Towards computationally efficient and realtime distracted driver detection with mobilevgg network
According to the World Health Organization (WHO) report, the number of road traffic deaths
have been continuously increasing since last few years though the rate of deaths relative to …
have been continuously increasing since last few years though the rate of deaths relative to …
Predicting road crash severity using classifier models and crash hotspots
The rapid increase in traffic volume on urban roads, over time, has altered the global traffic
scenario. Additionally, it has increased the number of road crashes, some of which are …
scenario. Additionally, it has increased the number of road crashes, some of which are …
Exploratory investigation of disengagements and crashes in autonomous vehicles under mixed traffic: An endogenous switching regime framework
ZH Khattak, MD Fontaine… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose
some critical challenges. While AVs may help reduce crashes caused by human error, they …
some critical challenges. While AVs may help reduce crashes caused by human error, they …
FPT: fine-grained detection of driver distraction based on the feature pyramid vision transformer
According to the surveys of the World Health Organization, distracted driving is one of main
causes of road traffic accidents. To improve road traffic safety, real-time detection of drivers' …
causes of road traffic accidents. To improve road traffic safety, real-time detection of drivers' …
What do traffic simulations have to provide for virtual road safety assessment? Human error modeling in traffic simulations
Will Advanced Driving Assistance Systems (ADAS) and Highly Automated Driving (HAD)
perform in the expected manner? Will they actually make road traffic safer, or will they …
perform in the expected manner? Will they actually make road traffic safer, or will they …
[HTML][HTML] Glass half-full: On-road glance metrics differentiate crashes from near-crashes in the 100-Car data
Background Much of the driver distraction and inattention work to date has focused on
concerns over drivers removing their eyes from the forward roadway to perform non-driving …
concerns over drivers removing their eyes from the forward roadway to perform non-driving …
An empirical investigation of driver car-following risk evolution using naturistic driving data and random parameters multinomial logit model with heterogeneity in …
This study aims to address the questions of how driving risk evolves during car-following
processes and what factors contribute to the underlying evolution patterns. An empirical …
processes and what factors contribute to the underlying evolution patterns. An empirical …
An improved vehicle-pedestrian near-crash identification method with a roadside LiDAR sensor
Problem: Potential conflicts between pedestrians and vehicles represent a challenge to
pedestrian safety. Near-crash is used as a surrogate metric for pedestrian safety evaluations …
pedestrian safety. Near-crash is used as a surrogate metric for pedestrian safety evaluations …
Driver monitoring using sparse representation with part-based temporal face descriptors
Many driver monitoring systems (DMSs) have been proposed to reduce the risk of human-
caused accidents. Traditional DMSs focus on detecting specific predefined abnormal driving …
caused accidents. Traditional DMSs focus on detecting specific predefined abnormal driving …
Modeling the imperfect driver: Incorporating human factors in a microscopic traffic model
M Lindorfer, CF Mecklenbraeuker… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
In this paper, we present the enhanced human driver model (EHDM), a time-continuous
microscopic car-following model, which considers numerous characteristics attributable to …
microscopic car-following model, which considers numerous characteristics attributable to …