Accident Simulation for Extended eCall System Without Integration in Existing Car Onboard Systems

Omieljanowicz, Miroslaw; Klimowicz, Adam; Rubin, Grzegorz; Gruszewski, Marek; Zienkiewicz, Lukasz; Lupinska-Dubicka, Anna; Tabędzki, Marek; Adamski, Marcin; Rybnik, Mariusz; Szymkowski, Maciej

doi:10.1007/978-3-319-99954-8_18

Cited by 2 publications

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“…This machine allows only simulation of impact in a non-moving car, but it was sufficient at the early stage of sensors and accident detection testing. This impact simulator was precisely described in paper [4].…”

Section: A Early Stage Accident Simulatormentioning

confidence: 99%

“…This work is based on the authors' previous publications [4] [5] [6] [7]. In this article those particular works and approaches are generalized and extended with further details, regarding among others: 1) details on experimental accident simulation and accident data gathering using mounted eCall prototype devices and two accident simulators, created by the authors, 2) extended state of the art for human presence detection (in a vehicle) and details on selected approaches as well as used hardware and excerpt of detection results obtained.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Extension for e-Safety Initiative Based on Developed Fusion of Biometric Traits

et al. 2020

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Safety is one of the central elements of society functioning. The eSafety aims at increasing road safety through the use of intelligent integrated safety systems. This article presents the concept and PCB implementation of an on-board compact eCall device that can be installed at the owners' request in a used vehicle. The prototype includes accident and rollover detection, passenger detection, and GSM communication with the eCall PSAP service center. Two accident detection algorithms are implemented: the first relates to the collision detection based on exceeding the threshold of acceleration using an accelerometer to measure the dynamic force caused by movement and the gravity force, the second-the rollover detection based on exceeding the threshold of the vehicle angle of inclination using data coming from the accelerometer and a gyroscope. The prototype was tested in eight different test scenarios using laboratory accident simulators as well as during driving. The proposed solution of passenger detection is based on images coming from a built-in 360 • view camera. In the authors' approach the obtained images were transformed into linear ones and subject to subsequent operations-initial processing, object detection and redundant detection filtering. The authors utilize biometric methods in object detection such as Viola-Jones and Single Shot MultiBox Detector for face localization, and You Look Only Once for whole body detection. An additional testing mechanism for passenger detection are seat pressure pads that are independent of camera detection. All necessary sensors and communication components verified by practical experiments have been integrated on the custom designed motherboard with the NVIDIA Jetson Nano processing module installed. The tests confirmed the performance is sufficient for rapid accident detection, real-time image analysis and all mandatory eCall communication functions. Results of experiments were promising, providing high accident and passenger detection rates.

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Section: A Early Stage Accident Simulatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%