Xiaobo Qu

Chair Professor

Chalmers University of Technology

Sweden

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About

Professor Xiaobo Qu is a Chair Professor at Chalmers University of Technology in Sweden. His research interests encompass urban air mobility, vehicle perception technologies, and advanced strategies for traffic and transportation systems, as reflected in his recent publications. His work addresses innovative solutions for intelligent vehicles, including the calibration methods for sensor technologies and efficient traffic management using connected autonomous vehicles.

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Collaborators (3)

Yang Liu

Chalmers tekniska högskola

SWEDEN

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Cheng Lyu

Technical University of Munich

GERMANY

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Klaus Hubacek

Professor

University of Groningen

NETHERLANDS

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Xiaobo Qu

Research Interests

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About

Articles (28)

The potential for differentiated vehicle segment tariffs

Flying cars and urban air mobility: Redefining cities in three dimensions

Communicating with two vehicles immediately ahead boosts traffic capacity sixfold in connected autonomous vehicle platoons

Big Data-Driven Advancements and Future Directions in Vehicle Perception Technologies: From Autonomous Driving to Modular Buses

A High-Precision Calibration and Evaluation Method Based on Binocular Cameras and LiDAR for Intelligent Vehicles

AEFusion: An Attention-Based Ensemble Learning Approach for BEV Fusion Perception in Autonomous Modular Buses

Event triggered cooperative trajectory coordination for platooning among heterogeneous vehicles

A Survey and Comprehensive Taxonomy of Tire-Road Adhesion Coefficient Estimation for Intelligent Vehicles

Economic Operation Strategy for Fast Charging Station Assisted by HESS Consisting of Retired Batteries Considering Concurrent Decommissioning

Utilizing eVTOL Aircraft to Alleviate Traffic Congestion on an Arterial Road

Exploring the benefits of personal rapid transit in metropolitan area

Enhancing State Representation in Multi-Agent Reinforcement Learning for Platoon-Following Models

Erratum for “Multiple Emergency Vehicle Priority in a Connected Vehicle Environment: A Cooperative Method”

Delay-throughput tradeoffs for signalized networks with finite queue capacity

Formation control of multi-agent systems with actuator saturation via neural-based sliding mode estimators

An Universal Crack Detection Framework for Intelligent Road-Perceptive Vehicles

Enhanced Scene Understanding and Situation Awareness for Autonomous Vehicles Based on Semantic Segmentation

Improving Freeway Merging Efficiency via Flow-Level Coordination of Connected and Autonomous Vehicles

What's next for battery-electric bus charging systems

Predictability of Vehicle Fuel Consumption Using LSTM: Findings from Field Experiments

Lifecycle Cost Optimization for Electric Bus Systems With Different Charging Methods: Collaborative Optimization of Infrastructure Procurement and Fleet Scheduling

On the Impact of Prior Experiences in Car-Following Models: Model Development, Computational Efficiency, Comparative Analyses, and Extensive Applications

Urban aerial mobility: Network structure, transportation benefits, and Sino-US comparison

Urban aerial mobility: Reshaping the future of urban transportation

A Context-Aware Framework for Risky Driving Behavior Evaluation Based on Trajectory Data

Optimization of Electric Bus Scheduling for Mixed Passenger and Freight Flow in an Urban-Rural Transit System

Deep adaptive control: Deep reinforcement learning-based adaptive vehicle trajectory control algorithms for different risk levels

Multiple Emergency Vehicle Priority in a Connected Vehicle Environment: A Cooperative Method

Collaborators (3)

Yang Liu

Cheng Lyu

Klaus Hubacek

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