Evaluating Advanced Driver Assistance Systems: A Reliability and Performance Analysis

The automotive industry is characterized by the implementation of sophisticated automation solutions, particularly in the domain of driver assistance systems and autonomous driving. The integration of autonomous vehicles, in conjunction with systems that merely assist the driver in the driving process, holds the potential to engender a multitude of advantages. These include the mitigation of road accidents attributable to human error, the enhancement of traffic efficiency and the reduction of emissions, the augmentation of driver comfort, and the optimization of the efficiency of certain maneuvers through the provision of assistance to the driver or the execution of these maneuvers on an automated basis. This work constitutes the implementation of systems designed to aid and assist the driver in a number of maneuvers, including parking, avoiding head-on collisions with obstacles or other vehicles, turning on or off lights, and maintaining the distance from the car in front. The vehicle on which the systems are to be installed has been designed and assembled, as well as its wireless control from a joystick via radio frequency. These systems were also subjected to reliability analysis, i.e. based on the connection of the components, the RBD diagram of the whole system was created and the reliability of the whole subassembly was calculated. The behavior of the system is also analyzed by using the Markov chain and calculating the transition matrix of the system.

Authors

Institutions

Publication Details

Published
2025-08-07
DOI
https://doi.org/10.1109/acdsa65407.2025.11166391
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating Advanced Driver Assistance Systems: A Reliability and Performance Analysis

Marius Misaroş, Dan-Ioan Gota, Honoriu Vălean, Liviu Cristian Miclea et al.
Human-Automation Interaction and Safety
article

Evaluating Advanced Driver Assistance Systems: A Reliability and Performance Analysis

Marius Misaroş, Dan-Ioan Gota, Honoriu Vălean, Liviu Cristian Miclea, Ovidiu Stan, Anca Stan
article en

Abstract

The automotive industry is characterized by the implementation of sophisticated automation solutions, particularly in the domain of driver assistance systems and autonomous driving. The integration of autonomous vehicles, in conjunction with systems that merely assist the driver in the driving process, holds the potential to engender a multitude of advantages. These include the mitigation of road accidents attributable to human error, the enhancement of traffic efficiency and the reduction of emissions, the augmentation of driver comfort, and the optimization of the efficiency of certain maneuvers through the provision of assistance to the driver or the execution of these maneuvers on an automated basis. This work constitutes the implementation of systems designed to aid and assist the driver in a number of maneuvers, including parking, avoiding head-on collisions with obstacles or other vehicles, turning on or off lights, and maintaining the distance from the car in front. The vehicle on which the systems are to be installed has been designed and assembled, as well as its wireless control from a joystick via radio frequency. These systems were also subjected to reliability analysis, i.e. based on the connection of the components, the RBD diagram of the whole system was created and the reliability of the whole subassembly was calculated. The behavior of the system is also analyzed by using the Markov chain and calculating the transition matrix of the system.

Technical University of Cluj-Napoca (RO)
Openalex Percentile: Top 70%
Human-Automation Interaction and Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.