothesis test determines whether the observed behavior is anomalous.
Gabriel Agamennoni +3 more
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Inspect Road Quality by Using Anomaly Detection Approach
2018 International Conference on System Science and Engineering (ICSSE), 2018Road quality can be representative of a country's development status, affect transportation speeds and traveler safety. However, there is no standard or set of rules to protect people from the dangers of damaged roads. This study proposes a method for evaluating road quality, which has been made possible by the recent rapid development of information ...
Yu-Lin Jeng +2 more
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Inferring the Root Cause in Road Traffic Anomalies
2012 IEEE 12th International Conference on Data Mining, 2012We propose a novel two-step mining and optimization framework for inferring the root cause of anomalies that appear in road traffic data. We model road traffic as a time-dependent flow on a network formed by partitioning a city into regions bounded by major roads.
Sanjay Chawla, Yu Zheng, Jiafeng Hu
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Vehicle road departure detection using anomalies in dynamics
2016 American Control Conference (ACC), 2016This research investigates the viability of detecting vehicle road departure via the measurements of anomalies in vehicle dynamics, especially under conditions when left and right tires experience imbalance of forces (split-μ condition). This approach is based on established low-order vehicle models to facilitate real-time implementation.
Hang Yang +4 more
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