SPADE Workshop
About the SPADE workshop
The SPADE workshop focuses on advancing intelligent and autonomous driving systems by adopting a human-centric approach that enhances user acceptance and system effectiveness. It emphasises the importance of modelling individual driving behaviours, including factors such as risk awareness, decision-making, motor control, and environmental perception, all influenced by drivers’ affective states.
Unstructured driving environments, characterised by complex and unpredictable scenarios —such as roads lacking proper markings or signals, the presence of anomalies like potholes, and diverse participants like pedestrians and non-standard vehicles— present unique challenges and opportunities for developing robust mobility solutions.
By addressing these challenges, the workshop aims to explore advancements in Intelligent Transportation Systems (ITS), Intelligent Vehicles (IV), Advanced Driver Assistance Systems (ADAS), Assistive Mobility (AM), and Driver Monitoring technologies.
A core aspect lies in harnessing multimodal naturalistic driving data to derive meaningful insights while addressing key considerations such as scalable data collection, privacy-aware frameworks, secure data management, and ethical protocols.
Highlighting collaborative efforts like the European BERTHA project, the workshop seeks to foster innovation through open-access datasets, multidisciplinary research, and practical methodologies. By convening experts from academia and industry, SPADE will promote a collaborative ecosystem to drive forward intelligent vehicle technologies and future mobility solutions.
Attend the workshop during IEEE IV 2025!
The SPADE workshop will be held on June 22 in the context of the 36th IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2025), taking place in Cluj-Napoca, Romania.
Workshop schedule
Duration: 9:00 am – 5:00 pm. Breaks: 2 (in between sessions) + the lunch break. Schedule may be subject to minor adjustments.
| Start time | Description | Speaker | Duration |
|---|---|---|---|
| 09:00 | Welcome & Introduction Chair: Antonio Manuel López Peña / Co-chair: Jason Rambach | Organisation | 10’ |
| 09:10 | Jason Rambach Modelling human driver perception, challenges and opportunities | Spatial Sensing and Machine Perception, German Research Center for Artificial Intelligence | 30+5’ |
| 09:45 | Antonio Manuel López Peña Vision-based End-to-End Driving by Imitation Learning | Computer Vision Center, Universitat Autónoma de Barcelona | 30+5’ |
| 10:20 | Javier Ibanez-Guzman | Corporate Expert: Autonomous Systems (AI), Groupe Renault, Paris | 30+5’ |
| 10:55 | Coffee Break | 20’ | |
| 11:15 | Miguel Ángel Sotelo Context-based behaviour prediction for socially-accepted automated vehicles | Computer Engineering Department, University of Alcalá, Spain | 30+5’ |
| 11:50 | Anuj Sharma (online) Towards Scalable, Non-Invasive Screening of Cognitive Impairment: Evidence from Naturalistic Driving Studies | Department of Civil, Construction and Environmental Engineering, Iowa State University Department of Neurological Sciences, University of Nebraska Medical Center | 30+5’ |
| 12:25 | Round table Moderator: Antonio Manuel López Peña | All speakers | 30’ |
| Lunch Break | |||
| 14:30 | Introduction to workshop/conference papers Chair: Jason Rambach / Co-chair: Antonio Manuel López Peña | Organisation | 10’ |
| 14:40 | Chuong Dang*, William Siegle, Ottmar Gehring, Steven Peters (Germany), Physics-Informed Loss Function for Robust Electric Truck Range Estimation | Institute of Automotive Engineering (FZD), TU Darmstadt | 15’ + 5’ |
| 15:00 | Yuzhi Chen*, Yuanchang Xie, Lei Zhao, Chen Wang (China), Trade-offs Between Safety and Volatility in Driving Interactions: Evidence from A Connected Vehicle Pilot Study | Intelligent Transportation Systems Research Center – Southeast University | 15’ + 5’ |
| 15:20 | Yun Li *, Ehsan Javanmardi, Simon Thompson, Alex Orsholits, Manabu Tsukada (Japan), PrefDrive: Enhancing Autonomous Driving through Preference-Guided Large Language Models | School of Information Science and Technology at The University of Tokyo | 15’ + 5’ |
| 15:40 | Sien Chen*, Lifei Zhao, Shihao Li, Xiao Zhang, Boyang Wang, Haiou Liu (China), A Human-Like Trajectory Learning Approach Fusing Unstructured Scene Feature Extraction with Predictive Goal Point Guidance | Beijing Institute of Technology | 15’ + 5’ |
| 16:00 | Coffee Break | 30’ | |
| 16:30 | Round table and final remarks Moderator: Jason | All invited papers | 30’ |
Workshop organisers
- Dr. José S. Solaz Sanahuja, Instituto de Biomecánica de Valencia, Valencia, Spain
- Dr. Jason Rambach, German Research Institute for AI, DFKI, Germany
- Prof. Dr. Antonio M. López, Computer Vision Center (CVC), Barcelona, Spain
- Bruna Fonseca, Manager at FI Group, Porto, Portugal
- Joana Tarana, EU Communication Consultant at FI Group, Porto, Portugal
- Sofia Oliveira, EU Communication Consultant at FI Group, Porto, Portugal
- Dr. Ayesha Choudhary, School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India
- Prof. S. Indu, Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India
- Prof. Anuj Sharma, Pitt-Des Moines Inc. Professor in Civil Engineering, Iowa State University
- Dr. Abhijit Sarkar, Senior Research Associate, Team Lead, Virginia Tech Transportation Institute
- Dr. Pujitha Gunaratne, Toyota Motor North America, USA