Relevant bibliographies by topics / Driver information support

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  1. Journal articles

Academic literature on the topic 'Driver information support'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Driver information support"

1

Chang, Cheng, Gen Ohbayashi, Toru Yamaguchi, and Eri Sato-Shimokawara. "Information Presentation Support of Car Robotics Simulator System Based on Humatronics." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 3 (2011): 389–95. http://dx.doi.org/10.20965/jaciii.2011.p0389.

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Most traffic accidents are caused by drivers’ carelessness and lack of information about the surrounding objects. In this paper, authors develop information presentation support system of a car robotics system based on humatronics. The main purpose of humatronics is to establish the symmetric interaction between human and electronics system by giving the system the capability of understanding human. Car robotics system based on humatronics is used in this research. Car robotics system is developed on human centered city. In this city, systems judge the situation and autonomously support human. A car recognizes driver’s intention by car robotics system, and acquires environmental information by connecting to the network of the human centered city’s system. The environmental information is divided into two parts: foreground information and background information. Authors develop information presentation support system which presents foreground information and gackground information. Driver is supported by the system which can be used to predict the driving reaction beforehand and send a warning signal to the driver in time.
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Cauffman, Stephen J., Yulin Deng, Yunmei Liu, Christopher Cunningham, David Kaber, and Jing Feng. "Driver Logo Sign Detection and Hazard Responses during Partially Automated Driving." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 1960–64. http://dx.doi.org/10.1177/1071181320641472.

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This study investigates the presentation of service logo information under partially automated driving. Drivers completed simulated drives with partial automation during which they had to detect target logo signs and react to hazards by taking over vehicle control when needed. Driver performance was measured in terms of sign detection rate, crash rate, and hazard response time. A number of factors, including sign information source, sign information load, and driver age group, were investigated. In general, our findings support the delivery of service logo information via in-vehicle display under partially automated driving, especially when the in-vehicle display occurred simultaneously with the on-road signage. Under this presentation condition, drivers were most accurate in detecting target logo signs, and showed little impairment from processing sign information as a secondary task when negotiating a hazard. Implications of the findings and future directions were discussed.
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Hill, Melinda J., Nancy W. Hudson, Brenda M. Lantz, and Gene C. Griffin. "Commercial Vehicle Driver Family Issues Assessment." Transportation Research Record: Journal of the Transportation Research Board 1640, no. 1 (1998): 74–83. http://dx.doi.org/10.3141/1640-10.

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The dissatisfaction of truck drivers associated with issues related to the family is examined. This dissatisfaction is seen as a major reason for high turnover rates in the trucking industry. The nature of commercial vehicle driver work and family environments is more clearly defined through mail survey questions asked of both the driver and their spouse/partner. Specific questions in the survey address work concerns, family concerns, decision making, informational needs, communication, and leisure time. Methods to apply this information to programs of intervention and support useful to commercial vehicle companies are identified. Results indicated that family-related information would help support drivers and their families. In addition, a literature review discusses job characteristics of drivers, describes stressors for the families, and identifies possible coping skills and intervention methods.
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Laberge, Jason, Nicholas Ward, Michael Rakauskas, and Janet Creaser. "A Comparison of Work Domain and Task Analysis for Identifying Information Requirements: A Case Study of Rural Intersection Decision Support Systems." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 51, no. 4 (2007): 298–302. http://dx.doi.org/10.1177/154193120705100432.

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Minnesota drivers are over-represented in accidents at rural intersections and many crashes are attributable to drivers accepting unsafe gaps. In this context, intersection decision support (IDS) systems are promising technologies for supporting driver decision-making. A significant activity during IDS development is to determine the information requirements to display to drivers. To be effective, an IDS system must present information that helps drivers successfully negotiate intersections. This paper compares two methods for identifying information requirements: work domain analysis (WDA) and hierarchical task analysis (HTA). Results showed that 58% of the requirements were identified by WDA, 7% by HTA, and 35% by both methods. An analysis of driver errors at intersections during the HTA activity identified that drivers can perceive gaps at intersections in different ways. This important nuance was not captured in the WDA. Therefore, both WDA and HTA are effective methods for identifying information requirements. Discussion focuses on the importance of both WDA and HTA in IDS system development.
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Riener, Andreas, Pierre Chalfoun, and Claude Frasson. "The Potential of Subliminal Information Displays to Change Driver Behavior." Presence: Teleoperators and Virtual Environments 23, no. 1 (2014): 51–70. http://dx.doi.org/10.1162/pres_a_00170.

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In the long history of subliminal messages and perception, many contradictory results have been presented. One group of researchers suggests that subliminal interaction techniques improve human–computer interaction by reducing sensory workload, whereas others have found that subliminal perception does not work. In this paper, we want to challenge this prejudice by first defining a terminology and introducing a theoretical taxonomy of mental processing states, then reviewing and discussing the potential of subliminal approaches for different sensory channels, and finally recapitulating the findings from our studies on subliminally triggered behavior change. Our objective is to mitigate driving problems caused by excessive information. Therefore, this work focuses on subliminal techniques applied to driver–vehicle interaction to induce a nonconscious change in driver behavior. Based on a survey of related work which identified the potential of subliminal cues in driving, we conducted two user studies assessing their applicability in real-world situations. The first study evaluated whether subtle (subliminal) vibrations could promote economical driving, and the second exposed drivers to very briefly flashed visual stimuli to assess their potential to improve steering behavior. Our results suggest that subliminal approaches are indeed feasible to provide drivers with added driving support without dissipating attention resources. Despite the lack of general evidence for uniform effectiveness of such interfaces in all driving circumstances, we firmly believe that such interfaces are valuable since they may eventually prevent accidents, save lives, and even reduce fuel costs and CO2 emissions for some drivers. For all these reasons, we are confident that subliminally driven interfaces will find their way into cars of the (near) future.
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Hashimoto, Kohjiro, Tetsuyasu Yamada, Takeshi Tsuchiya, Kae Doki, Yuki Funabora, and Shinji Doki. "Detection of contributing object to driving operations based on hidden Markov model." International Journal of Advanced Robotic Systems 16, no. 5 (2019): 172988141987679. http://dx.doi.org/10.1177/1729881419876794.

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With increase in the number of elderly people in the Japanese society, traffic accidents caused by elderly driver is considered problematic. The primary factor of the traffic accidents is a reduction in their driving cognitive performance. Therefore, a system that supports the cognitive performance of drivers can greatly contribute in preventing accidents. Recently, the development of devices for visually providing information, such as smart glasses or head up display, is in progress. These devices can provide more effective supporting information for cognitive performance. In this article, we focus on the selection problem of information to be presented for drivers to realize the cognitive support system. It has been reported that the presentation of excessive information to a driver reduces the judgment ability of the driver and makes the information less trustworthy. Thus, indiscriminate presentation of information in the vision of the driver is not an effective cognitive support. Therefore, a mechanism for determining the information to be presented to the driver based on the current driving situation is required. In this study, the object that contributes to execution of avoidance driving operation is regarded as the object that drivers must recognize and present for drivers. This object is called as contributing object. In this article, we propose a method that selects contributing objects among the appeared objects on the current driving scene. The proposed method expresses the relation between the time series change of an appeared object and avoidance operation of the driver by a mathematical model. This model can predict execution timing of avoidance driving operation and estimate contributing object based on the prediction result of driving operation. This model named as contributing model consisted of multi-hidden Markov models. Hidden Markov model is time series probabilistic model with high readability. This is because that model parameters express the probabilistic distribution and its statistics. Therefore, the characteristics of contributing model are that it enables the designer to understand the basis for the output decision. In this article, we evaluated detection accuracy of contributing object based on the proposed method, and readability of contributing model through several experiments. According to the results of these experiments, high detection accuracy of contributing object was confirmed. Moreover, it was confirmed that the basis of detected contributing object judgment can be understood from contributing model.
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7

Taramov, A. A., and N. G. Shilov. "Recommender Systems for Driver Information Support: State-of-the-Art Review." Proceedings of Tomsk State University of Control Systems and Radioelectronics 21, no. 2 (2018): 68–74. http://dx.doi.org/10.21293/1818-0442-2018-21-2-68-74.

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8

FitzGerald, Clare. "Getting Past “Purposeful”: Exploring Dimensionality in Nonprofit Executive Performance Information Use." Journal of Public and Nonprofit Affairs 6, no. 3 (2020): 281–302. http://dx.doi.org/10.20899/jpna.6.3.281-302.

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Although performance information use (PIU) among public managers is a growing and increasingly relevant research area, the existing evidence base has two significant limitations for those interested in its application to nonprofit executives. First, large survey investigations, the predominant method used to assess PIU behaviors, have rarely sampled outside of government. Second, despite theoretical arguments and empirical support for PIU being a multidimensional behavior, only ‘purposeful’ use (i.e., the deliberate and instrumental use of performance information in decision-making to improve organizational operations) has been examined with any regularity. Thus, in addition to developing theory around PIU for nonprofit executives (rather than just public managers within governments), I test established drivers of purposeful and political PIU using survey data from 260 nonprofit executives throughout the United States. Results show that nonprofit executive PIU is driven by different considerations than public manager PIU. Additionally, results show that leadership support of performance measurement is an important driver of purposeful and political PIU, with organizational goal clarity and networking behavior also, specifically, driving political PIU.
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9

KUBOTA, Shinichi, Ichiro KAGEYAMA, and Yukiyo KURIYAGAWA. "3216 Study on Indication Method of Driving Information as Driver Support System." Proceedings of the Transportation and Logistics Conference 2005.14 (2005): 259–62. http://dx.doi.org/10.1299/jsmetld.2005.14.259.

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10

Hollander, Cornelia, Nadine Rauh, Frederik Naujoks, Sebastian Hergeth, Josef F. Krems, and Andreas Keinath. "Methodological Approach towards Evaluating the Effects of Non-Driving Related Tasks during Partially Automated Driving." Information 11, no. 7 (2020): 340. http://dx.doi.org/10.3390/info11070340.

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Partially automated driving (PAD, Society of Automotive Engineers (SAE) level 2) features provide steering and brake/acceleration support, while the driver must constantly supervise the support feature and intervene if needed to maintain safety. PAD could potentially increase comfort, road safety, and traffic efficiency. As during manual driving, users might engage in non-driving related tasks (NDRTs). However, studies systematically examining NDRT execution during PAD are rare and most importantly, no established methodologies to systematically evaluate driver distraction during PAD currently exist. The current project’s goal was to take the initial steps towards developing a test protocol for systematically evaluating NDRT’s effects during PAD. The methodologies used for manual driving were extended to PAD. Two generic take-over situations addressing system limits of a given PAD regarding longitudinal and lateral control were implemented to evaluate drivers’ supervisory and take-over capabilities while engaging in different NDRTs (e.g., manual radio tuning task). The test protocol was evaluated and refined across the three studies (two simulator and one test track). The results indicate that the methodology could sensitively detect differences between the NDRTs’ influences on drivers’ take-over and especially supervisory capabilities. Recommendations were formulated regarding the test protocol’s use in future studies examining the effects of NDRTs during PAD.
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