Kun Gao
Kun Gao is an Assistant Professor and Research Area Leader 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 and connected mobility, and data-driven methods. 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 JPI Urban Europe, FORMAS, Swedish Innovation Agency, Swedish Energy Agency, and Chalmers AoA Transport/Energy.
Showing 70 publications
Multisensor Information Fusion: Future of Environmental Perception in Intelligent Vehicles
Data-driven rolling eco-speed optimization for autonomous vehicles
An intelligent optimization method for the facility environment on rural roads
Enhancing State Representation in Multi-Agent Reinforcement Learning for Platoon-Following Models
Enhancing choice-set generation and route choice modeling with data- and knowledge-driven approach
Bi-level ramp merging coordination for dense mixed traffic conditions
Delay-throughput tradeoffs for signalized networks with finite queue capacity
Generative Edge Intelligence for IoT-Assisted Vehicle Accident Detection: Challenges and Prospects
Data-driven optimization for rebalancing shared electric scooters
Smart Transportation Systems 2024 - Proceedings of 7th KES-STS International Symposium
Deciphering spatial heterogeneity of maritime accidents considering impact scale variations
Preface - Smart Transportation Systems 2024, Proceedings of 7th KES-STS International Symposium.
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
Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction
Driving Style Recognition Incorporating Risk Surrogate by Support Vector Machine
Cumulative prospect theory coupled with multi-attribute decision making for modeling travel behavior
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
Download publication list
You can download this list to your computer.
Filter and download publication list
As logged in user (Chalmers employee) you find more export functions in MyResearch.
You may also import these directly to Zotero or Mendeley by using a browser plugin. These are found herer:
Zotero Connector
Mendeley Web Importer
The service SwePub offers export of contents from Research in other formats, such as Harvard and Oxford in .RIS, BibTex and RefWorks format.
Showing 16 research projects
Data-driven planning of transport consumption and promotion of micromobility
Digital solution for parking and charging management of shared micromobility
Adaptive and Network-Level Traffic Signal Control for Sustainable Traffic Management (ANTSC)
Uncertainty-aware and safety-enhanced management of CAVs for safer mixed traffic
Electrifying multimodal public transport with distributed renewable energy (e-REMPT)
Secure 5G/6G radio positioning and sensing for transport systems
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