What is he best known for?
The fields of study he is best known for:
- Statistics
- Computer network
- Artificial intelligence
Byungkyu Park mainly investigates Simulation, Traffic simulation, Fuel efficiency, SIGNAL and Microsimulation.
His research integrates issues of Genetic algorithm and Traffic flow in his study of Simulation.
The study incorporates disciplines such as Real-time computing and Traffic signal in addition to Traffic simulation.
His study in Fuel efficiency is interdisciplinary in nature, drawing from both Control and Transport engineering.
Byungkyu Park has included themes like VisSim and Control theory in his Microsimulation study.
The Automotive engineering study combines topics in areas such as Trajectory and Optimal control.
His most cited work include:
- Development and Evaluation of a Cooperative Vehicle Intersection Control Algorithm Under the Connected Vehicles Environment (437 citations)
- Microscopic Simulation Model Calibration and Validation: Case Study of VISSIM Simulation Model for a Coordinated Actuated Signal System (171 citations)
- Short-Term Freeway Traffic Volume Forecasting Using Radial Basis Function Neural Network (135 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Simulation, Traffic simulation, Transport engineering, VisSim and Traffic flow.
The various areas that Byungkyu Park examines in his Simulation study include Control system, Genetic algorithm, Microsimulation and Calibration.
His Traffic simulation research is multidisciplinary, incorporating elements of Real-time computing, Automotive engineering, Vehicle dynamics and Simulation modeling.
Byungkyu Park regularly links together related areas like Fuel efficiency in his Transport engineering studies.
His VisSim research includes elements of Control, CarSim and Calibration.
His Traffic flow research is multidisciplinary, incorporating perspectives in Measure and Engineering research.
He most often published in these fields:
- Simulation (35.00%)
- Traffic simulation (25.50%)
- Transport engineering (25.00%)
What were the highlights of his more recent work (between 2015-2021)?
- Automotive engineering (8.50%)
- Fuel efficiency (10.50%)
- Simulation (35.00%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Automotive engineering, Fuel efficiency, Simulation, Real-time computing and Signal.
He combines subjects such as Throughput, Driving simulator, Optimal control and Market penetration with his study of Automotive engineering.
His biological study spans a wide range of topics, including Control system, Intersection and Traffic congestion.
His Simulation study combines topics in areas such as VisSim, Traffic conditions and Dedicated short-range communications.
His work carried out in the field of VisSim brings together such families of science as Kalman filter, Hardware-in-the-loop simulation and Traffic simulation.
His Real-time computing research incorporates elements of Linear programming, Optimal control algorithm, Cooperative Adaptive Cruise Control and Trajectory.
Between 2015 and 2021, his most popular works were:
- Parsimonious shooting heuristic for trajectory design of connected automated traffic part II: Computational issues and optimization (92 citations)
- Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment (81 citations)
- Optimal Control for Speed Harmonization of Automated Vehicles (53 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Computer network
His primary scientific interests are in Automotive engineering, Simulation, Travel time, Mathematical optimization and Fuel efficiency.
Byungkyu Park has researched Automotive engineering in several fields, including Computation, Throughput and Trajectory.
In general Simulation, his work in Headway is often linked to Intersection linking many areas of study.
His studies in Travel time integrate themes in fields like Artificial neural network, Support vector machine, Artificial intelligence and Data mining.
In the subject of general Mathematical optimization, his work in Trajectory optimization and Heuristic is often linked to SIGNAL and Subroutine, thereby combining diverse domains of study.
His Fuel efficiency research is multidisciplinary, relying on both Intersection, Market penetration, Optimal control and Traffic flow.
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