Driver behavior modeling towards autonomous vehicles: Comprehensive review
Driver behavior models have been used as input to self-coaching, accident prevention
studies, and developing driver-assisting systems. In recent years, driver behavior …
studies, and developing driver-assisting systems. In recent years, driver behavior …
Driver behavior classification: a systematic literature review
Driver behavior is receiving increasing attention because of the staggering number of road
accidents. Many road safety reports regard human behavior as the most important factor in …
accidents. Many road safety reports regard human behavior as the most important factor in …
Vehicles driving behavior recognition based on transfer learning
Due to the complexity of experiments to test driving behaviors and the high cost of data
collection for some types of vehicles, eg, heavy-duty freight vehicles, it is normally hard to …
collection for some types of vehicles, eg, heavy-duty freight vehicles, it is normally hard to …
Intersense: An XGBoost model for traffic regulator identification at intersections through crowdsourced GPS data
Digital maps of the transportation network are the foundation of future mobility solutions.
Autonomous and connected vehicles rely on real-time, at-scale updating of the environment …
Autonomous and connected vehicles rely on real-time, at-scale updating of the environment …
Analysis of mobile phone use engagement during naturalistic driving through explainable imbalanced machine learning
While driver distraction remains an issue in modernized societies, technological
advancements in data collection, storage and analysis provide the means for deeper …
advancements in data collection, storage and analysis provide the means for deeper …
Smartphone Inertial Measurement Unit Data Features for Analyzing Driver Driving Behavior
K Kanwal, F Rustam, R Chaganti… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Driving behavior is an important aspect of maintaining and sustaining safe transport on the
roads. It also directly affects fuel consumption, traffic flow, public health, and air pollution …
roads. It also directly affects fuel consumption, traffic flow, public health, and air pollution …
Driver maneuver detection and analysis using time series segmentation and classification
A Aboah, Y Adu-Gyamfi, SV Gursoy… - … engineering, Part A …, 2023 - ascelibrary.org
The current paper implements a methodology for automatically detecting vehicle maneuvers
from vehicle telemetry data under naturalistic driving settings. Previous approaches have …
from vehicle telemetry data under naturalistic driving settings. Previous approaches have …
New LSTM deep learning algorithm for driving behavior classification
N Kadri, A Ellouze, M Ksantini… - Cybernetics and Systems, 2023 - Taylor & Francis
Road safety is an important topic of interest around the world. The road traffic accidents
claim more than 1.2 million lives and cause as many as 50 million injuries each year without …
claim more than 1.2 million lives and cause as many as 50 million injuries each year without …
[HTML][HTML] Using reputation scores to foster car-sharing activities
MN Postorino, GML Sarnè - Sustainability, 2023 - mdpi.com
In the near future, the growth of personal mobility is expected to continue all over the world
and to cause impacts such as increased levels of traffic congestion and worsened quality of …
and to cause impacts such as increased levels of traffic congestion and worsened quality of …
Smart edge-based driver drowsiness detection in mobile crowdsourcing
Traffic accidents caused by drowsy drivers represent a crucial threat to public safety. Recent
statistics show that drowsy drivers cause an estimated 15.5% of fatal accidents. With the …
statistics show that drowsy drivers cause an estimated 15.5% of fatal accidents. With the …