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Safety and performance are key enablers for autonomous driving: on the one hand we want our autonomous vehicles (AVs) to be safe, while at the same time their performance (e.g., comfort or progression) is key to adoption.
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Harry Joe · 2014
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Augmented vehicle tracking under occlusions for decision-making in autonomous driving
Enric Galceran, Edwin Olson, and Ryan M Eustice · 2015
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Collision avoidance: A literature review on threat-assessment techniques
John Dahl, Gabriel Rodrigues de Campos, Claes Olsson, and Jonas Fredriksson · 2018
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Model assertions for debugging machine learning
Daniel Kang, Deepti Raghavan, Peter Bailis, and Matei Zaharia · 2018
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Map-aided dead-reckoning with lane-level maps and integrity monitoring
Franck Li, Philippe Bonnifait, and Javier Ibañez-Guzmán · 2018
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Failing to learn: Autonomously identifying perception failures for self-driving cars
Manikandasriram Srinivasan Ramanagopal, Cyrus Anderson, Ram Vasudevan, and Matthew Johnson-Roberson · 2018
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Specifying and evaluating quality metrics for vision-based perception systems
A. Balakrishnan, A. G. Puranic, X. Qin, A. Dokhanchi, J. V. Deshmukh, H. Ben Amor, and G. Fainekos · 2019
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Scaling out-of-distribution detection for real-world settings
Dan Hendrycks, Steven Basart, Mantas Mazeika, Mohammadreza Mostajabi, Jacob Steinhardt, and Dawn Song · 2019
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Pedestrian occupancy prediction for autonomous vehicles
Peter Zechel, Ralph Streiter, Klaus Bogenberger, and Ulrich Göhner · 2019
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Quantifying robot localization safety: A new integrity monitoring method for fixed-lag smoothing
O. A. Hafez, G. D. Arana, M. Joerger, and M. Spenko · 2020
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Set-based prediction of traffic participants considering occlusions and traffic rules
Markus Koschi and Matthias Althoff · 2020
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On infusing reachability-based safety assurance within planning frameworks for human–robot vehicle interactions
Karen Leung, Edward Schmerling, Mengxuan Zhang, Mo Chen, John Talbot, J Christian Gerdes, and Marco Pavone · 2020
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Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, and Marco Pavone · 2020
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Monitoring and diagnosability of perception systems
Pasquale Antonante, David I. Spivak, and Luca Carlone · 2021
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Risk perception in driving scenes
Nakul Agarwal and Yi-Ting Chen · 2022
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Limitations and improvements of the intelligent driver model (IDM)
Saleh Albeaik, Alexandre Bayen, Maria Teresa Chiri, Xiaoqian Gong, Amaury Hayat, Nicolas Kardous, Alexander Keimer, Sean T McQuade, Benedetto Piccoli, and Yiling You · 2022
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Monitoring of perception systems: Deterministic, probabilistic, and learning-based fault detection and identification
P. Antonante, H. Nilsen, and L. Carlone · 2022
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Risk-based safety envelopes for autonomous vehicles under perception uncertainty
Julian Bernhard, Patrick Hart, Amit Sahu, Christoph Schöller, and Michell Guzman Cancimance · 2022
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Anomaly detection in autonomous driving: A survey
Daniel Bogdoll, Maximilian Nitsche, and J Marius Zöllner · 2022
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Percemon: Online monitoring for perception systems
Anand Balakrishnan, Jyotirmoy Deshmukh, Bardh Hoxha, Tomoya Yamaguchi, and Georgios Fainekos · 2021
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Risk ranked recall: Collision safety metric for object detection systems in autonomous vehicles
Ayoosh Bansal, Jayati Singh, Micaela Verucchi, Marco Caccamo, and Lui Sha · 2021
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Triggering failures: Out-of-distribution detection by learning from local adversarial attacks in semantic segmentation
Victor Besnier, Andrei Bursuc, David Picard, and Alexandre Briot · 2021
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Task-driven out-of-distribution detection with statistical guarantees for robot learning
Alec Farid, Sushant Veer, and Anirudha Majumdar · 2021
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Nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
K. Tan et al. H. Caesar, J. Kabzan · 2021
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Planning paths through unknown space by imagining what lies therein
Yutao Han, Jacopo Banfi, and Mark Campbell · 2021
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Trust, but verify: Cross-modality fusion for hd map change detection
John Lambert and James Hays · 2021
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Filippos Christianos, Peter Karkus, Boris Ivanovic, Stefano V Albrecht, and Marco Pavone · 2022
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Sim-to-lab-to-real: Safe reinforcement learning with shielding and generalization guarantees
Kai-Chieh Hsu, Allen Z Ren, Duy Phuong Nguyen, Anirudha Majumdar, and Jaime F Fisac · 2022
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Sharp: Shielding-aware robust planning for safe and efficient human-robot interaction
Haimin Hu, Kensuke Nakamura, and Jaime F Fisac · 2022
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Multi-agent variational occlusion inference using people as sensors
Masha Itkina, Ye-Ji Mun, Katherine Driggs-Campbell, and Mykel J Kochenderfer · 2022
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Integrity monitoring of gnss/ins based positioning systems for autonomous vehicles: State-of-the-art and open challenges
Hao Jing, Yang Gao, Sepeedeh Shahbeigi, and Mehrdad Dianati · 2022
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Predictionnet: Real-time joint probabilistic traffic prediction for planning, control, and simulation
Alexey Kamenev, Lirui Wang, Ollin Boer Bohan, Ishwar Kulkarni, Bilal Kartal, Artem Molchanov, Stan Birchfield, David Nistér, and Nikolai Smolyanskiy · 2022
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What’s in the black box? the false negative mechanisms inside object detectors
Dimity Miller, Peyman Moghadam, Mark Cox, Matt Wildie, and Raja Jurdak · 2022
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Fsnet: A failure detection framework for semantic segmentation
Quazi Marufur Rahman, Niko Sünderhauf, Peter Corke, and Feras Dayoub · 2022
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Interaction-dynamics-aware perception zones for obstacle detection safety evaluation
Sever Topan, Karen Leung, Yuxiao Chen, Pritish Tupekar, Edward Schmerling, Jonas Nilsson, Michael Cox, and Marco Pavone · 2022
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Criticality metrics for automated driving: A review and suitability analysis of the state of the art
Lukas Westhofen, Christian Neurohr, Tjark Koopmann, Martin Butz, Barbara Schütt, Fabian Utesch, Birte Neurohr, Christian Gutenkunst, and Eckard Böde · 2023
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