AutoExp: A Multidisciplinary, Multi-Sensor Framework to Evaluate Human Activities in Self-Driving Cars-Reference-Cited by-同舟云学术

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AutoExp: A Multidisciplinary, Multi-Sensor Framework to Evaluate Human Activities in Self-Driving Cars

Published:2023-09-24 Issue: Volume: Page:4059-4065
ISSN:
Container-title:2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
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Author:

Crispim-Junior Carlos¹,Guesdon Romain¹,Jallais Christophe²,Laroche Florent³,Corvec Stephanie Souche-Le³,Rodet Laure Tougne¹

Affiliation:

1. Univ Lyon, Lyon 2, LIRIS UMR 5205,Lyon,France,F-69676

2. TS2-LESCOT, Univ Gustave Eiffel, IFSTTAR, Univ Lyon,Lyon,France,F-69675

3. Univ Lyon, Université Lyon 2,LAET,LYON,France,F-69007

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420842/10420843/10421877.pdf?arnumber=10421877

Reference20 articles.

1. A Gaze-Based Driver Distraction Warning System and Its Effect on Visual Behavior

2. SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark

3. A reduced feature set for driver head pose estimation

4. Longitudinal Dynamics Model Identification of an Electric Car Based on Real Response Approximation

5. DriPE: A Dataset for Human Pose Estimation in Real-World Driving Settings

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