Yingshi Guo

Orcid: 0000-0001-9384-7558

According to our database1, Yingshi Guo authored at least 20 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Trajectory Planning for Automated Merging Vehicles on Freeway Acceleration Lane.
IEEE Trans. Veh. Technol., November, 2024

Long and short-term characteristics of motion sickness: a test track investigation in a passenger car.
Cogn. Technol. Work., June, 2024

Driver Lane-Changing Intention Recognition Based on Stacking Ensemble Learning in the Connected Environment: A Driving Simulator Study.
IEEE Trans. Intell. Transp. Syst., February, 2024

Driving Maneuver Detection at Intersections for Connected Vehicles: A Micro-Cluster-Based Online Adaptable Approach.
IEEE Trans. Intell. Transp. Syst., February, 2024

What Challenges Does the Full-Touch HMI Mode Bring to Driver's Lateral Control Ability? A Comparative Study Based on Real Roads.
IEEE Trans. Hum. Mach. Syst., February, 2024

2023
Passenger non-driving related tasks detection using a light weight neural network based on human prior knowledge and soft-hard feature constraints.
Expert Syst. Appl., June, 2023

Comparing the Effects of Visual Distraction in a High-Fidelity Driving Simulator and on a Real Highway.
IEEE Trans. Intell. Transp. Syst., April, 2023

2022
Turning Maneuver Prediction of Connected Vehicles at Signalized Intersections: A Dictionary Learning-Based Approach.
IEEE Internet Things J., 2022

2021
Lane change strategy analysis and recognition for intelligent driving systems based on random forest.
Expert Syst. Appl., 2021

Computational Analysis of Behavioral Intervention for the Acceptance of Automated Driving Technology.
Proceedings of the EITCE 2021: 5th International Conference on Electronic Information Technology and Computer Engineering, Xiamen, China, October 22, 2021

2020
Improving the User Acceptability of Advanced Driver Assistance Systems Based on Different Driving Styles: A Case Study of Lane Change Warning Systems.
IEEE Trans. Intell. Transp. Syst., 2020

Research on a Cognitive Distraction Recognition Model for Intelligent Driving Systems Based on Real Vehicle Experiments.
Sensors, 2020

Human-Like Obstacle Avoidance Trajectory Planning and Tracking Model for Autonomous Vehicles That Considers the Driver's Operation Characteristics.
Sensors, 2020

Research on the Influence of Vehicle Speed on Safety Warning Algorithm: A Lane Change Warning System Case Study.
Sensors, 2020

Cyclist detection and tracking based on multi-layer laser scanner.
Hum. centric Comput. Inf. Sci., 2020

Do situational or cognitive factors contribute more to risky driving? A simulated driving study.
Cogn. Technol. Work., 2020

Factors Influencing the User Acceptance of Automated Vehicles Based on Vehicle-Road Collaboration.
IEEE Access, 2020

2019
The Impact of Cognitive Distraction on Driver Perception Response Time Under Different Levels of Situational Urgency.
IEEE Access, 2019

Improved Car-Following Strategy Based on Merging Behavior Prediction of Adjacent Vehicle From Naturalistic Driving Data.
IEEE Access, 2019

2010
Simulation and optimization of angle characteristic model for steer by wire system.
Proceedings of the Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010


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