Develo** a time-series speed prediction model using Transformer networks for freeway interchange areas
L Wu, Y Wang, J Liu, D Shan - Computers and Electrical Engineering, 2023 - Elsevier
This study investigates the lane-level speed distribution in the freeway interchange area and
develops a time-series speed prediction model using Transformer networks. The full-sample …
develops a time-series speed prediction model using Transformer networks. The full-sample …
Physics-informed neural network for cross-dynamics vehicle trajectory stitching
High-accuracy long-coverage vehicle trajectory data can benefit the investigations of various
traffic phenomena. However, existing datasets frequently contain broken trajectories due to …
traffic phenomena. However, existing datasets frequently contain broken trajectories due to …
Driving behavior classification at signalized intersections using vehicle kinematics: Application of unsupervised machine learning
Driving behavior is considered as a unique driving habit of each driver and has a significant
impact on road safety. This study proposed a novel data-driven Machine Learning …
impact on road safety. This study proposed a novel data-driven Machine Learning …
Does anisotropy hold in mixed traffic conditions?
Traditionally, car-following models have focused on the interaction between leader and
follower vehicles. However, some researchers have explored the significance of …
follower vehicles. However, some researchers have explored the significance of …
Empirical investigation of fundamental diagrams in mixed traffic
A thorough understanding of the fundamental relation of traffic flow variables is critical for the
efficient operation of traffic systems. However, their relationships in mixed traffic are …
efficient operation of traffic systems. However, their relationships in mixed traffic are …
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 …
Modeling car-following behavior during queue discharge at signalized intersections with countdown timer
Countdown timers impact driver behavior significantly and are widely used at signalized
intersections in many countries. Literature shows potential vehicle class-specific temporal …
intersections in many countries. Literature shows potential vehicle class-specific temporal …
Universality of area occupancy-based fundamental diagrams in mixed traffic
Modeling and investigating the properties of fundamental diagrams (FDs) in mixed traffic,
which encompasses heterogeneous with non-lane-based flow, has been one of the …
which encompasses heterogeneous with non-lane-based flow, has been one of the …
Obtaining Long Trajectory Data of Disordered Traffic Using a Swarm of Unmanned Aerial Vehicles
For the development of algorithms and models for driver behaviour at microscopic levels,
trajectory data is needed. Access to trajectory datasets under disordered traffic conditions …
trajectory data is needed. Access to trajectory datasets under disordered traffic conditions …
Scenario-aware clustered federated learning for vehicle trajectory prediction with non-IID data
L Tao, Y Cui, X Zhang, W Shen… - Proceedings of the …, 2024 - journals.sagepub.com
In recent years, Federated Learning (FL) has attracted much attention in Vehicle Trajectory
Prediction (VTP) as it can resolve the critical issues of insufficient data, data privacy, and …
Prediction (VTP) as it can resolve the critical issues of insufficient data, data privacy, and …