Traffic accident detection and condition analysis based on social networking data
Accurate detection of traffic accidents as well as condition analysis are essential to
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …
Analysis of Urban Traffic Incidents through Road Network Features
T Saber, L Capatina… - 2020 IEEE 22nd …, 2020 - ieeexplore.ieee.org
Road traffic prediction is crucial for transport operators. Traffic operators use traffic
simulators with different precision levels (from microscopic to macroscopic simulators) to …
simulators with different precision levels (from microscopic to macroscopic simulators) to …
Riskcast: social sensing based traffic risk forecasting via inductive multi-view learning
Road traffic accidents are a major challenge in urban transportation systems. An effective
countermeasure to address this problem is to accurately forecast the traffic risks in a city …
countermeasure to address this problem is to accurately forecast the traffic risks in a city …
Deeprisk: A deep transfer learning approach to migratable traffic risk estimation in intelligent transportation using social sensing
This paper focuses on the migratable traffic risk estimation problem in intelligent
transportation systems using the social (human-centric) sensing. The goal is to accurately …
transportation systems using the social (human-centric) sensing. The goal is to accurately …
Traffic information mining from social media based on the MC-LSTM-Conv model
Y Wang, Z He, J Hu - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Social media (eg, Sina Weibo) have the advantage of reflecting traffic information, including
the reasons for jams, illegal behaviors, and emergency recourses on roads. However, there …
the reasons for jams, illegal behaviors, and emergency recourses on roads. However, there …
A Novel Short-term Post-accident Traffic Prediction Model
Traffic forecasting at appropriate times is vital for a variety of urban traffic control
applications. There are a plethora of factors that can severely affect the performance of such …
applications. There are a plethora of factors that can severely affect the performance of such …
Toward a social sensor based framework for intelligent transportation
RYK Lau - 2017 IEEE 18th International Symposium on A …, 2017 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITSs) are supposed to constantly provide drivers with
useful navigation information (eg, the shortest driving paths, real-time traffic conditions, and …
useful navigation information (eg, the shortest driving paths, real-time traffic conditions, and …
Keynote speech 3: Big data Computing and Machine Learning for Intelligent Transportation and Connected Vehicles
S Ranka - 2020 Fifth International Conference on Fog and …, 2020 - ieeexplore.ieee.org
We are developing machine learning algorithms and software to fuse real-time feeds from
video cameras and traffic sensor data to generate real-time detection, classification, and …
video cameras and traffic sensor data to generate real-time detection, classification, and …
A multimodal coupled graph attention network for joint traffic event detection and sentiment classification
Traffic events are one of the main causes of traffic accidents, leading to traffic event detection
being a challenging research problem in traffic management and intelligent transportation …
being a challenging research problem in traffic management and intelligent transportation …