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Journal articles on the topic 'ADAS systémy'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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1

Louis, Renee St, David Eby, Lidia Kostyniuk, et al. "PREVALENCE AND USE OF ADVANCED DRIVER ASSISTANCE SYSTEMS IN THE OLDER DRIVER POPULATION." Innovation in Aging 6, Supplement_1 (2022): 614. http://dx.doi.org/10.1093/geroni/igac059.2286.

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Abstract Research on advanced driver assistance systems (ADAS) in the older driver population has suggested the potential for ADAS to improve safety and driving comfort by helping aging drivers overcome functional declines commonly experienced in later-life. However, attaining anticipated ADAS benefits is dependent upon drivers’ awareness, understanding, and use of ADAS in their own vehicles. Questionnaire data from 2,374 older drivers enrolled in the AAA LongROAD study were analyzed to investigate changes in the prevalence and use of 15 ADAS and how participants learned to use these technolog

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Chickrin, D. "STRUCTURE AND HIERARCHIES OF INFOCOMMUNICATION SYSTEMS IN DRIVER ASSISTANCE SYSTEMS AS DESIGN TEMPLATES FOR SUBSYSTEMS OF UNMANNED VEHICLE." Izvestiya of Samara Scientific Center of the Russian Academy of Sciences 23, no. 4 (2021): 86–95. http://dx.doi.org/10.37313/1990-5378-2021-23-4-86-95.

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The article presents the structure of infocommunication systems of unmanned transport systems developed by the author, which combines the main information subsystems of the control loop in Advanced driver-assistance systems (ADAS) and shows their interaction. The analysis of the architecture of the ADAS system as a complex system from the point of view of the application of Mesarovich's theory of hierarchical multilevel systems is given (also known as stratification process) - as a result of which ADAS infocommunication systems are presented in the form of a hierarchy of the strata-layers-eche

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Hansen, Abigail, Kim Kiely, Tuki Attuquayefio, et al. "GENDER AND AGE DIFFERENCES IN ACCEPTANCE OF ADVANCED DRIVER ASSISTANCE SYSTEMS: INSIGHTS FROM OLDER AUSTRALIANS." Innovation in Aging 7, Supplement_1 (2023): 409. http://dx.doi.org/10.1093/geroni/igad104.1352.

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Abstract Advanced Driver-Assistance Systems (ADAS) are in-vehicle technologies that promise to improve driver safety and may help support older drivers to drive safer for longer, however there is little research examining acceptance and use of ADAS among older adults. This study investigated age and gender differences in attitudes to ADAS and use of ADAS. We conducted an online survey of 1330 drivers aged 65 years or older (M=72, SD=6.9, 23% women) in partnership with National Seniors Australia. ADAS use was self-reported, classifying respondents in to users (96%) and non-users (4%). ADAS acce

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Hansen, Abigail, Kim Kiely, Tuki Attuquayefio, Diane Hosking, Ranmalee Eramudugolla, and Kaarin Anstey. "PREDICTING USE OF ADVANCED DRIVER-ASSISTANCE SYSTEMS IN OLDER DRIVERS THROUGH STRUCTURAL EQUATION MODELING." Innovation in Aging 8, Supplement_1 (2024): 404. https://doi.org/10.1093/geroni/igae098.1313.

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Abstract Older drivers are an at-risk population when on-road. Normal ageing processes, such as declines in visual, sensorimotor and cognitive processes, impact driving skills and contribute to the increasing crash rate. Advanced Driver-Assistance Systems (ADAS) may provide a solution to keep older drivers safe on the road. This study investigated what technology acceptance and trust factors predict use of ADAS between older drivers who have ADAS in their car and a) use it (n=790) or b) do not use it (n=32). We conducted an online survey to 1330 Australian drivers aged 65 years or older (M=72,

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Kang, Heejin, Yoseph Lee, Harim Jeong, Giok Park, and Ilsoo Yun. "Applying the Operational Design Domain Concept to Vehicles Equipped with Advanced Driver Assistance Systems for Enhanced Safety." Journal of Advanced Transportation 2023 (December 11, 2023): 1–14. http://dx.doi.org/10.1155/2023/4640069.

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Advanced driver assistance systems (ADASs) assist drivers by alerting them of the occurrence of events based on the sensing capabilities of the vehicle, reducing the effort required by drivers. Most vehicles that are recently launched vehicles have been endowed with ADAS, thereby significantly reducing traffic accidents. However, the Insurance Institute for Highway Safety has reported that traffic accidents caused by driver negligence may increase as drivers have become accustomed to using ADAS. Therefore, drivers must be provided with sufficient information on the appropriate use of ADAS thro

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Vishal Goyal, Kamal Sharma, Amit Jain,. "A Comprehensive Analysis of AI/ML-enabled Predictive Maintenance Modelling for Advanced Driver-Assistance Systems." Journal of Electrical Systems 20, no. 4s (2024): 486–507. http://dx.doi.org/10.52783/jes.2060.

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Advanced Driver-Assistance Systems (ADAS) are changing driver-vehicle interactions to improve road safety and reduce distractions. Technological advances like ADAS and AI in cars present societal challenges and opportunities. It shows how AI aids human-machine communication by improving motor skills. The auto industry is interested in ADAS because it can increase energy efficiency, safety, and comfort. Numerous studies have shown its benefits. ADAS and vehicle networking show promise, but establishing a sound control system is challenging. Model Predictive Control (MPC) is one answer to these

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Fourie, Christiaan M., and Hermanus Carel Myburgh. "An Intra-Vehicular Wireless Multimedia Sensor Network for Smartphone-Based Low-Cost Advanced Driver-Assistance Systems." Sensors 22, no. 8 (2022): 3026. http://dx.doi.org/10.3390/s22083026.

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Advanced driver-assistance system(s) (ADAS) are more prevalent in high-end vehicles than in low-end vehicles. Wired solutions of vision sensors in ADAS already exist, but are costly and do not cater for low-end vehicles. General ADAS use wired harnessing for communication; this approach eliminates the need for cable harnessing and, therefore, the practicality of a novel wireless ADAS solution was tested. A low-cost alternative is proposed that extends a smartphone’s sensor perception, using a camera-based wireless sensor network. This paper presents the design of a low-cost ADAS alternative th

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Choy, Elaine C., Shivani J. Patel, and Alex Chaparro. "Safety first: User needs analysis of advanced driver assistance systems (ADAS) to determine learning preferences." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (2022): 1310–14. http://dx.doi.org/10.1177/1071181322661442.

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Adaptive cruise control, lane keep assist, and forward emergency braking are some examples of advanced driver assistance systems (ADAS) currently available in many automotive vehicles on the road today. As the capabilities of ADAS in vehicles continue to grow, is the driver’s understanding of these advanced features and their limitations also growing? We administered a 15-item online survey gauging familiarity, perceived importance, comfort using, and learning resource preferences of ADAS to 956 participants. These participants were drivers with experience in owning or renting ADAS-equipped ve

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González-Saavedra, Juan Felipe, Miguel Figueroa, Sandra Céspedes, and Samuel Montejo-Sánchez. "Survey of Cooperative Advanced Driver Assistance Systems: From a Holistic and Systemic Vision." Sensors 22, no. 8 (2022): 3040. http://dx.doi.org/10.3390/s22083040.

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The design of cooperative advanced driver assistance systems (C-ADAS) involves a holistic and systemic vision that considers the bidirectional interaction among three main elements: the driver, the vehicle, and the surrounding environment. The evolution of these systems reflects this need. In this work, we present a survey of C-ADAS and describe a conceptual architecture that includes the driver, vehicle, and environment and their bidirectional interactions. We address the remote operation of this C-ADAS based on the Internet of vehicles (IoV) paradigm, as well as the involved enabling technol

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Ataman, Tevfik, Mehmet Ali Biberci, and Mustafa Bahattin Celik. "Simulation of Advanced Driving Assistance Systems for a Dynamic Vehicle Model." Engineering, Technology & Applied Science Research 14, no. 5 (2024): 16553–58. http://dx.doi.org/10.48084/etasr.8294.

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Advanced Driving Assistance Systems (ADAS), such as collision avoidance systems and adaptive cruise control, are important features of autonomous driving and are gaining importance day by day in terms of increasing road safety. To increase the reliability of the system, virtual simulation environments are used during the design and development stages. This study examines the effect of ADAS features on energy parameters during the driving cycle in a virtual simulation environment. The discussion focuses on the simulation of an electric vehicle and the relationship between energy use and ADAS fu

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Mansourifar, Fariborz, Navid Nadimi, and Fahimeh Golbabaei. "Novice and Young Drivers and Advanced Driver Assistant Systems: A Review." Future Transportation 5, no. 1 (2025): 32. https://doi.org/10.3390/futuretransp5010032.

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The risk of serious crashes is notably higher among young and novice drivers. This increased risk is due to several factors, including a lack of recognition of dangerous situations, an overestimation of driving skills, and vulnerability to peer pressure. Recently, advanced driver assistance systems (ADAS) have been integrated into vehicles to help mitigate crashes linked to these factors. While numerous studies have examined ADAS broadly, few have specifically investigated its effects on young and novice drivers. This study aimed to address that gap by exploring ADAS’s impact on these drivers.

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Orlovska, J., C. Wickman, and R. Soderberg. "THE USE OF VEHICLE DATA IN ADAS DEVELOPMENT, VERIFICATION AND FOLLOW-UP ON THE SYSTEM." Proceedings of the Design Society: DESIGN Conference 1 (May 2020): 2551–60. http://dx.doi.org/10.1017/dsd.2020.322.

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AbstractAdvanced Driver Assistance Systems (ADAS) require a high level of interaction between the driver and the system, depending on driving context at a particular moment. Context-aware ADAS evaluation based on vehicle data is the most prominent way to assess the complexity of ADAS interactions. In this study, we conducted interviews with the ADAS development team at Volvo Cars to understand the role of vehicle data in the ADAS development and evaluation. The interviews’ analysis reveals strategies for improvement of current practices for vehicle data-driven ADAS evaluation.

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Massow, Kay, and Ilja Radusch. "A Rapid Prototyping Environment for Cooperative Advanced Driver Assistance Systems." Journal of Advanced Transportation 2018 (2018): 1–32. http://dx.doi.org/10.1155/2018/2586520.

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Advanced Driver Assistance Systems (ADAS) were strong innovation drivers in recent years, towards the enhancement of traffic safety and efficiency. Today’s ADAS adopt an autonomous approach with all instrumentation and intelligence on board of one vehicle. However, to further enhance their benefit, ADAS need to cooperate in the future, using communication technologies. The resulting combination of vehicle automation and cooperation, for instance, enables solving hazardous situations by a coordinated safety intervention on multiple vehicles at the same point in time. Since the complexity of suc

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Oviedo-Trespalacios, Oscar, Jennifer Tichon, and Oliver Briant. "Is a flick-through enough? A content analysis of Advanced Driver Assistance Systems (ADAS) user manuals." PLOS ONE 16, no. 6 (2021): e0252688. http://dx.doi.org/10.1371/journal.pone.0252688.

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Advanced Driver Assistance Systems (ADAS) are being developed and installed in increasing numbers. Some of the most popular ADAS include blind spot monitoring and cruise control which are fitted in the majority of new vehicles sold in high-income countries. With more drivers having access to these technologies, it is imperative to develop policy and strategies to guarantee the safe uptake of ADAS. One key issue is that ADAS education has been primarily centred on the user manual which are not widely utilised. Moreover, it is unclear if user manuals are an adequate source of education in terms

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Souders, Dustin J., Kathryn Baringer, Savana L. King, and Alan Mintz. "How Do Advanced Driver Assistance Systems Fit into Level of Automation Frameworks?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (2022): 346–50. http://dx.doi.org/10.1177/1071181322661323.

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Advanced driver assistance systems (ADAS) have been increasingly incorporated in cars for nearly four decades and have changed the relationship of the driver to the driving task substantially. Over this period, original equipment manufacturers (OEMs) have developed similar ADAS functions (e.g., adaptive cruise control, lane keeping assist, forward collision warning), but these functions lack uniformity in their implementation such that there is the possibility of negative transfer of learning across different implementations of the same ADAS function. This brief theoretical paper aims to highl

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B M,, Mohit. "ADAS USING TOUCH SENSOR." International Journal of Advanced Research in Computer Science 14, no. 03 (2023): 164–69. http://dx.doi.org/10.26483/ijarcs.v14i3.7009.

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EPS systems integrate Advanced Driver Assistance Systems (ADAS) while the driver controls the steering wheel. Touch sensors, torque, and position sensors improve driver involvement, safety, and control in EPS. ADAS features like lane-keeping assistance and adaptive cruise control are activated by the driver’s steering wheel touch. EPS with driver-enabled ADAS integration, using touch sensors, empowers drivers while leveraging enhanced automation. The vehicle model design incorporates touch sensors, Arduino, and motor drivers to enable Advanced Driver Assistance Systems (ADAS) exclusively when

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Vishal Goyal, Kamal Sharma, Amit Jain,. "Enhancing Reliability of Advanced Driver-Assistance Systems through Predictive Maintenance and Data-Driven Insights." Journal of Electrical Systems 20, no. 4s (2024): 508–23. http://dx.doi.org/10.52783/jes.2061.

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The advancement of Advanced Driver Assistance Systems (ADAS) marks a pivotal evolution in automotive technology, aiming to enhance road safety and driving efficiency through a wide array of functionalities like blind spot detection, emergency braking, and adaptive cruise control. This research paper delves into the operational integrity, performance metrics, and maintenance strategies of ADAS components, underpinned by a comprehensive methodology involving data collection, pre-processing, feature engineering, machine learning model development, and rigorous validation processes. Systematic ins

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Classen, Sherrilene, Mary Jeghers, Jane Morgan-Daniel, Sandra Winter, Luther King, and Linda Struckmeyer. "Smart In-Vehicle Technologies and Older Drivers: A Scoping Review." OTJR: Occupation, Participation and Health 39, no. 2 (2019): 97–107. http://dx.doi.org/10.1177/1539449219830376.

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In-vehicle technologies may decrease crash risk in drivers with age-related declines. Researchers determined the impact of in-vehicle information systems (IVIS) or advanced driving assistance systems (ADAS) on driving. Through a scoping review, the effect of IVIS or ADAS on older drivers’ convenience (i.e., meets one’s needs), comfort (i.e., physical or psychological ease), or safety (i.e., absence of errors or crashes) was examined. Researchers synopsized findings from 28 studies, including driving simulators and on-road environments. Findings indicated that IVIS or ADAS enhanced safety and m

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Anand A, Ajay. "Driving into the Future: The Synergy of ADAS and AI in Automobile Engineering." Journal of Applied Science, Engineering, Technology and Management 2, no. 01 (2024): 03–08. http://dx.doi.org/10.61779/jasetm.v2i1.1.

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This abstract explores the integration of Advanced Driver Assistance Systems (ADAS) and Artificial Intelligence (AI) in automobile engineering. As automotive technology advances, the synergy between ADAS and AI becomes crucial for enhancing safety, efficiency, and the overall driving experience. The paper discusses ADAS components, such as collision avoidance and adaptive cruise control, highlighting their roles in accident prevention and performance optimization. It also examines the pivotal role of AI, including machine learning and computer vision, in processing data from sensors and camera

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Sule, Samaila Yerima, Emmanuel Bitrus, and Yamta Solomon. "The Impact of Advanced Driver-Assistance Systems (ADAS) on Road Safety in Nigeria." Asian Journal of Science, Technology, Engineering, and Art 2, no. 5 (2024): 784–95. http://dx.doi.org/10.58578/ajstea.v2i5.3880.

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This study investigates the impact of Advanced Driver-Assistance Systems (ADAS) on road safety in Nigeria, focusing on their effectiveness in reducing traffic accidents, public awareness, and the challenges hindering their adoption. Utilizing a descriptive survey research design, data were collected from 310 respondents, including administrators, teachers, and students across various Government Technical Colleges in Adamawa State. The study revealed a strong positive correlation between the availability of ADAS and the reduction of road traffic accidents (r = 0.65, p = 0.002) and a significant

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Giuliano, Romeo, Franco Mazzenga, Eros Innocenti, Francesca Fallucchi, and Ibrahim Habib. "Communication Network Architectures for Driver Assistance Systems." Sensors 21, no. 20 (2021): 6867. http://dx.doi.org/10.3390/s21206867.

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Autonomous Driver Assistance Systems (ADAS) are of increasing importance to warn vehicle drivers of potential dangerous situations. In this paper, we propose one system to warn drivers of the presence of pedestrians crossing the road. The considered ADAS adopts a CNN-based pedestrian detector (PD) using the images captured from a local camera and to generate alarms. Warning messages are then forwarded to vehicle drivers approaching the crossroad by means of a communication infrastructure using public radio networks and/or local area wireless technologies. Three possible communication architect

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Ledezma, Agapito, Víctor Zamora, Óscar Sipele, M. Paz Sesmero, and Araceli Sanchis. "Implementing a Gaze Tracking Algorithm for Improving Advanced Driver Assistance Systems." Electronics 10, no. 12 (2021): 1480. http://dx.doi.org/10.3390/electronics10121480.

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Car accidents are one of the top ten causes of death and are produced mainly by driver distractions. ADAS (Advanced Driver Assistance Systems) can warn the driver of dangerous scenarios, improving road safety, and reducing the number of traffic accidents. However, having a system that is continuously sounding alarms can be overwhelming or confusing or both, and can be counterproductive. Using the driver’s attention to build an efficient ADAS is the main contribution of this work. To obtain this “attention value” the use of a Gaze tracking is proposed. Driver’s gaze direction is a crucial facto

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Abdul Razak, Siti Fatimah, Sumendra Yogarayan, Afizan Azman, Mohd Fikri Azli Abdullah, Anang Hudaya Muhamad Amin, and Mazrah Salleh. "Driver perceptions of advanced driver assistance systems: A case study." F1000Research 10 (November 8, 2021): 1122. http://dx.doi.org/10.12688/f1000research.73400.1.

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Background: Automobile manufacturers need to have an insight and understand how consumers, specifically drivers, respond to the advanced driver assistance systems (ADAS) technology in their manufactured vehicles. This study reveals drivers’ perceptions of Malaysia’s advanced driver assistance systems, which is currently lacking in the literature. So far, other studies have focused on countries that are unlike Malaysia’s multi-culture environment. Methods: A survey was designed and distributed using convenience sampling to obtain responses from licensed drivers. Questions included demographic a

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Aravind, Ravi. "Optimizing ADAS and Autonomous Driving Systems with Advanced Ethernet Protocols and Machine Learning." International Journal of Science and Research (IJSR) 12, no. 10 (2023): 2147–55. http://dx.doi.org/10.21275/es24611084428.

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Елисеев, Н. "СИСТЕМЫ ADAS – УДОБСТВО И БЕЗОПАСНОСТЬ". ELECTRONICS: SCIENCE, TECHNOLOGY, BUSINESS 203, № 2 (2021): 102–7. http://dx.doi.org/10.22184/1992-4178.2021.203.2.102.107.

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Рассмотрены усовершенствованные системы помощи водителю (Advanced driver-assistance systems, ADAS). Приведена информация о структуре и функциях систем ADAS, а также примеры решений, предлагаемых для них рядом ведущих производителей.

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NATANI, SUSHANT. "Implementing Doppler Radar with Advanced Driver Assistance Systems (ADAS)." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47516.

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Abstract - The implementation of Doppler radar in Advanced Driver Assistance Systems (ADAS) has gained extensive attention because of its capability to decorate car protection through unique object detection and movement estimation. Doppler radar affords key benefits, which includes the potential to measure item velocity at once, operate successfully in low visibility conditions such as fog and heavy rain, and paintings independently of ambient lighting situations. This paper explores the combination of Doppler radar inside ADAS, that specialize in its advantages over other sensing technologie

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Bukshetwar, Pawan. "ADAS using AI." International Journal for Research in Applied Science and Engineering Technology 12, no. 1 (2024): 112–14. http://dx.doi.org/10.22214/ijraset.2024.57919.

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Abstract: Advanced Driver Assistance Systems (ADAS) have emerged as a crucial technology in enhancing road safety and promoting autonomous driving. This thesis explores the integration of Artificial Intelligence (AI) techniques within ADAS for improved vehicle following performance. We delve into various AI approaches, including machine learning, deep learning, and computer vision, analyzing their strengths and limitations in the context of vehicle following. Additionally, the thesis highlights the challenges associated with AI-powered ADAS, such as sensor accuracy, environmental adaptability,

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Dai, Wei, Yongjun Pan, Chuan Min, Sheng-Peng Zhang, and Jian Zhao. "Real-Time Modeling of Vehicle’s Longitudinal-Vertical Dynamics in ADAS Applications." Actuators 11, no. 12 (2022): 378. http://dx.doi.org/10.3390/act11120378.

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The selection of an appropriate method for modeling vehicle dynamics heavily depends on the application. Due to the absence of human intervention, the demand for an accurate and real-time model of vehicle dynamics for intelligent control increases for autonomous vehicles. This paper develops a multibody vehicle model for longitudinal-vertical dynamics applicable to advanced driver assistance (ADAS) applications. The dynamic properties of the chassis, suspension, and tires are considered and modeled, which results in accurate vehicle dynamics and states. Unlike the vehicle dynamics models built

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Aron, Csato, and MARIASIU Florin. "Current Approaches in Traffic Lane Detection: a minireview." Archives of Automotive Engineering – Archiwum Motoryzacji 104, no. 2 (2024): 19–47. http://dx.doi.org/10.14669/am/190157.

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The continuous development and importance of the field of road transport these days make it necessary to design, develop and implement technological solutions that reduce (eliminate as much as possible) the risk of road accidents. Such a technological solution is also represented by advanced driver assistance systems (ADAS), systems that assist drivers in various ways, such as collision avoidance, automatic parking, adaptive cruise control, attention and lane departure warnings. Over the next ten years, there will likely be a rise in the need for ADAS system deployment in automobile constructi

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Abraham, Hillary, Bryan Reimer, and Bruce Mehler. "Learning to Use In-Vehicle Technologies: Consumer Preferences and Effects on Understanding." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 1589–93. http://dx.doi.org/10.1177/1541931218621359.

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Advanced Driver Assistance Systems (ADAS) have the potential to increase driver safety. However, driver misuse or failure to use ADAS could mitigate potential benefits. Appropriate training is one established method for encouraging proper use of technology. An online survey of 2364 respondents revealed significant differences between utilized and preferred methods for learning to use technologies. Drivers who learned through their preferred methods reported higher understanding and use of in-vehicle systems. Providing readily available methods of learning that align with learning preferences m

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Shahini, Farzaneh, Vanessa Nasr, David Wozniak, and Maryam Zahabi. "Law enforcement officers’ acceptance of advanced driver assistance systems: An application of technology acceptance modeling (TAM)." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (2022): 325–29. http://dx.doi.org/10.1177/1071181322661071.

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Vehicle crashes are one of the main causes of injuries and deaths for law enforcement officers (LEOs) in the line of duty. These crashes occur due to factors such as driving at high speed in emergency situations, fatigue, or use of in- vehicle technologies while driving. Advanced driver assistance systems (ADAS) have the potential to reduce crashes and improve LEO safety in police operations; however, there has been no prior research on acceptance of these technologies among LEOs. A survey study with 73 LEOs was conducted to understand factors that affect their acceptance and intention to use

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Nylen, Ashley B., Michelle L. Reyes, Cheryl A. Roe, and Daniel V. McGehee. "Impacts on Driver Perceptions in Initial Exposure to ADAS Technologies." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 10 (2019): 354–60. http://dx.doi.org/10.1177/0361198119847975.

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Advanced driver assistance systems (ADAS) offer great promise in improving the safety of our roadways. Although ADAS have rapidly entered the U.S. passenger vehicle market, little is known about driver understanding and attitudes toward ADAS, especially the impact of their initial exposure to the technologies. Whereas some ADAS may be easy to learn and use, others are more complex and have limitations that may not be obvious to the driver. The Technology Demonstration Study was conducted to evaluate how the ways in which drivers learn about ADAS affect their knowledge and perceptions of the te

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Biassoni, Federica, and Martina Gnerre. "Understanding Elderly Drivers’ Perception of Advanced Driver Assistance Systems: A Systematic Review of Perceived Risks, Trust, Ease of Use, and Usefulness." Geriatrics 9, no. 6 (2024): 144. http://dx.doi.org/10.3390/geriatrics9060144.

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Background: Elderly drivers often face safety challenges due to age-related declines in cognitive, sensory, and motor functions. Advanced Driver Assistance Systems (ADAS) offer a potential solution by enhancing safety and mobility. Objectives and method: This systematic review investigates the factors influencing the perception and usage of ADAS among elderly drivers, focusing on perceived safety, usefulness, trust, and ease of use. Results: Older adults show a preference for Level 1 ADAS, which they perceive as safer. Although they acknowledge the usefulness of ADAS in supporting their autono

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van den Beukel, Arie, Cornelie van Driel, Anika Boelhouwer, Nina Veders, and Tobias Heffelaar. "Assessment of Driving Proficiency When Drivers Utilize Assistance Systems—The Case of Adaptive Cruise Control." Safety 7, no. 2 (2021): 33. http://dx.doi.org/10.3390/safety7020033.

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Driver assistance systems (ADAS), and especially those containing driving automation, change the role of drivers to supervisors who need to safeguard the system’s operation. Despite the aim to increase safety, the new tasks (supervision and intervention) may jeopardize safety. Consequently, safety officers address the need for specific training on ADAS. However, these tasks are not assessed in driver licensing today. Therefore, we developed a framework to assess in-practice driving proficiency when drivers utilize ADAS. This study evaluated whether the proposed framework is able to identify me

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Pradhan, Anuj K., Ganesh Pai, Jaydeep Radadiya, Michael A. Knodler, Cole Fitzpatrick, and William J. Horrey. "Proposed Framework for Identifying and Predicting Operator Errors When using Advanced Vehicle Technologies." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (2020): 105–13. http://dx.doi.org/10.1177/0361198120938778.

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Advanced vehicle technologies include systems that are defined by the Society for Automotive Engineers as automated driving features or driver support features. The latter are increasingly available in late model vehicles in the form of advanced driver assistance systems (ADAS). ADAS features remove some responsibilities from drivers, but still depend on the drivers for safe operation. This can result in drivers committing errors while using ADAS, especially if their understanding of these systems, that is, their mental model, is incorrect. To understand how these systems could be used incorre

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Charness, Neil, Dustin Souders, Ryan Best, Nelson Roque, JongSung Yoon, and Cary Stothart. "Acceptance of Transportation Technologies by Aging Adults." Innovation in Aging 4, Supplement_1 (2020): 555. http://dx.doi.org/10.1093/geroni/igaa057.1822.

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Abstract Older adults are at greater risk of death and serious injury in transportation crashes which have been increasing in older adult cohorts relative to younger cohorts. Can technology provide a safer road environment? Even if technology can mitigate crash risk, is it acceptable to older road users? We outline the results from several studies that tested 1) whether advanced driver assistance systems (ADAS) can improve older adult driving performance, 2) older adults’ acceptance of ADAS and Autonomous Vehicle (AV) systems, and 3) perceptions of value for ADAS systems, particularly for blin

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Mahmoud, Ahmed, Khaled Shaaban, and Mohammed Salama. "New Algorithm for Vehicle-to-Vehicle Advanced Driver-Assistance Systems (V2V-ADAS) to Prevent Collisions." International Uni-Scientific Research Journal 3 (2022): 133–38. http://dx.doi.org/10.59271/s44915.022.1225.20.

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With the rise in traffic and stress levels among drivers, driving has become increasingly dangerous. As a result, it is essential to implement systems that can prevent collisions to ensure safer and more efficient journeys on the road. This paper proposes a novel algorithm for Vehicle-to-Vehicle Advanced Driver Assistance Systems (V2V-ADAS) that uses cooperative systems with vehicular communication technologies expected to become mandatory installations in cars. The proposed algorithm specifically focuses on detecting forward collisions and calculating current breaking distances to identify po

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Palac, Daniel, Iiona D. Scully, Rachel K. Jonas, John L. Campbell, Douglas Young, and David M. Cades. "Advanced Driver Assistance Systems (ADAS): Who’s Driving What and What’s Driving Use?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (2021): 1220–24. http://dx.doi.org/10.1177/1071181321651234.

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The emergence of vehicle technologies that promote driver safety and convenience calls for investigation of the prevalence of driver assistance systems as well as of their use rates. A consumer driven understanding as to why certain vehicle technology is used remains largely unexplored. We examined drivers’ experience using 13 different advanced driver assistance systems (ADAS) and several reasons that may explain rates of use through a nationally-distributed survey. Our analysis focused on drivers’ levels of understanding and trust with their vehicle’s ADAS as well as drivers’ perceived ease,

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Pai, Ganesh, Apoorva P. Hungund, Sarah Widrow, Jaydeep Radadiya, and Anuj K. Pradhan. "Users’ Perception Of Training Approaches For Advanced Driver Assistance Systems (Adas)." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (2021): 279–83. http://dx.doi.org/10.1177/1071181321651266.

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Advanced Driver Assistance Systems (ADAS) provide safety and comfort while driving. However, to effectively use ADAS, it is necessary for users to have proper knowledge of the systems and to trust the system to operate safely. Providing knowledge about operational capabilities and limitations of a system may help improve drivers’ mental models and calibrate their trust resulting in proper use of ADAS. Traditionally system information is provided via the owner’s manual, which is known to be tedious and time-consuming and underscores the need for alternate training approaches. This study evaluat

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Cemil, Alper, and Mehmet Ünlü. "Analysis of ADAS Radars with Electronic Warfare Perspective." Sensors 22, no. 16 (2022): 6142. http://dx.doi.org/10.3390/s22166142.

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The increasing demand in the development of autonomous driving systems makes the employment of automotive radars unavoidable. Such a motivation for the demonstration of fully-autonomous vehicles brings the challenge of secure driving under high traffic jam conditions. In this paper, we present the investigation of Advanced Driver Assistance Systems (ADAS) radars from the perspective of electronic warfare (EW). Close to real life, four ADAS jamming scenarios have been defined. Considering these scenarios, the necessary jamming power to jam ADAS radars is calculated. The required jamming Effecti

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Ulrich, Luca, Francesca Nonis, Enrico Vezzetti, et al. "Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis." Applied Sciences 11, no. 24 (2021): 11587. http://dx.doi.org/10.3390/app112411587.

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Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images

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ENDACHEV, Denis V., Sergey V. BAKHMUTOV, Vladimir V. EVGRAFOV, and Nikolay P. MEZENTCEV. "ELECTRONIC SYSTEMS OF INTELLIGENT VEHICLES." Mechanics of Machines, Mechanisms and Materials 4, no. 53 (2020): 5–10. http://dx.doi.org/10.46864/1995-0470-2020-4-53-5-10.

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Modern automotive engineering is closely related to the implementation of information systems. In automobile transport, the range of such developments is considerably wide: from driver assistance systems (ADAS — Advanced Driver Assistance System) to full autopilot systems. The article provides a brief overview of the state of the problem and presents the main directions of development of the State Research Center of the Russian Federation FSUE “NAMI” in the field of ADAS and highly automated (unmanned) vehicles. Descriptions of on-board vehicle systems of a high level of automation are given d

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Morden, Jarrad Neil, Fabio Caraffini, Ioannis Kypraios, Ali H. Al-Bayatti, and Richard Smith. "Driving in the Rain: A Survey toward Visibility Estimation through Windshields." International Journal of Intelligent Systems 2023 (August 31, 2023): 1–26. http://dx.doi.org/10.1155/2023/9939174.

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Rain can significantly impair the driver’s sight and affect his performance when driving in wet conditions. Evaluation of driver visibility in harsh weather, such as rain, has garnered considerable research since the advent of autonomous vehicles and the emergence of intelligent transportation systems. In recent years, advances in computer vision and machine learning led to a significant number of new approaches to address this challenge. However, the literature is fragmented and should be reorganised and analysed to progress in this field. There is still no comprehensive survey article that s

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Tumasov, A. V., D. Yu Tyugin, D. M. Porubov, V. I. Filatov, and A. A. Gladyshev. "Research of algorithms for road marking recognition in the lane departure warning system." Journal of Physics: Conference Series 2061, no. 1 (2021): 012130. http://dx.doi.org/10.1088/1742-6596/2061/1/012130.

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Abstract The way to improve the safety of vehicles using ADAS systems has successfully proved itself in practice. The use of ADAS systems in vehicles is mandatory in many countries of the world and is accepted at the state level. One of the most widely used ADAS systems is the Lane Departure Warning System (LDWS). The paper describes the principles of operation of existing LDWS in the segment of light commercial vehicles (LCV). The algorithm and structure of the developed LDWS for the GAZelle Next vehicle are presented. The description and analysis of algorithms for recognition of road marking

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Yang, Eunmok, and Okyeon Yi. "Enhancing Road Safety: Deep Learning-Based Intelligent Driver Drowsiness Detection for Advanced Driver-Assistance Systems." Electronics 13, no. 4 (2024): 708. http://dx.doi.org/10.3390/electronics13040708.

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Driver drowsiness detection is a significant element of Advanced Driver-Assistance Systems (ADASs), which utilize deep learning (DL) methods to improve road safety. A driver drowsiness detection system can trigger timely alerts like auditory or visual warnings, thereby stimulating drivers to take corrective measures and ultimately avoiding possible accidents caused by impaired driving. This study presents a Deep Learning-based Intelligent Driver Drowsiness Detection for Advanced Driver-Assistance Systems (DLID3-ADAS) technique. The DLID3-ADAS technique aims to enhance road safety via the detec

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Pizzicori, Matteo, Simone Piantini, Cosimo Lucci, Pierluigi Cordellieri, Marco Pierini, and Giovanni Savino. "Retrofitting ADAS for Enhanced Truck Safety: Analysis Through Systematic Review, Cost–Benefit Assessment, and Pilot Field Testing." Sustainability 17, no. 11 (2025): 4928. https://doi.org/10.3390/su17114928.

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Road transport remains a dominant mode of transportation in Europe, yet it significantly contributes to fatalities and injuries, particularly in crashes involving heavy goods vehicles and trucks. Advanced Driver Assistance Systems (ADAS) are widely recognized as a promising solution for improving truck safety. However, given that the average age of the EU truck fleet is 12 years and ADAS technologies is mandatory for new vehicles from 2024, their full impact on crash reduction may take over a decade to materialize. To address this delay, retrofitting ADAS onto existing truck fleets presents a

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Greenwood, Pamela M., John K. Lenneman, and Carryl L. Baldwin. "Advanced driver assistance systems (ADAS): Demographics, preferred sources of information, and accuracy of ADAS knowledge." Transportation Research Part F: Traffic Psychology and Behaviour 86 (April 2022): 131–50. http://dx.doi.org/10.1016/j.trf.2021.08.006.

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Wang, Tao, Yuzhi Chen, Xingchen Yan, Jun Chen, and Wenyong Li. "The Relationship between Bus Drivers’ Improper Driving Behaviors and Abnormal Vehicle States Based on Advanced Driver Assistance Systems in Naturalistic Driving." Mathematical Problems in Engineering 2020 (August 20, 2020): 1–12. http://dx.doi.org/10.1155/2020/9743504.

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In order to improve the adaptation of driver to the advanced driver assistance system (ADAS) and optimize the active safety control technology of vehicle under man-computer cooperative driving, this paper investigated the correlation between driver’s improper driving behaviors and abnormal vehicle states under the ADAS. Based on the warning data collected from the driver’s assistance warning system equipped on buses, the interaction between improper behaviors, between abnormal vehicle states, and between improper behaviors and abnormal vehicle states were quantitatively analyzed through the hi

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Karle, Ujjwala. "Driving Safety through ADAS: An Indian Perspective." ARAI Journal of Mobility Technology 1, no. 1 (2021): pp51–60. http://dx.doi.org/10.37285/ajmt.1.0.7.

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Analysis of the National Motor Vehicle Crash Causation Survey, conducted by the National Highway Traffic Safety Administration (NHTSA), shows that driver error is a factor in 94% of crashes. Although it is important to remember multiple factors contribute to all crashes, the largest portion of driver error issues involve the driver failing to recognize hazards, including distraction. Around 3,700 people die in traffic every day around the world, and 100,000 are injured. The automotive industry is striving to make driving safer. ADAS in India is comparatively in a nascent stage. However, it is

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Murtaza, Mohsin, Chi-Tsun Cheng, Mohammad Fard, and John Zeleznikow. "Assessing Training Methods for Advanced Driver Assistance Systems and Autonomous Vehicle Functions: Impact on User Mental Models and Performance." Applied Sciences 14, no. 6 (2024): 2348. http://dx.doi.org/10.3390/app14062348.

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Understanding the complexities of Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicle (AV) technologies is critical for road safety, especially concerning their adoption by drivers. Effective training is a crucial element in ensuring the safe and competent operation of these technologies. This study emphasises the critical role of training methodologies in shaping drivers’ mental models, defined as an individual’s cognitive frameworks for understanding and interacting with ADAS and AV systems. Their mental models substantially influence their interactions with those technologies.

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