Predicting Road Surface Anomalies by Visual Tracking of a Preceding Vehicle

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387137" target="_blank" >RIV/68407700:21230/25:00387137 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/IV64158.2025.11097610" target="_blank" >https://doi.org/10.1109/IV64158.2025.11097610</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IV64158.2025.11097610" target="_blank" >10.1109/IV64158.2025.11097610</a>

Result language

angličtina

Original language name

Predicting Road Surface Anomalies by Visual Tracking of a Preceding Vehicle

Original language description

A novel approach to detect road surface anomalies by visual tracking of a preceding vehicle is proposed. The method is versatile, predicting any kind of road anomalies, such as potholes, bumps, debris, etc., unlike direct observation methods that rely on training visual detectors of those cases. The method operates in low visibility conditions or in dense traffic where the anomaly is occluded by a preceding vehicle. Anomalies are detected predictively, i.e., before a vehicle en-counters them, which allows to pre-configure low-level vehicle systems (such as chassis) or to plan an avoidance maneuver in case of autonomous driving. A challenge is that the signal coming from camera-based tracking of a preceding vehicle may be weak and disturbed by camera ego motion due to vibrations affecting the ego vehicle. Therefore, we propose an efficient method to compensate camera pitch rotation by an iterative robust estimator. Our experiments on both controlled setup and normal traffic conditions show that road anomalies can be detected reliably at a distance even in challenging cases where the ego vehicle traverses imperfect road surfaces. The method is effective and performs in real time on standard consumer hardware.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

IEEE IV2025 36th IEEE Intelligent Vehicles Symposium

ISBN

979-8-3315-3803-3

ISSN

1931-0587

e-ISSN

2642-7214

Number of pages

6

Pages from-to

1795-1800

Publisher name

IEEE Institute of Electrical and Electronics Engineers Inc.

Place of publication

Piscataway, New Jersey

Event location

Cluj-Napoca

Event date

Jun 22, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001556907500281