Evaluating Sequential Reasoning about Hidden Objects in Traffic

Truls Nyberg; Jose Manuel Gaspar Sanchez; Christian Pek; Jana Tumova; Martin Torngren

doi:10.1109/ICCPS54341.2022.00044

Evaluating Sequential Reasoning about Hidden Objects in Traffic

Truls Nyberg, Jose Manuel Gaspar Sanchez, Christian Pek, Jana Tumova, Martin Torngren

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

Abstract

Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving.

Original language	English
Title of host publication	Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022
Publisher	IEEE
Pages	306-307
ISBN (Electronic)	9781665409674
DOIs	https://doi.org/10.1109/ICCPS54341.2022.00044
Publication status	Published - 2022
Externally published	Yes
Event	13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022 - Virtual, Online, Italy Duration: 4 May 2022 → 6 May 2022

Conference

Conference	13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022
Country/Territory	Italy
City	Virtual, Online
Period	4/05/22 → 6/05/22

Keywords

Autonomous Vehicles
Hidden Traffic Participants
Motion Planning
Reachability Analysis
Safe Autonomy
Traffic Occlu-sions

Access to Document

10.1109/ICCPS54341.2022.00044

Cite this

@inproceedings{4039b75030ed44da842b322374517a75,

title = "Evaluating Sequential Reasoning about Hidden Objects in Traffic",

abstract = "Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving. ",

keywords = "Autonomous Vehicles, Hidden Traffic Participants, Motion Planning, Reachability Analysis, Safe Autonomy, Traffic Occlu-sions",

author = "Truls Nyberg and {Gaspar Sanchez}, {Jose Manuel} and Christian Pek and Jana Tumova and Martin Torngren",

year = "2022",

doi = "10.1109/ICCPS54341.2022.00044",

language = "English",

pages = "306--307",

booktitle = "Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022",

publisher = "IEEE",

address = "United States",

note = "13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022 ; Conference date: 04-05-2022 Through 06-05-2022",

}

Nyberg, T, Gaspar Sanchez, JM, Pek, C, Tumova, J & Torngren, M 2022, Evaluating Sequential Reasoning about Hidden Objects in Traffic. in Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022. IEEE, pp. 306-307, 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022, Virtual, Online, Italy, 4/05/22. https://doi.org/10.1109/ICCPS54341.2022.00044

Evaluating Sequential Reasoning about Hidden Objects in Traffic. / Nyberg, Truls; Gaspar Sanchez, Jose Manuel; Pek, Christian et al.
Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022. IEEE, 2022. p. 306-307.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Evaluating Sequential Reasoning about Hidden Objects in Traffic

AU - Nyberg, Truls

AU - Gaspar Sanchez, Jose Manuel

AU - Pek, Christian

AU - Tumova, Jana

AU - Torngren, Martin

PY - 2022

Y1 - 2022

N2 - Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving.

AB - Hidden traffic participants pose a great challenge for autonomous vehicles. Previous methods typically do not use previous obser-vations, leading to over-conservative behavior. In this paper, we present a continuation of our work on reasoning about objects out-side the current sensor view. We aim to demonstrate our recently proposed method on an autonomous platform and evaluate its relia-bility and real-time feasibility when using real sensor data. Showing a significant driving performance increase on a real platform, with-out compromising safety, would be a significant contribution to the field of autonomous driving.

KW - Autonomous Vehicles

KW - Hidden Traffic Participants

KW - Motion Planning

KW - Reachability Analysis

KW - Safe Autonomy

KW - Traffic Occlu-sions

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U2 - 10.1109/ICCPS54341.2022.00044

DO - 10.1109/ICCPS54341.2022.00044

M3 - Conference contribution

AN - SCOPUS:85134248642

SP - 306

EP - 307

BT - Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022

PB - IEEE

T2 - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022

Y2 - 4 May 2022 through 6 May 2022

ER -

Evaluating Sequential Reasoning about Hidden Objects in Traffic

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Keywords

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