Data-driven approaches for road safety: A comprehensive systematic literature review
Road crashes cost over a million lives each year. Consequently, researchers and transport
engineers continue their efforts to improve road safety and minimize road crashes. With the …
engineers continue their efforts to improve road safety and minimize road crashes. With the …
Real-time travel time prediction using particle filtering with a non-explicit state-transition model
The research presented in this paper develops a particle filter approach for the real-time
short to medium-term travel time prediction using real-time and historical data. Given the …
short to medium-term travel time prediction using real-time and historical data. Given the …
[HTML][HTML] A dynamic approach to predict travel time in real time using data driven techniques and comprehensive data sources
Having access to accurate travel time is of great importance for both highway network users
and traffic engineers. The travel time which is currently reported on highways is usually …
and traffic engineers. The travel time which is currently reported on highways is usually …
Spatiotemporal K-Nearest Neighbors Algorithm and Bayesian Approach for Estimating Urban Link Travel Time Distribution From Sparse GPS Trajectories
W Qin, M Zhang, W Li, Y Liang - IEEE Intelligent Transportation …, 2023 - ieeexplore.ieee.org
Travel time distribution (TTD) estimation on urban arterial links with sparse trajectory data is
a practically important while substantially challenging subject. Although several methods …
a practically important while substantially challenging subject. Although several methods …
Constructing spatiotemporal speed contour diagrams: using rectangular or non-rectangular parallelogram cells?
Z He, Y Lv, L Lu, W Guan - Transportmetrica B: transport dynamics, 2019 - Taylor & Francis
ABSTRACT A spatiotemporal speed contour (SSC, or time-space traffic) diagram that
exhibits traffic dynamics in time and space is of importance in transportation research and …
exhibits traffic dynamics in time and space is of importance in transportation research and …
Dynamic travel time prediction using pattern recognition
Travel-time information is an essential part of Advanced Traveler Information Systems
(ATISs) and Advanced Traffic Management Systems (ATMSs). A key component of these …
(ATISs) and Advanced Traffic Management Systems (ATMSs). A key component of these …
A distributed local Kalman consensus filter for traffic estimation
This work proposes a distributed local Kalman consensus filter (DLKCF) for large-scale multi-
agent traffic density estimation. The switching mode model (SMM) is used to describe the …
agent traffic density estimation. The switching mode model (SMM) is used to describe the …
Learning traffic flow dynamics using random fields
This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-
temporal evolution of the probability distributions of vehicle trajectories. The dynamics are …
temporal evolution of the probability distributions of vehicle trajectories. The dynamics are …
A spatiotemporal motion prediction network based on multi-level feature disentanglement
S Chen, Y Bo, X Wu - Image and Vision Computing, 2024 - Elsevier
The prediction task is significantly challenged by the intricate scene information and motion
variations present in spatiotemporal data. Existing prediction methods struggle to accurately …
variations present in spatiotemporal data. Existing prediction methods struggle to accurately …
Random forest travel time prediction algorithm using spatiotemporal speed measurements
Accurate prediction of dynamic travel times can assist commuters in making better travel
decisions. In this paper, a new algorithm is proposed to accurately predict the expected and …
decisions. In this paper, a new algorithm is proposed to accurately predict the expected and …