What are the leading causes of fatal and severe injury crashes involving older pedestrian? Evidence from Bayesian network model
Introduction: Identifying factors contributing to the risk of older pedestrian fatal/severe
injuries, along with their possible interdependency, is the first step towards improving safety …
injuries, along with their possible interdependency, is the first step towards improving safety …
Entropy-based traffic flow labeling for CNN-based traffic congestion prediction from meta-parameters
MZ Mehdi, HM Kammoun, NG Benayed… - IEEE …, 2022 - ieeexplore.ieee.org
Traffic congestion affects quality of life by inducing frustration and wasting time. The
congestion is also critical to vehicles with high emergencies such as ambulances or police …
congestion is also critical to vehicles with high emergencies such as ambulances or police …
A Bayesian clustering ensemble Gaussian process model for network-wide traffic flow clustering and prediction
Traffic flow prediction is an essential component in intelligent transportation systems.
Recently, there has been a notable trend in applying machine learning models, especially …
Recently, there has been a notable trend in applying machine learning models, especially …
Mixed traffic flow state detection: A connected vehicles-assisted roadside radar and video data fusion scheme
An increasing number of connected vehicles (CVs) driving together with regular vehicles
(RVs) on the road is an inevitable stage of future traffic development. As accurate traffic flow …
(RVs) on the road is an inevitable stage of future traffic development. As accurate traffic flow …
Evaluating capacity of transportation operations with highway travel time reliability
Highway traffic congestion is often considered part of routine operations and is anticipated
with transportation travel times; however, severe and unexpected delays cause disruption to …
with transportation travel times; however, severe and unexpected delays cause disruption to …
Estimating the mobility benefits of adaptive signal control technology using a Bayesian switch-point regression model
The adaptive signal control technology (ASCT) is a traffic management strategy that adjusts
signal timing parameters to optimize corridor performance based on actual traffic demand …
signal timing parameters to optimize corridor performance based on actual traffic demand …
Developing Florida-specific mobility enhancement factors (MEFs) and crash modification factors (CMFs) for TSM&O strategies
Transportation Systems Management and Operations (TSM&O) focus on improving the
safety and operational performance of the transportation network by integrating proven …
safety and operational performance of the transportation network by integrating proven …
Examining the impact of adverse weather on travel time reliability of urban corridors in Shanghai
Y Zou, T Zhu, Y Xie, L Li, Y Chen - Journal of Advanced …, 2020 - Wiley Online Library
Travel time reliability (TTR) is widely used to evaluate transportation system performance.
Adverse weather condition is an important factor for affecting TTR, which can cause traffic …
Adverse weather condition is an important factor for affecting TTR, which can cause traffic …
Bayesian regression approach to estimate speed threshold under uncertainty for traffic breakdown event identification
This study aims at developing a robust Bayesian statistical approach to determine the speed
threshold (ST) for detecting a traffic breakdown event using traffic flow parameters. Data …
threshold (ST) for detecting a traffic breakdown event using traffic flow parameters. Data …
[图书][B] Evaluating the mobility and safety benefits of adaptive signal control technology (ASCT)
JH Kodi - 2019 - search.proquest.com
Abstract The Adaptive Signal Control Technology (ASCT) is a traffic management strategy
that optimizes signal timing based on real-time traffic demand. This thesis proposes a …
that optimizes signal timing based on real-time traffic demand. This thesis proposes a …