2024 Hong Kong Society for Transportation Studies (HKSTS)
Optimizing dynamic allocation of dedicated lanes for crowd movements in urban transportation networks (이소연)
We propose a framework for optimizing dynamic lanes (DL) for pedestrians in mixed traffic networks involving vehicles and pedestrians, using a Mixed-Integer Linear Programming (MILP) model.
A bi-level recursive calibration approach for pedestrian microscopic behavioral models with crowd density dynamics (이소연)
This study introduces an advanced calibration methodology for microscopic pedestrian dynamic models, integrating an unsupervised machine learning approach with a Genetic Algorithm (GA).
Priority-based charging strategy for autonomous mobile robotic chargers for electric vehicles (서문정)
This study proposes a priority-based charging strategy using autonomous mobile robotic chargers, utilizing the dynamic vehicle routing problem.
A group-based adaptive emergency vehicle priority signal system (홍슬빈)
This study proposes the GAEVP system to reduce travel times for both EVs and normal traffic and integrates adaptive signal control with EVP preemptively switching signals to green 100 meters before an EV reaches the intersection.
A bi-level calibration framework of microscopic traffic flow models for inconstant maneuvers of drivers (남혁주)
The purposes of this study are to build a bi-level, iterative framework that calibrates parameters of Intelligent Driver Model that varies along the dynamic traffic flow states.
Integrating a time-dependent reactive local signal control policy with queue-based green light optimal speed advisory (Q-GLOSA) systems (김도현)
Integrating an adaptive traffic control system that reconstructs the signal structure based on traffic demand for each cycle, max-pressure, and a queue-based GLOSA algorithm.