Haoran Wang (Eric)

Haoran Wang is an experienced transport engineer with a solid foundation in civil engineering. His expertise encompasses various facets of traffic and transport engineering, including traffic signal control, transport research and analytics, transport planning and modeling, and simulation at microscopic, mesoscopic, and macroscopic levels. He is skilled in optimization algorithms, traffic investigation, and transit signal priority (TSP) control, and is proficient in AIMSUN API programming. Haoran is also experienced in traffic and highway engineering, as well as preparing progress reports for projects.

Haoran has accumulated valuable experience in his career, having worked with Metis Consultants and Research & Analytics, alongside his university studies. After three years in the industry, he joined Queensland University of Technology as a full-time PhD student in 2020. During his PhD, he completed a six-month Higher Degree Research internship and another six months as a full-time research assistant for the Old Cleveland Rd Bus Priority Project with Brisbane City Council (BCC). His PhD thesis is titled "Adaptive Group-based Signal Control with Transit Signal Priority (TSP) based on Multi-agent Deep Q-Network Model."

His research interests include traffic signal control, motorway control, ramp metering, transit signal priority (TSP), queue length estimation, and machine learning. Haoran is known for his dedication and attention to detail in his work, and he consistently delivers practical and innovative solutions for transport issues independently.

High-Profile Projects:

• Old Cleveland Rd Bus Priority Project, Brisbane City Council (April 2022- April 2023): High Degree Research internship and full-time research assistant.
• Traffic Investigations for Townsville City Council (June - October 2016): Analyzed over 160 intersections.
• Gold Coast 2018 Commonwealth Games: Implemented real-time 24-hour traffic monitoring systems at entrances/exits for 12 Park and Ride sites.
• University Analytical Project: Determined traffic conditions at intersections by analyzing traffic flow data.