16 citations · 22 across the 5 of their papers we have counts for
5 papers
Predicting Pedestrian Crossing Behavior in Germany and Japan: Insights into Model Transferability
Chi Zhang, Janis Sprenger, Zhongjun Ni +1
Predicting pedestrian crossing behavior is important for intelligent traffic systems to avoid pedestrian-vehicle collisions. Most existing pedestrian crossing behavior models are t…
Predicting and Analyzing Pedestrian Crossing Behavior at Unsignalized Crossings
Chi Zhang, Janis Sprenger, Zhongjun Ni +1
Understanding and predicting pedestrian crossing behavior is essential for enhancing automated driving and improving driving safety. Predicting gap selection behavior and the use o…
Investigating ChatGPT's Potential to Assist in Requirements Elicitation Processes
Krishna Ronanki, Christian Berger, Jennifer Horkoff
Natural Language Processing (NLP) for Requirements Engineering (RE) (NLP4RE) seeks to apply NLP tools, techniques, and resources to the RE process to increase the quality of the re…
ChatGPT as a tool for User Story Quality Evaluation: Trustworthy Out of the Box?
Krishna Ronanki, Beatriz Cabrero-Daniel, Christian Berger
In Agile software development, user stories play a vital role in capturing and conveying end-user needs, prioritizing features, and facilitating communication and collaboration wit…
Cross or Wait? Predicting Pedestrian Interaction Outcomes at Unsignalized Crossings
Chi Zhang, Amir Hossein Kalantari, Yue Yang +4
Predicting pedestrian behavior when interacting with vehicles is one of the most critical challenges in the field of automated driving. Pedestrian crossing behavior is influenced b…