Fusion of engineering insights and emerging trends: Intelligent urban traffic management system
Traffic congestion is a great concern, especially in urban areas where the vehicles' number
on roads continues to intensify significantly against the slow development of road …
on roads continues to intensify significantly against the slow development of road …
[HTML][HTML] Applications of deep learning in congestion detection, prediction and alleviation: A survey
Detecting, predicting, and alleviating traffic congestion are targeted at improving the level of
service of the transportation network. With increasing access to larger datasets of higher …
service of the transportation network. With increasing access to larger datasets of higher …
[HTML][HTML] Smart cities: Fusion-based intelligent traffic congestion control system for vehicular networks using machine learning techniques
Smart cities have been developed over the past decade, and reducing traffic congestion has
been the top concern in smart city development. Short delays in communication between …
been the top concern in smart city development. Short delays in communication between …
Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
Driving safety is the most important element that needs to be considered for autonomous
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
Risk assessment based collision avoidance decision-making for autonomous vehicles in multi-scenarios
In this paper, we proposed a new risk assessment based decision-making algorithm to
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …
guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic …
Aide: A vision-driven multi-view, multi-modal, multi-tasking dataset for assistive driving perception
Driver distraction has become a significant cause of severe traffic accidents over the past
decade. Despite the growing development of vision-driven driver monitoring systems, the …
decade. Despite the growing development of vision-driven driver monitoring systems, the …
A temporal–spatial deep learning approach for driver distraction detection based on EEG signals
Distracted driving has been recognized as a major challenge to traffic safety improvement.
This article presents a novel driving distraction detection method that is based on a new …
This article presents a novel driving distraction detection method that is based on a new …
A vehicle rollover evaluation system based on enabling state and parameter estimation
There is an increasing awareness of the need to reduce the traffic accidents and fatality
rates due to vehicle rollover incidents. The accurate detection of impending rollover is …
rates due to vehicle rollover incidents. The accurate detection of impending rollover is …
On-road driver emotion recognition using facial expression
H Xiao, W Li, G Zeng, Y Wu, J Xue, J Zhang, C Li… - Applied Sciences, 2022 - mdpi.com
With the development of intelligent automotive human-machine systems, driver emotion
detection and recognition has become an emerging research topic. Facial expression-based …
detection and recognition has become an emerging research topic. Facial expression-based …
Analysis of the injury severity of motor vehicle–pedestrian crashes at urban intersections using spatiotemporal logistic regression models
This paper conducted a comprehensive study on the injury severity of motor vehicle–
pedestrian crashes at 489 urban intersections across a dense road network based on high …
pedestrian crashes at 489 urban intersections across a dense road network based on high …