Kun Gao
Kun Gao is an Assistant Professor in the Urban Mobility Systems research group, Division of Geology and Geotechnics, Department of Architecture and Civil Engineering. His research works on promoting sustainable mobility with focuses on electrification, shared mobility, and connected automation. Special interests are attached to establishing new approaches and tools for system planning, optimization and evaluation of emerging transport systems leveraging big data and machine learning. The overall goal is to facilitate the development of a safer, more sustainable and equitable transportation system. His research in above areas has been supported by Chalmers AoA Transport/Energy, Swedish Energy Agency, CHAIR, and Swedish Innovation Agency Vinnova.
Showing 51 publications
Data-driven rolling eco-speed optimization for autonomous vehicles
Enhancing State Representation in Multi-Agent Reinforcement Learning for Platoon-Following Models
Bi-level ramp merging coordination for dense mixed traffic conditions
Delay-throughput tradeoffs for signalized networks with finite queue capacity
A spatio-temporal deep learning model for short-term bike-sharing demand prediction
LSTM-Based Vehicle Trajectory Prediction Using UAV Aerial Data
A Context-Aware Framework for Risky Driving Behavior Evaluation Based on Trajectory Data
Optimizing the Deployment of Automated Speed Camera at the Intersections Using GPS Trajectories
Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers
Adaptive Collision-Free Trajectory Tracking Control for String Stable Bidirectional Platoons
Autonomous vehicle fleets for public transport: scenarios and comparisons
Data and Code Disclosure and Sharing Policy of communications in transportation research
Cumulative prospect theory coupled with multi-attribute decision making for modeling travel behavior
Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction
Driving Style Recognition Incorporating Risk Surrogate by Support Vector Machine
Diverging effects of subjective prospect values of uncertain time and money
Modeling Commercial Vehicle Drivers’ Acceptance of Forward Collision Warning System
Modeling Measurements Towards Effect of Past Behavior on Travel Behavior
Modelling the Relationships Between Headway and Speed in Saturation Flow of Signalised Intersections
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Showing 11 research projects
Electrifying multimodal public transport with distributed renewable energy (e-REMPT)
Digital solutions for sustainable planning and management of shared micromobility using Big Data
Electric Multimodal Transport Systems for Enhancing Urban Accessibility and Connectivity (eMATS)
Analyzing and promoting micro-shared mobility system leveraging big data
Battery Ageing Prediction and Optimization in a Fleet of Electric Autonomous Vehicles
AI-cloud-based Vehicle Management Strategies for Electrified Vehicles
Online Lithium-ion Battery State of Health Prognostics (LiBSoHP)
ICV-Safe: Testing safety of intelligent connected vehicles in open and mixed road environment