Chih‐Wei Chen

National Center for High-Performance Computing

Papers

1

Total Citations

5

H-Index

1

About

Chih-Wei Chen is a leading researcher in autonomous driving and intelligent transportation systems, with a primary focus on trajectory prediction and proactive safety at complex intersections. His most impactful work introduces a Social Conditional Generative Adversarial Network (SCGAN) for trajectory prediction at unsignalized intersections—a critical challenge for autonomous vehicles. By modeling the social interactions between multiple road users and generating probabilistic future paths, Chen’s approach enables vehicles to anticipate the intentions of pedestrians, cyclists, and other cars, moving beyond deterministic models to capture real-world uncertainty. This work has garnered early citations, reflecting its importance for defensive driving algorithms. Chen’s contributions are foundational for developing safer, more human-like autonomous navigation, directly addressing the need for robust prediction in mixed-traffic environments. His research bridges generative AI and robotics, offering practical solutions for accident prevention. As a rising voice in the field, Chen continues to push the boundaries of how machines understand and anticipate dynamic, unstructured driving scenarios.

Research Focus

Key Achievements

1
H-Index
1
Papers
5
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Trajectory Prediction at Unsignalized Intersections using Social Conditional Generative Adversarial Network
5 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: National Center for High-Performance Computing

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago