Journal articles: 'Advanced Driver Assistance Systems (ADAS)'

1

Crump, Caroline, David Cades, Benjamin Lester, Scott Reed, Brandon Barakat, Laurene Milan, and Douglas Young. "Differing Perceptions of Advanced Driver Assistance Systems (ADAS)." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 861–65. http://dx.doi.org/10.1177/1541931213601197.

Full text

Abstract:

The extent to which drivers’ attitudes toward the use of autonomous vehicle systems can be influenced by various driver factors (e.g., driver age, experience with the systems, etc.) has yet to be firmly established. To investigate driver perceptions and acceptance of advanced vehicle systems, the current research examined initial and repeated exposure to systems while driving under various commonly encountered on-road situations (e.g., emergency braking). Somewhat surprisingly, driver perceptions of safety when driving vehicles with assistive technologies diminished following repeated exposure to the technologies. However, when drivers were afforded more extensive experience, they reported a heightened appreciation of the systems—especially drivers who might benefit most from this assistance (e.g., distracted or older drivers).

APA, Harvard, Vancouver, ISO, and other styles

2

Mahmudur Rahman, Md, Lesley Strawderman, and Daniel W. Carruth. "Effect of Driving Contexts on Driver Acceptance of Advanced Driver Assistance Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1944–48. http://dx.doi.org/10.1177/1541931213601965.

Full text

Abstract:

Advanced Driver Assistance Systems (ADASs) has been developed to enhance driver performance and comfort and improve transportation safety. The potential benefits of these technologies include: reduction in the number of crashes, enhanced vehicle control for drivers, reduced environmental impact, etc. However, for these technologies to achieve their potential, drivers must accept them and use them appropriately in traffic. This study investigated the effect of driving contexts on driver acceptance, more specifically, on the intention to use such technologies. Three contextual factors were considered: drivers’ fatigue level, time pressure, and time of day. Data collection was done using an online survey approach ( n = 386). Results found that fatigue and time pressure significantly affect drivers’ intention to use an ADAS. Results showed that drivers have increased intention to use an ADAS when they are fatigued or when there is no time pressure, as compared to a general driving condition.

APA, Harvard, Vancouver, ISO, and other styles

3

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 (June 19, 2021): 1480. http://dx.doi.org/10.3390/electronics10121480.

Full text

Abstract:

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 factor in understanding fatal distractions, as well as discerning when it is necessary to warn the driver about risks on the road. In this paper, a real-time gaze tracking system is proposed as part of the development of an ADAS that obtains and communicates the driver’s gaze information. The developed ADAS uses gaze information to determine if the drivers are looking to the road with their full attention. This work gives a step ahead in the ADAS based on the driver, building an ADAS that warns the driver only in case of distraction. The gaze tracking system was implemented as a model-based system using a Kinect v2.0 sensor and was adjusted on a set-up environment and tested on a suitable-features driving simulation environment. The average obtained results are promising, having hit ratios between 96.37% and 81.84%.

APA, Harvard, Vancouver, ISO, and other styles

4

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.

Full text

Abstract:

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 such cooperative ADAS grows with each vehicle involved, very large parameter spaces need to be regarded during their development, which necessitate novel development approaches. In this paper, we present an environment for rapidly prototyping cooperative ADAS based on vehicle simulation. Its underlying approach is either to bring ideas for cooperative ADAS through the prototyping stage towards plausible candidates for further development or to discard them as quickly as possible. This is enabled by an iterative process of refining and assessment. We reconcile the aspects of automation and cooperation in simulation by a tradeoff between precision and scalability. Reducing precise mapping of vehicle dynamics below the limits of driving dynamics enables simulating multiple vehicles at the same time. In order to validate this precision, we also present a method to validate the vehicle dynamics in simulation against real world vehicles.

APA, Harvard, Vancouver, ISO, and other styles

5

Abraham, Hillary, Bryan Reimer, and Bruce Mehler. "Advanced Driver Assistance Systems (ADAS): A Consideration of Driver Perceptions on Training, Usage & Implementation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1954–58. http://dx.doi.org/10.1177/1541931213601967.

Full text

Abstract:

As the first phase of a larger project, drivers were recruited to drive for a month one of two different vehicles with a range of advanced driver assistance systems (ADAS). Training methods for introducing the systems and questionnaire and structured interview methods were tested for collecting driver perceptions and understanding of the technologies. Participant perceptions and selected observations are detailed.

APA, Harvard, Vancouver, ISO, and other styles

6

Iacomussi, Paola. "Metrology Impact of Advanced Driver Assistance Systems." Electronic Imaging 2020, no. 16 (January 26, 2020): 202–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.16.avm-200.

Full text

Abstract:

Metrological applications to road environment are usually focused on the characterization of the road, considering as measurands several characteristics related to the road as a whole or the performances of single components, like the road surface, lighting systems, active and/or passive signaling and obviously vehicles equipment. In current standards approach, driving on the road means to navigate ”visually” (for a human being driver), the characterizations are mostly photometric performances oriented for given reference conditions and reference observer (photometric observer observing the road from assigned points of view, with given spectral sensitivity). But considering the present and future technological trends and knowledge on visual performances, characterizations based on only photometric quantities in reference conditions as described in the current standards would be not fully suitable, even for human driver visual needs. Nowadays research on components and systems for advanced driver assistance are evolving, following different paths toward different solutions: it is not possible, nor useful to define strict constraints as it has been done previously for road applications measurements. The paper presents the current situation of metrological characterization of road environment and components, on laboratory and on site using mobile high efficiency laboratories, and suggests to use ADAS (Advanced Driver Assistance System) for diffuse mapping of road characteristics for a better understanding of the road environment and maintenance. The suggestion has the additional advantage of minimizing measurement costs, but for its full applicability, the reliability and metrological performances of installed devices and of the measurements performed by ADAS are a priority.

APA, Harvard, Vancouver, ISO, and other styles

7

Davoli, Luca, Marco Martalò, Antonio Cilfone, Laura Belli, Gianluigi Ferrari, Roberta Presta, Roberto Montanari, et al. "On Driver Behavior Recognition for Increased Safety: A Roadmap." Safety 6, no. 4 (December 12, 2020): 55. http://dx.doi.org/10.3390/safety6040055.

Full text

Abstract:

Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.

APA, Harvard, Vancouver, ISO, and other styles

8

Ball, John E., and Bo Tang. "Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)." Electronics 8, no. 7 (July 2, 2019): 748. http://dx.doi.org/10.3390/electronics8070748.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

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 (September 2018): 1589–93. http://dx.doi.org/10.1177/1541931218621359.

Full text

Abstract:

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 may improve safe use of ADAS.

APA, Harvard, Vancouver, ISO, and other styles

10

Paiva, Sara, Xabiel García Pañeda, Victor Corcoba, Roberto García, Próspero Morán, Laura Pozueco, Marina Valdés, and Covadonga del Camino. "User Preferences in the Design of Advanced Driver Assistance Systems." Sustainability 13, no. 7 (April 2, 2021): 3932. http://dx.doi.org/10.3390/su13073932.

Full text

Abstract:

The transport network and mobility aspects are constantly changing, and major changes are expected in the coming years in terms of safety and sustainability purposes. In this paper, we present the main conclusions and analysis of data collected from a survey of drivers in Spain and Portugal regarding user preferences, highlighting the main functionalities and behavior that an advanced driver assistance system must have in order to grant it special importance on the road to prevent accidents and also to enable drivers to have a pleasant journey. Based on the results obtained from the survey, we developed and present a working prototype for an advanced driver assistance system (ADAS), its architecture and rules systems that allowed us to create and test some scenarios in a real environment.

APA, Harvard, Vancouver, ISO, and other styles

11

Елисеев, Н. "СИСТЕМЫ ADAS – УДОБСТВО И БЕЗОПАСНОСТЬ." ELECTRONICS: SCIENCE, TECHNOLOGY, BUSINESS 203, no. 2 (March 22, 2021): 102–7. http://dx.doi.org/10.22184/1992-4178.2021.203.2.102.107.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

12

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 (June 17, 2021): e0252688. http://dx.doi.org/10.1371/journal.pone.0252688.

Full text

Abstract:

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 of content and readability. To address this research gap, a content analysis was used to assess the differences in ADAS-related content and readability among the manuals of the highest selling vehicles in Australia. The qualitative findings showed that there are seven themes in the user manuals: differences between driving with and without ADAS, familiarisation requirements, operational limits of the ADAS, potential ADAS errors, behaviour adaptation warnings, confusion warnings, and malfunction warnings. The quantitative analysis found that some of the manuals require several years of education above the recommended for a universal audience (>8 years) to be understood. Additionally, there is a notable number of text diversions and infographics which could make comprehension of the user manual difficult. This investigation shows that there is a lack of standardisation of ADAS user manuals (in both content and delivery of information) which requires regulatory oversight. Driver ADAS education needs to be prioritised by policymakers and practitioners as smart technology continues to increase across the transport system. It seems that current strategies based on user manuals are insufficient to achieve successful adoption and safe use of these technologies.

APA, Harvard, Vancouver, ISO, and other styles

13

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 (May 18, 2019): 354–60. http://dx.doi.org/10.1177/0361198119847975.

Full text

Abstract:

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 technology. Two base learning methods were utilized for the study, both of which are traditional forms of learning for the average driver: reading the owner’s manual and making observations inside the vehicle. From these base learning methods, four learning protocols were developed, two of which included both methods. This paper investigates how drivers’ perceptions of usefulness, apprehension, and trust with regard to ADAS functionality were affected by initial exposure to the technology. Participants who observed ADAS during a demonstration drive had more positive perceptions relative to those who only read about them, particularly for ADAS that provide vehicle control.

APA, Harvard, Vancouver, ISO, and other styles

14

Bella, Francesco, and Manuel Silvestri. "VEHICLE–PEDESTRIAN INTERACTIONS INTO AND OUTSIDE OF CROSSWALKS: EFFECTS OF DRIVER ASSISTANCE SYSTEMS." Transport 36, no. 2 (April 30, 2021): 98–109. http://dx.doi.org/10.3846/transport.2021.14739.

Full text

Abstract:

This study aimed to analyse the driver’s behaviour during the interaction with a pedestrian crossing into and outside the zebra crossing, and evaluate the effectiveness of two kinds of Advanced Driver Assistance System (ADAS) that provided to the driver an auditory alert, and a visual alert to detect the pedestrian. 42 participants joined the experiment conducted using the fixed-base driving simulator of the Department of Engineering (Roma Tre University). They experienced different crossing conditions (legal and illegal) and ADAS conditions (no ADAS, visual warning and auditory warning) in an urban scenario. The parameters Time-To-Arrive (TTA) and Speed Reduction Time (SRT) were obtained from the drivers’ speed profiles in the last 150 m in advance of the conflict point with the pedestrian. Results clearly showed the criticality of illegal crossings. When the pedestrian crossed outside of the crosswalk, the highest number of collision occurred and the ANalysis Of VAriance (ANOVA) returned significant effects on both the dependent variables TTA and SRT, highlighting the higher criticality of the vehicle–pedestrian interaction and the more abrupt yielding manoeuvre. Positive effects (the vehicle–pedestrian interaction was less critical and the yielding manoeuvre was smoother) emerged for both the driver assistance systems, although not statistically significant. Besides, both the driver assistance systems positively affected the behaviour of the average cautious drivers. No significant effects of the warning systems were recorded on the aggressive drivers, which because of their behavioural characteristics ignored the warning alarm. In addition, no significant effects of the warning systems were recorded for the very cautious drivers, which adjusted their behaviour even before the alarm trigger. Finally, the outcomes of the questionnaire submitted to the participants highlighted the clear preference for the auditory warning, probably because of the different physical stimuli that are solicited by the warning signal. The results confirm that adequate pedestrian paths should be planned to avoid jaywalker conditions, which induce the driver to assume critical driving behaviour and provide useful findings of the effectiveness of driver assistance systems for pedestrian detection.

APA, Harvard, Vancouver, ISO, and other styles

15

Rowell, J. Martin. "Applying Map Databases to Advanced Navigation and Driver Assistance Systems." Journal of Navigation 54, no. 3 (September 2001): 355–63. http://dx.doi.org/10.1017/s0373463301001503.

Full text

Abstract:

Navigation map databases have evolved during the last 10 years in coverage, content and accuracy to such a degree that they are being used (and considered) for applications beyond vehicle navigation. For a number of advanced driver assistance systems (ADAS) in Europe and North America, the navigation maps are being enhanced to offer new functions. This will complement dynamic route guidance, with location referencing, descriptions of delays, floating car data and re-routeing, all requiring developments in traffic management, road capacity balancing and routing algorithms.

APA, Harvard, Vancouver, ISO, and other styles

16

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 (December 2020): 5–10. http://dx.doi.org/10.46864/1995-0470-2020-4-53-5-10.

Full text

Abstract:

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 developed by the State Research Center of the Russian Federation FSUE “NAMI” with the participation of manufacturers. The article also describes the key technologies of machine vision systems, test sites for highly automated vehicles.

APA, Harvard, Vancouver, ISO, and other styles

17

Rundo, Francesco. "Deep LSTM with Dynamic Time Warping Processing Framework: A Novel Advanced Algorithm with Biosensor System for an Efficient Car-Driver Recognition." Electronics 9, no. 4 (April 6, 2020): 616. http://dx.doi.org/10.3390/electronics9040616.

Full text

Abstract:

The latest generation of cars are increasingly equipped with driver assistance systems called ADAS (advanced driver assistance systems) which are able to assist the car driver in different driving scenarios, and in the most advanced automation levels, able to take over driving the car if required due to dangerous situations. Therefore, it is essential to adapt the ADAS specifically to the car-driver’s identity in order to better customize the driving assistance. To this end, algorithms that allow correct recognition of the vehicle driver are fundamental and preparatory. In this context, an algorithm for car-driver identity recognition is proposed which allows, with an accuracy close to 99%, recognition of the driver by means of a properly designed pipeline based on the analysis of the car driver PhotoPlethysmoGraphic (PPG) signal. The proposed approach makes use of deep long short-term memory (LSTM) architecture for learning such PPG signal features needed to discriminate one car driver from another. The extended validation and testing of the proposed system confirm the reliability of the proposed pipeline.

APA, Harvard, Vancouver, ISO, and other styles

18

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.

Full text

Abstract:

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 hierarchical clustering method and improved Apriori algorithm. The results showed that eye closure and yawn were high in concurrency (probability: 0.888) and interaction (average probability: 0.946); the interaction among lane departure, rapid acceleration, and rapid deceleration are frequent (average probability: 0.7224); eye closure (average probability: 0.452) and yawn (average probability: 0.444) are likely to induce abnormal vehicle states such as rapid acceleration and rapid deceleration. Some suggestions proposed based on the results are as follows. First, it is suggested that the ADAS should combine the warning modes of eye closure and yawn; second, when the driver closes eyes or yawns, the control of the ADAS over the lateral and longitudinal performance of vehicle should be enhanced; third, the extent of control by the ADAS should be determined according to the relationship probability; finally, the lateral control over the vehicle by the ADAS should be strengthened when there is a forward collision warning.

APA, Harvard, Vancouver, ISO, and other styles

19

Inagaki, Toshiyuki, and Makoto Itoh. "Human’s Overtrust in and Overreliance on Advanced Driver Assistance Systems: A Theoretical Framework." International Journal of Vehicular Technology 2013 (April 16, 2013): 1–8. http://dx.doi.org/10.1155/2013/951762.

Full text

Abstract:

This paper gives a theoretical framework to describe, analyze, and evaluate the driver’s overtrust in and overreliance on ADAS. Although “overtrust” and “overreliance” are often used as if they are synonyms, this paper differentiates the two notions rigorously. To this end, two aspects, (1) situation diagnostic aspect and (2) action selection aspect, are introduced. The first aspect is to describe overtrust, and it has three axes: (1-1) dimension of trust, (1-2) target object, and (1-3) chances of observation. The second aspect, (2), is to describe overreliance on the ADAS, and it has other three axes: (2-1) type of action selected, (2-2) benefits expected, and (2-3) time allowance for human intervention.

APA, Harvard, Vancouver, ISO, and other styles

20

Mata-Carballeira, Óscar, Jon Gutiérrez-Zaballa, Inés del Campo, and Victoria Martínez. "An FPGA-Based Neuro-Fuzzy Sensor for Personalized Driving Assistance." Sensors 19, no. 18 (September 17, 2019): 4011. http://dx.doi.org/10.3390/s19184011.

Full text

Abstract:

Advanced driving-assistance systems (ADAS) are intended to automatize driver tasks, as well as improve driving and vehicle safety. This work proposes an intelligent neuro-fuzzy sensor for driving style (DS) recognition, suitable for ADAS enhancement. The development of the driving style intelligent sensor uses naturalistic driving data from the SHRP2 study, which includes data from a CAN bus, inertial measurement unit, and front radar. The system has been successfully implemented using a field-programmable gate array (FPGA) device of the Xilinx Zynq programmable system-on-chip (PSoC). It can mimic the typical timing parameters of a group of drivers as well as tune these typical parameters to model individual DSs. The neuro-fuzzy intelligent sensor provides high-speed real-time active ADAS implementation and is able to personalize its behavior into safe margins without driver intervention. In particular, the personalization procedure of the time headway (THW) parameter for an ACC in steady car following was developed, achieving a performance of 0.53 microseconds. This performance fulfilled the requirements of cutting-edge active ADAS specifications.

APA, Harvard, Vancouver, ISO, and other styles

21

Daza, Iván, Luis Bergasa, Sebastián Bronte, J. Yebes, Javier Almazán, and Roberto Arroyo. "Fusion of Optimized Indicators from Advanced Driver Assistance Systems (ADAS) for Driver Drowsiness Detection." Sensors 14, no. 1 (January 9, 2014): 1106–31. http://dx.doi.org/10.3390/s140101106.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

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 (July 30, 2020): 105–13. http://dx.doi.org/10.1177/0361198120938778.

Full text

Abstract:

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 incorrectly it is necessary to have an insight into these mental models. One approach is to characterize users’ mental representations of systems based on the errors that they commit during system use. Such an approach necessitates a classification of potential errors that may be committed, and the underlying cognitive and behavioral reasons for such errors. To that end, a framework is proposed that can, among other goals, help predict user errors while using ADAS based on human factors and task analysis techniques. A methodology is detailed for mapping operator-system interactions using state diagrams, error identification techniques using task analysis are proposed, and a categorization scheme based on classic error taxonomies is described. This proposed framework can subsequently be expanded for error identification for a wider range and versions of ADAS, as well as for future automated driving systems (ADS). Moreover, the framework provides a systematic approach that can be used toward operationalizing mental models, forming the basis for structured user training, and for human-centered design of advanced vehicle technologies.

APA, Harvard, Vancouver, ISO, and other styles

23

Lu, Meng, Kees Wevers, and Rob Van Der Heijden. "Technical Feasibility of Advanced Driver Assistance Systems (ADAS) for Road Traffic Safety." Transportation Planning and Technology 28, no. 3 (June 2005): 167–87. http://dx.doi.org/10.1080/03081060500120282.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Ucińska, Monika. "Adaptation to driver-assistance systems depending on experience." Open Engineering 11, no. 1 (January 1, 2021): 650–61. http://dx.doi.org/10.1515/eng-2021-0064.

Full text

Abstract:

Abstract Many tasks that until recently could only be performed by humans are now entrusted to machines. Automation plays an increasingly important role in many areas of life, and its special role is observed in broadly understood transport, affecting the mobility, behaviour, and safety of drivers. Faced with the threat of a large number of accidents, deaths, and injuries, vehicles equipped with driver-assistance systems, the so-called ADAS (advanced driver-assistance system), are a significant support for the driver in reacting to the unexpected situations. The studies conducted so far indicate that the experience of using these systems may increase not only the comfort but most of all the safety of road users. In Poland, such analyses are still a challenge. The aim of the study designed by scientists from the Motor Transport Institute was to analyse the impact of the experience in using a vehicle equipped with systems on the speedy adaptation to the use of new driver-assistance systems. The adaptation process for the use of three systems was taken into account: adaptive cruise control, blind spot detection system, and lane keeping assistant. The research was carried out in real traffic. Particular attention was paid to the reactions of people who have no experience with the use of driver-assistance systems in vehicles, compared to those who have used these systems before. Proprietary questionnaires on the drivers’ feelings were used for the analyses. As expected, the analyses showed that experience with driver-assistance systems is an important factor influencing the speed of adaptation and the sense of comfort in using the systems.

APA, Harvard, Vancouver, ISO, and other styles

25

Šucha, Matúš, Ralf Risser, and Kristýna Honzíčková. "Advanced Driver Assistant Systems Focused on Pedestrians’ Safety: A User Experience Approach." Sustainability 13, no. 8 (April 12, 2021): 4264. http://dx.doi.org/10.3390/su13084264.

Full text

Abstract:

Globally, pedestrians represent 23% of all road deaths. Many solutions to protect pedestrians are proposed; in this paper, we focus on technical solutions of the ADAS–Advanced Driver Assistance Systems–type. Concerning the interaction between drivers and pedestrians, we want to have a closer look at two aspects: how to protect pedestrians with the help of vehicle technology, and how pedestrians–but also car drivers–perceive and accept such technology. The aim of the present study was to analyze and describe the experiences, needs, and preferences of pedestrians–and drivers–in connection with ADAS, or in other words, how ADAS should work in such a way that it would protect pedestrians and make walking more relaxed. Moreover, we interviewed experts in the field in order to check if, in the near future, the needs and preferences of pedestrians and drivers can be met by new generations of ADAS. A combination of different methods, specifically, an original questionnaire, on-the-spot interviewing, and expert interviews, was used to collect data. The qualitative data was analyzed using qualitative text analysis (clustering and categorization). The questionnaire for drivers was answered by a total of 70 respondents, while a total of 60 pedestrians agreed to complete questionnaires concerning pedestrian safety. Expert interviews (five interviews) were conducted by means of personal interviews, approximately one hour in duration. We conclude that systems to protect pedestrians–to avoid collisions of cars with pedestrians–are considered useful by all groups, though with somewhat different implications. With respect to the features of such systems, the considerations are very heterogeneous, and experimentation is needed in order to develop optimal systems, but a decisive argument put forward by some of the experts is that autonomous vehicles will have to be programmed extremely defensively. Given this argument, we conclude that we will need more discussion concerning typical interaction situations in order to find solutions that allow traffic to work both smoothly and safely.

APA, Harvard, Vancouver, ISO, and other styles

26

Hoyos, Christian, Benjamin D. Lester, Caroline Crump, David M. Cades, and Douglas Young. "Consumer perceptions, understanding, and expectations of Advanced Driver Assistance Systems (ADAS) and vehicle automation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 1888–92. http://dx.doi.org/10.1177/1541931218621429.

Full text

Abstract:

Consumers are faced with an increasingly complex decision process as novel safety technologies become commonplace in new vehicles. Consumers’ knowledge of these systems is potentially limited given the recent introduction and constant evolution of ADAS. We examined consumers’ understanding and perceptions of ADAS and vehicle automation in a national survey. Our analysis focused on consumers’ understanding of how certain driving tasks that can be automated (e.g., steering, braking, navigation, etc.) maps onto proposed levels of vehicle automation. Additionally, we report what sources of information and methods of education consumers prefer to utilize when learning about new safety systems. These data can inform new driver training, public policy and transportation goals of how best to educate the motoring public about new vehicle technologies and the capabilities of next-generation automated vehicles as well as facilitate public acceptance of higher levels of vehicle automation.

APA, Harvard, Vancouver, ISO, and other styles

27

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 (December 1, 2020): 555. http://dx.doi.org/10.1093/geroni/igaa057.1822.

Full text

Abstract:

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 blind-spot detection systems. We found that collision avoidance warning systems improved older adult simulator driving performance, but not lane departure warning systems. In a young to middle-aged sample the factor “concern with AV” showed age effects with older drivers less favorable. Older drivers, however, valued an active blind spot detection system more than younger drivers.

APA, Harvard, Vancouver, ISO, and other styles

28

Voinea, Gheorghe-Daniel, Cristian Cezar Postelnicu, Mihai Duguleana, Gheorghe-Leonte Mogan, and Radu Socianu. "Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System." International Journal of Environmental Research and Public Health 17, no. 19 (September 28, 2020): 7098. http://dx.doi.org/10.3390/ijerph17197098.

Full text

Abstract:

Technological advances are changing every aspect of our lives, from the way we work, to how we learn and communicate. Advanced driver assistance systems (ADAS) have seen an increased interest due to the potential of ensuring a safer environment for all road users. This study investigates the use of a smartphone-based ADAS in terms of driving performance and driver acceptance, with the aim of improving road safety. The mobile application uses both cameras of a smartphone to monitor the traffic scene and the driver’s head orientation, and offers an intuitive user interface that can display information in a standard mode or in augmented reality (AR). A real traffic experiment consisting of two driving conditions (a baseline scenario and an ADAS scenario), was conducted in Brasov, Romania. Objective and subjective data were recorded from twenty-four participants with a valid driver’s license. Results showed that the use of the ADAS influences the driving performance, as most of them adopted an increased time headway and lower mean speeds. The technology acceptance model (TAM) questionnaire was used to assess the users’ acceptance of the proposed driver assistance system. The results showed significant interrelations between acceptance factors, while the hierarchical regression analysis indicates that the variance of behavioral intention (BI) can be predicted by attitude toward behavior.

APA, Harvard, Vancouver, ISO, and other styles

29

Мякочкин, Ю., and М. Бирюков. "Миллиметровые радары АО «ПКК Миландр» для применения на автотранспорте и в системах безопасности." ELECTRONICS: SCIENCE, TECHNOLOGY, BUSINESS 189, no. 8 (October 4, 2019): 90–95. http://dx.doi.org/10.22184/1992-4178.2019.189.8.90.95.

Full text

Abstract:

Рассмотрен ряд приборов группы компаний АО «ПКК Миландр» – автомобильный радар, блок управления безопасностью автомобиля, однолучевой радар и СВЧ-приемопередатчики, – предназначенных для реализации функций интеллектуальной системы помощи водителю (Advanced Driver-Assistance Systems, ADAS) и построения систем контроля дорожного трафика, охраны периметра, определения скорости и дальности объектов.

APA, Harvard, Vancouver, ISO, and other styles

30

Sun, Chuan, Chaozhong Wu, Duanfeng Chu, Zhenji Lu, Jian Tan, and Jianyu Wang. "A Recognition Model of Driving Risk Based on Belief Rule-Base Methodology." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 11 (July 24, 2018): 1850037. http://dx.doi.org/10.1142/s0218001418500374.

Full text

Abstract:

This paper aims to recognize driving risks in individual vehicles online based on a data-driven methodology. Existing advanced driver assistance systems (ADAS) have difficulties in effectively processing multi-source heterogeneous driving data. Furthermore, parameters adopted for evaluating the driving risk are limited in these systems. The approach of data-driven modeling is investigated in this study for utilizing the accumulation of on-road driving data. A recognition model of driving risk based on belief rule-base (BRB) methodology is built, predicting driving safety as a function of driver characteristics, vehicle state and road environment conditions. The BRB model was calibrated and validated using on-road data from 30 drivers. The test results show that the recognition accuracy of our proposed model can reach about 90% in all situations with three levels (none, medium, large) of driving risks. Furthermore, the proposed simplified model, which provides real-time operation, is implemented in a vehicle driving simulator as a reference for future ADAS and belongs to research on artificial intelligence (AI) in the automotive field.

APA, Harvard, Vancouver, ISO, and other styles

31

Auricht, Maik, and Rainer Stark. "How to Consider Emotional Reactions of the Driver within the Development of Advanced Driver Assistance Systems (ADAS)?" Procedia CIRP 21 (2014): 70–74. http://dx.doi.org/10.1016/j.procir.2014.03.168.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Maag, Christian, Dominik Muhlbacher, Christian Mark, and Hans-Peter Kruger. "Studying Effects of Advanced Driver Assistance Systems (ADAS) on Individual and Group Level Using Multi-Driver Simulation." IEEE Intelligent Transportation Systems Magazine 4, no. 3 (2012): 45–54. http://dx.doi.org/10.1109/mits.2012.2203231.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Choi, Jaeheon, Kyuil Lee, Hyunmyung Kim, Sunghi An, and Daisik Nam. "Classification of Inter-Urban Highway Drivers’ Resting Behavior for Advanced Driver-Assistance System Technologies using Vehicle Trajectory Data from Car Navigation Systems." Sustainability 12, no. 15 (July 23, 2020): 5936. http://dx.doi.org/10.3390/su12155936.

Full text

Abstract:

Fatigue-related crashes, which are mainly caused by drowsy or distracted driving, account for a significant portion of fatal accidents on highways. Smart vehicle technologies can address this issue of road safety to improve the sustainability of transportation systems. Advanced driver-assistance system (ADAS) can aid drowsy drivers by recommending and guiding them to rest locations. Past research shows a significant correlation between driving distance and driver fatigue, which has been actively studied in the analysis of resting behavior. Previous research efforts have mainly relied on survey methods at specific locations, such as rest areas or toll booths. However, such traditional methods, like field surveys, are expensive and often produce biased results, based on sample location and time. This research develops methods to better estimate travel resting behavior by utilizing a large-scale dataset obtained from car navigation systems, which contain 591,103 vehicle trajectories collected over a period of four months in 2014. We propose an algorithm to statistically categorize drivers according to driving distances and their number of rests. The main algorithm combines a statistical hypothesis test and a random sampling method based on the renowned Monte-Carlo simulation technique. We were able to verify that cumulative travel distance shares a significant relationship with one’s resting decisions. Furthermore, this research identifies the resting behavior pattern of drivers based upon their travel distances. Our methodology can be used by sustainable traffic safety operators to their driver guiding strategies criterion using their own data. Not only will our methodology be able to aid sustainable traffic safety operators in constructing their driver guidance strategies criterion using their own data, but it could also be implemented in actual car navigation systems as a mid-term solution. We expect that ADAS combined with the proposed algorithm will contribute to improving traffic safety and to assisting the sustainability of road systems.

APA, Harvard, Vancouver, ISO, and other styles

34

Wang, Yugang, and Nengchao Lyu. "A Car-Following Model Based on Safety Margin considering ADAS and Driving Experience." Advances in Civil Engineering 2021 (February 19, 2021): 1–10. http://dx.doi.org/10.1155/2021/6619137.

Full text

Abstract:

Existing studies had shown that advanced driver assistance systems (ADAS) and driver individual characteristics can significantly affect driving behavior. Therefore, it is necessary to consider these factors when building the car-following model. In this study, we established a car-following model based on risk homeostasis theory, which uses safety margin (SM) as the risk level quantization parameter. Firstly, three-way Analysis of Variance (ANOVA) was used to analyze the influencing factors of car-following behavior. The results showed that ADAS and driving experience have a significant effect on the drivers’ car-following behavior. Then, according to these two significant factors, the car-following model was established. The statistical method was used to calibrate the parameter reaction response τ. Other four parameters (SMDL, SMDH, α1, and α2) were calibrated using a classical genetic algorithm, and the effects of ADAS and driving experience in these four parameters were analyzed using T-test. Finally, the proposed model was compared with the GHR model, and the result showed that the proposed model has a smaller Root Mean Square Error (RMSE) than the GHR model. The proposed model is a method of simulating different driving behaviors that are affected by ADAS and individual characteristics. Considering more driver individual characteristics, such as driving style, is the future research goal.

APA, Harvard, Vancouver, ISO, and other styles

35

Tak, Sehyun, Sunghoon Kim, Donghoun Lee, and Hwasoo Yeo. "A Comparison Analysis of Surrogate Safety Measures with Car-Following Perspectives for Advanced Driver Assistance System." Journal of Advanced Transportation 2018 (November 1, 2018): 1–14. http://dx.doi.org/10.1155/2018/8040815.

Full text

Abstract:

Surrogate Safety Measure (SSM) is one of the most widely used methods for identifying future threats, such as rear-end collision. Various SSMs have been proposed for the application of Advanced Driver Assistance Systems (ADAS), including Forward Collision Warning System (FCWS) and Emergency Braking System (EBS). The existing SSMs have been mainly used for assessing criticality of a certain traffic situation or detecting critical actions, such as severe braking maneuvers and jerking before an accident. The ADAS shows different warning signals or movements from drivers’ driving behaviours depending on the SSM employed in the system, which may lead to low reliability and low satisfaction. In order to explore the characteristics of existing SSMs in terms of human driving behaviours, this study analyzes collision risks estimated by three different SSMs, including Time-To-Collision (TTC), Stopping Headway Distance (SHD), and Deceleration-based Surrogate Safety Measure (DSSM), based on two different car-following theories, such as action point model and asymmetric driving behaviour model. The results show that the estimated collision risks of the TTC and SHD only partially match the pattern of human driving behaviour. Furthermore, the TTC and SHD overestimate the collision risk in deceleration process, particularly when the subject vehicle is faster than its preceding vehicle. On the other hand, the DSSM shows well-matched results to the pattern of the human driving behaviour. It well represents the collision risk even when the preceding vehicle moves faster than the follower one. Moreover, unlike other SSMs, the DSSM shows a balanced performance to estimate the collision risk in both deceleration and acceleration phase. These research findings suggest that the DSSM has a great potential to enhance the driver’s compliance to the ADAS, since it can reflect how the driver perceives the collision risks according to the driving behaviours in the car-following situation.

APA, Harvard, Vancouver, ISO, and other styles

36

Olaverri-Monreal, Cristina, Javier Errea-Moreno, Alberto Díaz-Álvarez, Carlos Biurrun-Quel, Luis Serrano-Arriezu, and Markus Kuba. "Connection of the SUMO Microscopic Traffic Simulator and the Unity 3D Game Engine to Evaluate V2X Communication-Based Systems." Sensors 18, no. 12 (December 12, 2018): 4399. http://dx.doi.org/10.3390/s18124399.

Full text

Abstract:

In-vehicle applications that are based on Vehicle-to-Everything (V2X) communication technologies need to be evaluated under lab-controlled conditions before performing field tests. The need for a tailored platform to perform specific research on the cooperative Advanced Driving Assistance System (ADAS) to assess the effect on driver behavior and driving performance motivated the development of a driver-centric traffic simulator that is built over a 3D graphics engine. The engine creates a driving situation as it communicates with a traffic simulator as a means to simulate real-life traffic scenarios. The TraCI as a Service (TraaS) library was implemented to perform the interaction between the driver-controlled vehicle and the Simulation of Urban MObility (SUMO). An extension of a previous version, this work improves simulation performance and realism by reducing computational demand and integrating a tailored scenario with the ADAS to be tested. The usability of the implemented simulation platform was evaluated by means of an experiment related to the efficiency of a Traffic Light Assistant (TLA), showing the analysis of the answer that 80% of the participants were satisfied with the simulator and the TLA system implemented.

APA, Harvard, Vancouver, ISO, and other styles

37

Deo, Ankur, Vasile Palade, and Md Nazmul Huda. "Centralised and Decentralised Sensor Fusion-Based Emergency Brake Assist." Sensors 21, no. 16 (August 11, 2021): 5422. http://dx.doi.org/10.3390/s21165422.

Full text

Abstract:

Many advanced driver assistance systems (ADAS) are currently trying to utilise multi-sensor architectures, where the driver assistance algorithm receives data from a multitude of sensors. As mono-sensor systems cannot provide reliable and consistent readings under all circumstances because of errors and other limitations, fusing data from multiple sensors ensures that the environmental parameters are perceived correctly and reliably for most scenarios, thereby substantially improving the reliability of the multi-sensor-based automotive systems. This paper first highlights the significance of efficiently fusing data from multiple sensors in ADAS features. An emergency brake assist (EBA) system is showcased using multiple sensors, namely, a light detection and ranging (LiDAR) sensor and camera. The architectures of the proposed ‘centralised’ and ‘decentralised’ sensor fusion approaches for EBA are discussed along with their constituents, i.e., the detection algorithms, the fusion algorithm, and the tracking algorithm. The centralised and decentralised architectures are built and analytically compared, and the performance of these two fusion architectures for EBA are evaluated in terms of speed of execution, accuracy, and computational cost. While both fusion methods are seen to drive the EBA application at an acceptable frame rate (~20 fps or higher) on an Intel i5-based Ubuntu system, it was concluded through the experiments and analytical comparisons that the decentralised fusion-driven EBA leads to higher accuracy; however, it has the downside of a higher computational cost. The centralised fusion-driven EBA yields comparatively less accurate results, but with the benefits of a higher frame rate and lesser computational cost.

APA, Harvard, Vancouver, ISO, and other styles

38

Özdemir, Özge, İslam Kılıç, Ahmet Yazıcı, and Kemal Özkan. "A V2V System Module for Inter Vehicle Communication." Applied Mechanics and Materials 850 (August 2016): 16–22. http://dx.doi.org/10.4028/www.scientific.net/amm.850.16.

Full text

Abstract:

An advanced driver assistance system (ADAS) is the premium technology for autonomous driving. It uses data from vision/camera systems, data from in vehicle sensors, and data from vehicle-to-vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communication systems. The next generation systems even autonomous vehicles are expected to use the V2V information to increase the safety for non-line of sight environments. Exchanging some data like vehicle position, speed, status etc., helps to the driver about potential problems, or to avoid collisions. In this paper, a V2V communication system module is designed and tested on the vehicles.

APA, Harvard, Vancouver, ISO, and other styles

39

Kim, Jisu, Jeonghyun Baek, Hyukdoo Choi, and Euntai Kim. "Wet area and puddle detection for Advanced Driver Assistance Systems (ADAS) using a stereo camera." International Journal of Control, Automation and Systems 14, no. 1 (February 2016): 263–71. http://dx.doi.org/10.1007/s12555-015-0024-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Hojjati-Emami, Khashayar, Balbir S. Dhillon, and Kouroush Jenab. "Reliability prediction for the vehicles equipped with advanced driver assistance systems (ADAS) and passive safety systems (PSS)." International Journal of Industrial Engineering Computations 3, no. 5 (October 1, 2012): 731–42. http://dx.doi.org/10.5267/j.ijiec.2012.08.004.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Khan, Muhammad Qasim, and Sukhan Lee. "Gaze and Eye Tracking: Techniques and Applications in ADAS." Sensors 19, no. 24 (December 14, 2019): 5540. http://dx.doi.org/10.3390/s19245540.

Full text

Abstract:

Tracking drivers’ eyes and gazes is a topic of great interest in the research of advanced driving assistance systems (ADAS). It is especially a matter of serious discussion among the road safety researchers’ community, as visual distraction is considered among the major causes of road accidents. In this paper, techniques for eye and gaze tracking are first comprehensively reviewed while discussing their major categories. The advantages and limitations of each category are explained with respect to their requirements and practical uses. In another section of the paper, the applications of eyes and gaze tracking systems in ADAS are discussed. The process of acquisition of driver’s eyes and gaze data and the algorithms used to process this data are explained. It is explained how the data related to a driver’s eyes and gaze can be used in ADAS to reduce the losses associated with road accidents occurring due to visual distraction of the driver. A discussion on the required features of current and future eye and gaze trackers is also presented.

APA, Harvard, Vancouver, ISO, and other styles

42

Souders, Dustin J., Neil Charness, Nelson A. Roque, and Hellen Pham. "Aging: Older Adults’ Driving Behavior Using Longitudinal and Lateral Warning Systems." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 2 (July 30, 2019): 229–48. http://dx.doi.org/10.1177/0018720819864510.

Full text

Abstract:

Objective This study assessed older drivers’ driving behavior when using longitudinal and lateral vehicle warning systems together. Background Advanced driver assistance systems (ADAS) can benefit drivers of all ages. Previous research with younger to middle-aged samples suggests that safety benefits are not necessarily additive with additional ADAS. Increases in following distance associated with the use of forward collision warning (FCW) decreased when drivers also used lane departure warning (LDW), likely due to attending to the LDW more than the FCW. Method The current study used a driving simulator to provide 128 older drivers experience with FCW and/or LDW system(s) during a ~25-min drive to gauge their usage’s effects on driving performance and subjective workload. Results There were no significant differences found in headway distance between older drivers who used different combinations of FCW and LDW systems, but those who used an FCW system showed significantly longer time-to-collision (TTC) when approaching the critical event than those who did not. Users of LDW systems did not show reductions in standard deviation of lane position. Analyses of subjective workload measures showed no significant differences between conditions. Conclusion Findings suggest that FCW could increase older drivers’ TTC over the course of a drive. Contrary to previous findings in younger samples, concurrent use of FCW and LDW systems did not adversely affect older drivers’ longitudinal driving performance and subjective workload. Application Potential applications of this research include the assessment of older drivers’ use of vehicle warning systems and their effects on subjective workload.

APA, Harvard, Vancouver, ISO, and other styles

43

Jezierska-Krupa, Katarzyna, and Wojciech Skarka. "Design Method of ADAS for Urban Electric Vehicle Based on Virtual Prototyping." Journal of Advanced Transportation 2018 (2018): 1–19. http://dx.doi.org/10.1155/2018/5804536.

Full text

Abstract:

Since 2012, the Smart Power Team has been actively participating in the Shell Eco-marathon, which is a worldwide competition. From the very beginning, the team has been working to increase driver’s safety on the road by developing Advanced Driver Assistance Systems. This paper presents unique method for designing ADAS systems in order to minimize the costs of the design phase and system implementation and, at the same time, to maximize the positive effect the system has on driver and vehicle safety. The described method is based on using virtual prototyping tool to simulate the system performance in real-life situations. This approach enabled an iterative design process, which resulted in reduction of errors with almost no prototyping and testing costs.

APA, Harvard, Vancouver, ISO, and other styles

44

AbdElSalam, Mohamed, Keroles Khalil, John Stickley, Ashraf Salem, and Bruno Loye. "Verification of Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles with Hardware Emulation-In-The-Loop." International Journal of Automotive Engineering 10, no. 2 (2019): 197–204. http://dx.doi.org/10.20485/jsaeijae.10.2_197.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Aung, Nyothiri, Weidong Zhang, Sahraoui Dhelim, and Yibo Ai. "Accident Prediction System Based on Hidden Markov Model for Vehicular Ad-Hoc Network in Urban Environments." Information 9, no. 12 (December 7, 2018): 311. http://dx.doi.org/10.3390/info9120311.

Full text

Abstract:

With the emergence of autonomous vehicles and internet of vehicles (IoV), future roads of smart cities will have a combination of autonomous and automated vehicles with regular vehicles that require human operators. To ensure the safety of the road commuters in such a network, it is imperative to enhance the performance of Advanced Driver Assistance Systems (ADAS). Real-time driving risk prediction is a fundamental part of an ADAS. Many driving risk prediction systems have been proposed. However, most of them are based only on vehicle’s velocity. But in most of the accident scenarios, other factors are also involved, such as weather conditions or driver fatigue. In this paper, we proposed an accident prediction system for Vehicular ad hoc networks (VANETs) in urban environments, in which we considered the crash risk as a latent variable that can be observed using multi-observation such as velocity, weather condition, risk location, nearby vehicles density and driver fatigue. A Hidden Markov Model (HMM) was used to model the correlation between these observations and the latent variable. Simulation results showed that the proposed system has a better performance in terms of sensitivity and precision compared to state of the art single factor schemes.

APA, Harvard, Vancouver, ISO, and other styles

46

De-Las-Heras, Gonzalo, Javier Sánchez-Soriano, and Enrique Puertas. "Advanced Driver Assistance Systems (ADAS) Based on Machine Learning Techniques for the Detection and Transcription of Variable Message Signs on Roads." Sensors 21, no. 17 (August 31, 2021): 5866. http://dx.doi.org/10.3390/s21175866.

Full text

Abstract:

Among the reasons for traffic accidents, distractions are the most common. Although there are many traffic signs on the road that contribute to safety, variable message signs (VMSs) require special attention, which is transformed into distraction. ADAS (advanced driver assistance system) devices are advanced systems that perceive the environment and provide assistance to the driver for his comfort or safety. This project aims to develop a prototype of a VMS (variable message sign) reading system using machine learning techniques, which are still not used, especially in this aspect. The assistant consists of two parts: a first one that recognizes the signal on the street and another one that extracts its text and transforms it into speech. For the first one, a set of images were labeled in PASCAL VOC format by manual annotations, scraping and data augmentation. With this dataset, the VMS recognition model was trained, a RetinaNet based off of ResNet50 pretrained on the dataset COCO. Firstly, in the reading process, the images were preprocessed and binarized to achieve the best possible quality. Finally, the extraction was done by the Tesseract OCR model in its 4.0 version, and the speech was done by the cloud service of IBM Watson Text to Speech.

APA, Harvard, Vancouver, ISO, and other styles

47

Noble, Alexandria M., Sheila G. Klauer, Zachary R. Doerzaph, and Michael P. Manser. "Driver Training for Automated Vehicle Technology – Knowledge, Behaviors, and Perceived Familiarity." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2110–14. http://dx.doi.org/10.1177/1071181319631249.

Full text

Abstract:

Advanced driver-assistance systems and partial driving automation are becoming increasingly common, yet despite their growing prevalence, drivers seem to know very little about them. Previous studies have found that owners of ADAS equipped vehicles have demonstrated misperceptions or lack of awareness about system limitations, which may impact driver comfort with and reliance on these systems. The purpose of this study was to determine the effectiveness of two training strategies on drivers’ knowledge and perceived familiarity of vehicle automation as well as their environment monitoring behaviors during system use. Forty volunteers participated in a multi-stage research study in which they were exposed to either a conventional training protocol, self-learning through the owner’s manual, or an experimental (multimedia) training protocol, using the in-vehicle display technologies as training tools. Results indicate training strategy elicits limited differences in knowledge and no difference in driver behaviors or attitudes. Behaviors and attitudes were heavily influenced by time and experience with the driving automation system while knowledge of the vehicle systems remained unchanged.

APA, Harvard, Vancouver, ISO, and other styles

48

Brunner, Sebastian, Manfred Stadler, Xin Wang, Frank Bauer, and Klaus Aichholzer. "ADVANCED HIGH FREQUENCY LTCC MATERIALS FOR APPLICATIONS BEYOND 60 GHZ." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2012, CICMT (September 1, 2012): 000077–81. http://dx.doi.org/10.4071/cicmt-2012-tp11.

Full text

Abstract:

In this paper we will present an application of advanced Low Temperature Cofired Ceramic (LTCC) technology beyond 60 GHz. Therefore a RF frontend for 76–81 GHz radar frequency was built. LTCC is a well established technology for applications for consumer handheld units <5 GHz but will provide solutions for applications for high frequencies in the range of 60 GHz and beyond. Radar sensors operating in the 76-81 GHz range are considered key for Advanced Driver Assistance Systems (ADAS) like Adaptive Cruise Control (ACC), Collision Mitigation and Avoidance Systems (CMS) or Lane Change Assist (LCA). These applications are the next wave in automotive safety systems and have thus generated increased interest in lower-cost solutions especially for the mm-wave frontend section.

APA, Harvard, Vancouver, ISO, and other styles

49

Wali, Safat B., Majid A. Abdullah, Mahammad A. Hannan, Aini Hussain, Salina A. Samad, Pin J. Ker, and Muhamad Bin Mansor. "Vision-Based Traffic Sign Detection and Recognition Systems: Current Trends and Challenges." Sensors 19, no. 9 (May 6, 2019): 2093. http://dx.doi.org/10.3390/s19092093.

Full text

Abstract:

The automatic traffic sign detection and recognition (TSDR) system is very important research in the development of advanced driver assistance systems (ADAS). Investigations on vision-based TSDR have received substantial interest in the research community, which is mainly motivated by three factors, which are detection, tracking and classification. During the last decade, a substantial number of techniques have been reported for TSDR. This paper provides a comprehensive survey on traffic sign detection, tracking and classification. The details of algorithms, methods and their specifications on detection, tracking and classification are investigated and summarized in the tables along with the corresponding key references. A comparative study on each section has been provided to evaluate the TSDR data, performance metrics and their availability. Current issues and challenges of the existing technologies are illustrated with brief suggestions and a discussion on the progress of driver assistance system research in the future. This review will hopefully lead to increasing efforts towards the development of future vision-based TSDR system.

APA, Harvard, Vancouver, ISO, and other styles

50

Eskandarian, Azim, and Ce Zhang. "A Brain Wave-Verified Driver Alert System for Vehicle Collision Avoidance." SAE International Journal of Transportation Safety 9, no. 1 (June 18, 2021): 105–22. http://dx.doi.org/10.4271/09-09-01-0002.

Full text

Abstract:

Collision alert and avoidance systems (CAS) could help to minimize driver errors. They are instrumental as an advanced driver-assistance system (ADAS) when the vehicle is facing potential hazards. Developing effective ADAS/CAS, which provides alerts to the driver, requires a fundamental understanding of human sensory perception and response capabilities. This research explores the premise that external stimulation can effectively improve drivers’ reaction and response capabilities. Therefore this article proposes a light-emitting diode (LED)-based driver warning system to prevent potential collisions while evaluating novel signal processing algorithms to explore the correlation between driver brain signals and external visual stimulation. When the vehicle approaches emerging obstacles or potential hazards, an LED light box flashes to warn the driver through visual stimulation to avoid the collision through braking. Thirty (30) subjects completed a driving simulator experiment under different near-collision scenarios. The Steady-State Visually Evoked Potentials (SSVEP) of the drivers’ brain signals and their collision mitigation (control performance) data were analyzed to evaluate the LED warning system’s effectiveness. The results show that (1) The proposed modified canonical correlation analysis evaluation (CCA-EVA) algorithm can detect SSVEP responses with 4.68% higher accuracy than the Adaptive Kalman filter; (2) The proposed driver monitoring and alert system produce on average a 52% improvement in time to collision (TTC), 54% improvement in reaction distance (RD), and an overall 26% reduction in collision rate as compared to similar tests without the LED warning.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Advanced Driver Assistance Systems (ADAS)'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles