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Article

Detecting Change between Urban Road Environments along a Route Based on Static Road Object Occurrences

1
Institute for Computer Science and Control (SZTAKI), Eötvös Loránd Research Network (ELKH), 13-17. Kende Utca, H-1111 Budapest, Hungary
2
Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics (BME), 2 Stoczek Utca, H-1111 Budapest, Hungary
*
Author to whom correspondence should be addressed.
Academic Editor: Luís Picado Santos
Appl. Sci. 2021, 11(8), 3666; https://doi.org/10.3390/app11083666
Received: 24 March 2021 / Revised: 10 April 2021 / Accepted: 14 April 2021 / Published: 19 April 2021
(This article belongs to the Section Robotics and Automation)
For over a decade, urban road environment detection has been a target of intensive research. The topic is relevant for the design and implementation of advanced driver assistance systems. Typically, embedded systems are deployed in these for the operation. The environments can be categorized into road environment-types. Abrupt transitions between these pose a traffic safety risk. Road environment-type transitions along a route manifest themselves also in changes in the distribution of traffic signs and other road objects. Can the placement and the detection of traffic signs be modelled jointly with an easy-to-handle stochastic point process, e.g., an inhomogeneous marked Poisson process? Does this model lend itself for real-time application, e.g., via analysis of a log generated by a traffic sign detection and recognition system? How can the chosen change detector help in mitigating the traffic safety risk? A change detection method frequently used for Poisson processes is the cumulative sum (CUSUM) method. Herein, this method is tailored to the specific stochastic model and tested on realistic logs. The use of several change detectors is also considered. Results indicate that a traffic sign-based road environment-type change detection is feasible, though it is not suitable for an immediate intervention. View Full-Text
Keywords: marked Poisson processes; change detection methods; urban road environment detection; traffic sign detection and recognition; advanced driver assistance systems marked Poisson processes; change detection methods; urban road environment detection; traffic sign detection and recognition; advanced driver assistance systems
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MDPI and ACS Style

Fazekas, Z.; Gerencsér, L.; Gáspár, P. Detecting Change between Urban Road Environments along a Route Based on Static Road Object Occurrences. Appl. Sci. 2021, 11, 3666. https://doi.org/10.3390/app11083666

AMA Style

Fazekas Z, Gerencsér L, Gáspár P. Detecting Change between Urban Road Environments along a Route Based on Static Road Object Occurrences. Applied Sciences. 2021; 11(8):3666. https://doi.org/10.3390/app11083666

Chicago/Turabian Style

Fazekas, Zoltán, László Gerencsér, and Péter Gáspár. 2021. "Detecting Change between Urban Road Environments along a Route Based on Static Road Object Occurrences" Applied Sciences 11, no. 8: 3666. https://doi.org/10.3390/app11083666

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