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Grubb, Monty G. "Individual Differences and Driver Response to Highway Intersections." Proceedings of the Human Factors Society Annual Meeting 36, no. 13 (1992): 980–83. http://dx.doi.org/10.1177/154193129203601312.
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Along the Nation's roadways one of the most dangerous environments is the intersection. Accident investigations suggest several individual driver characteristics that may be associated with increased risk at intersections. To analyze the relationships of a number of driver characteristics to driver behavior in a controlled setting a laboratory simulation of the roadway intersection was created. Seventy-two research participants, ranging in age from 18 to 74, were measured on a battery of performance tests, administered questionnaires related to health and driving history, and exposed to a video display of approaching intersections as driver responses were measured. Each participant viewed 14 intersections containing a variety of traffic control devices. During the driving simulation portion of the research workload was assessed using six variables chosen to reflect three response modes-performance, subjective, and physiological. A MANOVA conducted to analyze the 3 (age level) by 2 (gender) factorial design indicated a main effect for both age and gender, based on three of the dependent variables-pedal response errors, speed of response, and heart rate reactivity. The responses to the intersection simulation indicated greater workloads for older drivers and female drivers. In a second phase of the data analysis stepwise multiple regressions were used to determine which independent variables, from among a set of driver characteristics, functioned as the best predictors of these performance decrements. As expected from the earlier MANOVA and univariate tests, age accounted for more variance in driver response than any single information processing variable. However, information processing variables that were most predictive of performance decrements included: field dependency, visual acuity, and depth perception.
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Radhakrishnan, Vishnu, Natasha Merat, Tyron Louw, et al. "Measuring Drivers’ Physiological Response to Different Vehicle Controllers in Highly Automated Driving (HAD): Opportunities for Establishing Real-Time Values of Driver Discomfort." Information 11, no. 8 (2020): 390. http://dx.doi.org/10.3390/info11080390.
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This study investigated how driver discomfort was influenced by different types of automated vehicle (AV) controllers, compared to manual driving, and whether this response changed in different road environments, using heart-rate variability (HRV) and electrodermal activity (EDA). A total of 24 drivers were subjected to manual driving and four AV controllers: two modelled to depict “human-like” driving behaviour, one conventional lane-keeping assist controller, and a replay of their own manual drive. Each drive lasted for ~15 min and consisted of rural and urban environments, which differed in terms of average speed, road geometry and road-based furniture. Drivers showed higher skin conductance response (SCR) and lower HRV during manual driving, compared to the automated drives. There were no significant differences in discomfort between the AV controllers. SCRs and subjective discomfort ratings showed significantly higher discomfort in the faster rural environments, when compared to the urban environments. Our results suggest that SCR values are more sensitive than HRV-based measures to continuously evolving situations that induce discomfort. Further research may be warranted in investigating the value of this metric in assessing real-time driver discomfort levels, which may help improve acceptance of AV controllers.
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Ye, Huixuan, Lili Tu, and Jie Fang. "Predicting Traffic Dynamics with Driver Response Model for Proactive Variable Speed Limit Control Algorithm." Mathematical Problems in Engineering 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/6181756.
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Variable Speed Limit (VSL) control contributes to potential crash risk reduction by suggesting a suitable dynamic speed limit to achieve more stable and uniform traffic flow. In recent studies, researchers adopted macroscopic traffic flow models and perform prediction-based optimal VSL control. The response of drivers to the advised VSL is one of the most critical parameters in VSL-controlled speed dynamics modeling, which significantly affects the accuracy of traffic state prediction as well as the control reliability and performance. Nevertheless, the variations of driver responses were not explicitly modeled. Thus, in this research, the authors proposed a dynamic driver response model to formulate how the drivers respond to the advised VSL during various traffic conditions. The model was established and calibrated using field data to quantitatively analyze the dynamics of drivers’ desired speed regarding the advised VSL and current traffic state variables. A proactive VSL control algorithm incorporating the established driver response model was designed and implemented in field-data-based simulation study. The design proactive control algorithm modifies VSL in real-time according to the traffic state prediction results, aiming to reduce potential crash risks over the experiment site. By taking into account the real-time driver response variations, the VSL-controlled traffic state dynamics was more accurately predicted. The experimental results illustrated that the proposed control algorithm effectively reduces the crash probabilities in the traffic network.
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Post, Eric S., and David W. Inouye. "Phenology: response, driver, and integrator1." Ecology 89, no. 2 (2008): 319–20. http://dx.doi.org/10.1890/07-1022.1.
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O'Leary, Patrick, Cheryl Bettinardi, Tim Daniel, Edward Nielsen, and David G. Curry. "Driver Response to Roadside Obstacles." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 50, no. 17 (2006): 2013–17. http://dx.doi.org/10.1177/154193120605001764.
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Zhang, Yiqi, and Changxu Wu. "Modeling the Effects of Warning Lead Time, Warning Reliability and Warning Style on Human Performance Under Connected Vehicle Settings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 701. http://dx.doi.org/10.1177/1541931218621158.
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Deaths and injuries resulted from traffic accidents is still a major public health problem. Recent advances in connected vehicle technology support a connected driving environment in which vehicles are enabled to communicate with each other and with roadside infrastructures via Dedicated Short Range Communication (DSRC). Connected vehicle safety applications supported by this technology allow drivers to learn about the traffic situations out of their sight and ahead of time so that drivers are warned early enough to make proper responses. As the connected vehicle systems (CVS) are designed with an aim to improving driver safety, the effectiveness of the CVS can not be achieved without drivers making proper responses in responding to the wireless warnings. Therefore, it is essential to understand and model the mechanism for human processing and responding to warnings from connected vehicle systems, and apply the driver model to optimize the design the CVS at the interface level and the communication level. Queuing Network-Model Human Processor (QN-MHP) is a computational framework that integrates three discrete serial stages of human information processing (i.e., perceptual, cognitive, and motor processing) into three continuous subnetworks. Each subnetwork is constructed of multiple servers and links among these servers. Each individual server is an abstraction of a brain area with specific functions, and links among servers represent neural pathways among functional brain areas. The neurological processing of stimuli is illustrated in the transformation of entities passing through routes in QN-MHP. Since this architecture was established, QN-MHP has been applied to quantify various aspects of aspects of driver behavior and performance, including speed control (Bi & Liu, 2009; Zhao & Wu, 2013b), lateral control (Bi et al., 2012; Bi et al., 2013), driver distraction (Bi et al., 2012; Fuller, Reed & Liu, 2012; Liu, Feyen & Tsimhoni, 2006), and driver workload (Wu & Liu, 2007; Wu et al., 2008). Most of the driver model built upon QN-MHP focused on the modeling of driver performance in normal driving situation. In a previous work of authors, a mathematical model was developed to predict the effects of warning loudness, word choice, and lead time on drivers’ warning reaction time (Zhang, Wu, & Wan, 2016). The current research focused on the development of a mathematical model based on QN-MHP to quantify and predict driver performance in responding to warnings from connected vehicle systems, including warning response time and the selection of warning response type. The model also quantified the effects of important warning characteristics in connected vehicle systems, including warning reliability, warning lead time, and speech warning style. The model was validated via an experimental study indicating its good predictability of driver behavior and performance in connected vehicle systems. In particular, the model was able to explain 68.83% of the warning response type in the initial trial of the experiment with a root mean square error (RMSE) of 0.18. By adding the warning effect on the probability of a response type through trials, the model was able to explain 65.13% of the warning response type in the initial trial of the experiment with a root mean square error (RMSE) of 0.16. In terms of warning response time, the model prediction of warning response time under different warning reliability, style and lead time were very similar to the response time results from the experiments. The model was able to explain 88.30% of the experimental response time in average with a root mean square error (RMSE) of 0.16s. The developed driver model could be applied to optimize the design of the connected vehicle systems based on driver
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Li, San Bo. "The Application and the Driver Design of Double Axis Step-Drive Electromotor in the Motorcycle Meter." Advanced Materials Research 201-203 (February 2011): 594–99. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.594.
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The traditional motorcycle meters are driven by the separate motors, these devices are simple and easy to be controlled, stable performance, but dial space has not been fully utilized. This paper introduces the double index show of motorcycle speed and speed，focus on analysis of dual-axis stepper motor driven connections, drive mode and the driver circuit design. The results of experiment and application shows that the coaxial two-pointer motorcycle display instrument has good repeatability, good linear scale, fast response, no jitter, high reliability and relatively small size and many other advantages, instrumentation stepper motor driver with dual-axis motor instrument design meet the relevant requirements of motorcycle meter, can be easily to achieve motor servo system driven synchronous control of double axis step-drive electromotor.
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Blommer, Mike, Reates Curry, Dev Kochhar, Rads Swaminathan, Walter Talamonti, and Louis Tijerina. "Off-Road Glance Behavior, Response Time to a Forward Collision Hazard, and Engagement Strategy Effects in Automated Driving." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (2017): 1909–13. http://dx.doi.org/10.1177/1541931213601958.
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Blommer et al. (2015) reported on a simulator study that investigated a driver engagement (DE) strategy designed to keep the driver-in-the-loop during automated driving in the face of two different types of secondary tasks. The method, first reported by Carsten et al. (2012), involved driving in fully automated driving mode for 6 minutes followed by 1 minute of manual driving, after which this fixed schedule was repeated several times throughout the drive. This scheduled strategy was compared to a reference condition in which different participants experienced continuous automated driving without interruptions. For each condition, some participants watched a video and others listened to the radio. All drives ended in automated driving mode with a surprise forward collision (FC) hazard to which the participant had to manually intervene. Compared to video watchers, radio listeners responded faster, looked to the road scene more, and they were more often looking forward at FC event onset. The DE strategy had no effect on radio listeners. In contrast, video watchers responded to the hazard more quickly with the scheduled strategy than without it. However, there was no reliable statistical difference between DE conditions in percent-eye-glance-time looking to the forward road scene during automated driving or in the number of drivers looking forward at FC event onset. This paper presents additional analyses of off-road eye glance behavior and finds no relationship between how long people were looking away prior to receiving a Forward Collision Warning (FCW) and driver response time (RT). About 95% of all video watching drivers glanced back to the road within 20 sec regardless of the automated driving condition. Approximately 85% of glances away from the road in the scheduled mitigation condition were 7 sec or less.
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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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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 (2021): 105–22. http://dx.doi.org/10.4271/09-09-01-0002.
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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.
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Hattori, Reiji, Satoshi Wakuda, Michihiro Asakawa, et al. "37.3: Three-Voltage-Level Driver Driven Quick-Response Liquid Powder Display." SID Symposium Digest of Technical Papers 37, no. 1 (2006): 1410. http://dx.doi.org/10.1889/1.2433249.
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Kang, Hyunmin, Kwanghee Han, and Jaesik Lee. "Differences in drivers’ pedestrian avoidance response based on Warning timing, stimulus-response compatibility and Drivers’ distraction of auditory pedestrian collision warning system." Korean Journal of Industrial and Organizational Psychology 29, no. 2 (2016): 257–77. http://dx.doi.org/10.24230/kjiop.v29i2.257-277.
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In this study, the effects of auditory pedestrian collision warning system’s stimulus-response compatibility (compatible vs. incompatible) and warning timing(TTC: 2sec. vs. 4sec.) and type of driver distraction (control condition vs. auditory distraction vs. visual distraction) on pedestrian avoidance response were examined. The dependent measures were time to initial steering wheel maneuvering, steering wheel rotation angle, clearance distance to the pedestrian, ratio of pedestrian-collision and ratio of lane departure. The experiment used driving simulator and the results was as follows. First, the effects of stimulus-response compatibility appeared to differ as warning timing and types of driver distraction were varied. To be specific, stimulus-response incompatible condition was more suitable for auditory pedestrian collision warning system than stimulus-response compatible condition. Second, compare to 4sec, 2sec TTC condition yielded larger steering wheel rotation angle and higher ratios both in pedestrian-collision and lane departure. Third, among the types of driver distraction, the visual distraction impaired drivers’ ability to avoid the pedestrian most seriously. In conclusion, stimulus-response incompatible warnings which provided 4sec TTC condition seemed to be more reliable and useful in providing pedestrian-collision warning to drivers.
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Hanowski, Richard J., Thomas A. Dingus, John P. Gallagher, Cheryl A. Kieliszewski, and Vicki L. Neale. "Driver Response to In-Vehicle Warnings." Transportation Human Factors 1, no. 1 (1999): 91–106. http://dx.doi.org/10.1207/sthf0101_10.
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Bahro, Marcel. "Response to The Driver With Dementia." American Journal of Geriatric Psychiatry 4, no. 4 (1996): 335. http://dx.doi.org/10.1097/00019442-199600440-00008.
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Mishler, Scott, and Jing Chen. "Effect of Response Method on Driver Responses to Auditory Warnings in Simulated Semi-autonomous Driving." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 1934–38. http://dx.doi.org/10.1177/1541931218621439.
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We examined how drivers’ response to automation warnings could improve driver performance by testing the traditional direct-response method against a new indirect-response method. A direct response, for which drivers manually take over control of the car after hearing the warning and seeing the scenario, was compared to an indirect response, for which drivers press a “yes” or “no” button to assist the automation in making a correct choice. Results showed no reaction time (RT) difference between the response methods, but accuracy was better for the direct response. Subtracting the action-execution time from RT showed that the indirect response took longer to mentally process, explaining why the indirect method was not faster and pointing to a potential source of increased errors. Buttons presses in the indirect method could eventually be faster, but better ways to convey the warning to the user and improve the human-machine interface are needed in future research.
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McManus, Wyatt, and Jing Chen. "The Effects of Vehicle Level Of Automation and Warning Type on Responses to Vehicle Hacking." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 1977. http://dx.doi.org/10.1177/1071181319631363.
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Modern surface transportation vehicles often include different levels of automation. Higher automation levels have the potential to impact surface transportation in unforeseen ways. For example, connected vehicles with higher levels of automation are at a higher risk for hacking attempts, because automated driving assistance systems often rely on onboard sensors and internet connectivity (Amoozadeh et al., 2015). As the automation level of vehicle control rises, it is necessary to examine the effect different levels of automation have on the driver-vehicle interactions. While research into the effect of automation level on driver-vehicle interactions is growing, research into how automation level affects driver’s responses to vehicle hacking attempts is very limited. In addition, auditory warnings have been shown to effectively attract a driver’s attention while performing a driving task, which is often visually demanding (Baldwin, 2011; Petermeijer, Doubek, & de Winter, 2017). An auditory warning can be either speech-based containing sematic information (e.g., “car in blind spot”) or non-sematic (e.g., a tone, or an earcon), which can influence driver behaviors differently (Sabic, Mishler, Chen, & Hu, 2017). The purpose of the current study was to examine the effect of level of automation and warning type on driver responses to novel critical events, using vehicle hacking attempts as a concrete example, in a driving simulator. The current study compared how level of automation (manual vs. automated) and warning type (non-semantic vs. semantic) affected drivers’ responses to a vehicle hacking attempt using time to collision (TTC) values, maximum steering wheel angle, number of successful responses, and other measures of response. A full factorial between-subjects design with the two factors made four conditions (Manual Semantic, Manual Non-Semantic, Automated Semantic, and Automated Non-Semantic). Seventy-two participants recruited using SONA ( odupsychology.sona-systems.com ) completed two simulated drives to school in a driving simulator. The first drive ended with the participant safely arriving at school. A two-second warning was presented to the participants three quarters of the way through the second drive and was immediately followed by a simulated vehicle hacking attempt. The warning either stated “Danger, hacking attempt incoming” in the semantic conditions or was a 500 Hz sine tone in the non-semantic conditions. The hacking attempt lasted five seconds before simulating a crash into a vehicle and ending the simulation if no intervention by the driver occurred. Our results revealed no significant effect of level of automation or warning type on TTC or successful response rate. However, there was a significant effect of level of automation on maximum steering wheel angle. This is a measure of response quality (Shen & Neyens, 2017), such that manual drivers had safer responses to the hacking attempt with smaller maximum steering wheel angles. In addition, an effect of warning type that approached significance was also found for maximum steering wheel angle such that participants who received a semantic warning had more severe and dangerous responses to the hacking attempt. The TTC and successful response results from the current experiment do not match those in the previous literature. The null results were potentially due to the warning implementation time and the complexity of the vehicle hacking attempt. In contrast, the maximum steering wheel angle results indicated that level of automation and warning type affected the safety and severity of the participants’ responses to the vehicle hacking attempt. This suggests that both factors may influence responses to hacking attempts in some capacity. Further research will be required to determine if level of automation and warning type affect participants ability to safely respond to vehicle hacking attempts. Acknowledgments. We are grateful to Scott Mishler for his assistance with STISIM programming and Faye Wakefield, Hannah Smith, and Pettie Perkins for their assistance in data collection.
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Borovsky, Joseph E., and Adnane Osmane. "Compacting the description of a time-dependent multivariable system and its multivariable driver by reducing the state vectors to aggregate scalars: the Earth's solar-wind-driven magnetosphere." Nonlinear Processes in Geophysics 26, no. 4 (2019): 429–43. http://dx.doi.org/10.5194/npg-26-429-2019.
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Abstract. Using the solar-wind-driven magnetosphere–ionosphere–thermosphere system, a methodology is developed to reduce a state-vector description of a time-dependent driven system to a composite scalar picture of the activity in the system. The technique uses canonical correlation analysis to reduce the time-dependent system and driver state vectors to time-dependent system and driver scalars, with the scalars describing the response in the system that is most-closely related to the driver. This reduced description has advantages: low noise, high prediction efficiency, linearity in the described system response to the driver, and compactness. The methodology identifies independent modes of reaction of a system to its driver. The analysis of the magnetospheric system is demonstrated. Using autocorrelation analysis, Jensen–Shannon complexity analysis, and permutation-entropy analysis the properties of the derived aggregate scalars are assessed and a new mode of reaction of the magnetosphere to the solar wind is found. This state-vector-reduction technique may be useful for other multivariable systems driven by multiple inputs.
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Kersavage, Kristin, Nicholas P. Skinner, John D. Bullough, Philip M. Garvey, Eric T. Donnell, and Mark S. Rea. "Driver Behavior in Response to Flashing Lights." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (2019): 703–8. http://dx.doi.org/10.1177/0361198119840616.
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Flashing yellow warning lights notify drivers about the presence of work along the road. Current standards for these lights address performance of the individual light but not how lights should function when multiple lights are used. In the present study, warning lights were used to delineate a lane change taper in a simulated work zone. Lights flashed with varying intensities and either randomly or in sequence, with lights flashing in turn along the length of the lane change taper, either to the right or to the left. In half of the trials, a flashing police light bar was used on a vehicle located within the simulated work zone. Participants were asked to drive a vehicle approaching the work zone and to identify, as quickly as possible, in which direction the taper’s lane change was (either to the right or left). Drivers were able to correctly identify the taper from farther away when the lights flashed in a sequential pattern than when the flash pattern was random; and the presence of a police light bar resulted in shorter identification distances. The results, along with previous research, can inform standards for the use of flashing lights and police lights in work zones for the safety of drivers and workers.
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Rakotonirainy, Andry, Frank Feller, and Narelle Haworth. "In-Vehicle Avatars to Elicit Social Response and Change Driving Behaviour." International Journal of Technology and Human Interaction 5, no. 4 (2009): 80–104. http://dx.doi.org/10.4018/jthi.2009062505.
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Social and psychological theories have provided a plethora of evidence showing that the physical difficulty to express appropriate social interactions between drivers expresses itself in aggression, selfish driving and anti-social behaviour. Therefore there is a need to improve interactions between drivers and allow clearer collective decision making between them. Personal characteristics and the driving situations play strong roles in driver’s aggression. Our approach is centered around the driving situation as opposed to focusing on personality characteristics. It examines aggression and manipulates contextual variables such as driver’s eye contact exchanges. This paper presents a new unobtrusive in-vehicle system that aims at communicating drivers’ intentions, elicit social responses and increasing mutual awareness. It uses eye gaze as a social cue to affect collective decision making with the view to contribute to safe driving. The authors used a driving simulator to design a case control experiment in which eye gaze movements are conveyed with an avatar. Participants were asked to drive through different types of intersections. An avatar representing the head of the other driver was displayed and driver behaviour was analysed. Significant eye gaze pattern difference where observed when an avatar was displayed. Drivers cautiously refer to the avatar when information is required on the intention of others (e.g. when they do not have the right of way). The majority of participants reported the perception of “being looked at”. The number of glances and time spent gazing at the avatar did not indicate an unsafe distraction by standards of in-vehicle device ergonomic design. Avatars were visually consulted primarily in less demanding driving situations, which underlines their non-distractive nature.
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Manser, Michael P., Nicholas J. Ward, Nobuyuki Kuge, and Erwin Boer. "Driver Behavioral Adaptation in Response to a Novel Haptic Driver Support System." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 49, no. 22 (2005): 1950–54. http://dx.doi.org/10.1177/154193120504902214.
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Shen, Jinyan, Li Li, Niall G. Howlett, Paul S. Cohen, and Gongqin Sun. "Application of a Biphasic Mathematical Model of Cancer Cell Drug Response for Formulating Potent and Synergistic Targeted Drug Combinations to Triple Negative Breast Cancer Cells." Cancers 12, no. 5 (2020): 1087. http://dx.doi.org/10.3390/cancers12051087.
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Triple negative breast cancer is a collection of heterogeneous breast cancers that are immunohistochemically negative for estrogen receptor, progesterone receptor, and ErbB2 (due to deletion or lack of amplification). No dominant proliferative driver has been identified for this type of cancer, and effective targeted therapy is lacking. In this study, we hypothesized that triple negative breast cancer cells are multi-driver cancer cells, and evaluated a biphasic mathematical model for identifying potent and synergistic drug combinations for multi-driver cancer cells. The responses of two triple negative breast cancer cell lines, MDA-MB-231 and MDA-MB-468, to a panel of targeted therapy drugs were determined over a broad range of concentrations. The analyses of the drug responses by the biphasic mathematical model revealed that both cell lines were indeed dependent on multiple drivers, and inhibitors of individual drivers caused a biphasic response: a target-specific partial inhibition at low nM concentrations, and an off-target toxicity at μM concentrations. We further demonstrated that combinations of drugs, targeting each driver, cause potent, synergistic, and cell-specific cell killing. Immunoblotting analysis of the effects of the individual drugs and drug combinations on the signaling pathways supports the above conclusion. These results support a multi-driver proliferation hypothesis for these triple negative breast cancer cells, and demonstrate the applicability of the biphasic mathematical model for identifying effective and synergistic targeted drug combinations for triple negative breast cancer cells.
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Fambro, Daniel B., Rodger J. Koppa, Dale L. Picha, and Kay Fitzpatrick. "Driver Perception–Brake Response in Stopping Sight Distance Situations." Transportation Research Record: Journal of the Transportation Research Board 1628, no. 1 (1998): 1–7. http://dx.doi.org/10.3141/1628-01.
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One of the most important requirements in highway design is the provision of adequate stopping sight distance at every point along the roadway. At a minimum, this sight distance should be long enough to enable a vehicle traveling at or near the design speed to stop before reaching a stationary object in its path. Stopping sight distance is the sum of two components–brake reaction distance and braking distance. Brake reaction distance is based on the vehicle’s speed and the driver’s perception–brake reaction time (PBRT). Four separate, but coordinated, driver braking performance studies measured driver perception–brake response to several different stopping sight distance situations. The results from the driver braking performance studies suggest that the mean perception–brake response time to an unexpected object scenario under controlled and open road conditions is about 1.1 s. The 95th percentile perception–brake response times for these same conditions was 2.0 s. The findings from these studies are consistent with those in the literature: that is, most drivers are capable of responding to an unexpected hazard in the roadway in 2.0 s or less. Thus, the American Association of State Highway and Transportation Officials’ perception–brake response time of 2.5 s encompasses most of the driving population and is an appropriate value for highway design.
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Peeta, Srinivas, Jorge L. Ramos, and Raghubhushan Pasupathy. "Content of Variable Message Signs and On-Line Driver Behavior." Transportation Research Record: Journal of the Transportation Research Board 1725, no. 1 (2000): 102–8. http://dx.doi.org/10.3141/1725-14.
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Variable message signs (VMS) are programmable traffic control devices that convey nonpersonalized real-time information on network traffic conditions to drivers encountering them. Especially useful under incidents, VMS aim to influence driver routing decisions to enhance network performance. This study investigates the effect of different message contents on driver response under VMS. Presumably, if the message content is a significant factor in driver response, the traffic controller can use it as a control variable to influence network traffic conditions positively without compromising the integrity of information. This issue is addressed through an on-site stated preference user survey. Logit models are developed for drivers’ diversion decisions. The analysis suggests that content in terms of the level of detail of relevant information significantly affects drivers’ willingness to divert. Other significant factors include socio-economic characteristics, network spatial knowledge, and confidence in the displayed information. Results also indicate differences in the response attitudes of semitrailer truck drivers compared to other travelers. They provide substantive insights for the design and operation of VMS-based information systems.
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Hawkins, H. Gene, Dale L. Picha, and Carlos A. Lopez. "Mexican Driver Comprehension of U.S. Traffic Control Devices." Transportation Research Record: Journal of the Transportation Research Board 1628, no. 1 (1998): 15–24. http://dx.doi.org/10.3141/1628-03.
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The Mexican border areas of Texas possess many unique characteristics that are not present in other parts of the state. One of the most obvious is the prevalence of Spanish as the primary language. Another characteristic is the large number of drivers from Mexico. These two factors may limit the ability of border area drivers to understand traffic control devices. The research study was conducted to determine how well drivers from Mexico understand 33 of the more significant traffic control devices used in the United States and Texas. The survey utilized flash-cards with open-ended questions to assess comprehension levels. It was administered to northbound traffic with Mexican license plates at international bridges in two Texas border cities. Driver responses were recorded on audiotape and later separated into several categories, including “correct” and “partially correct.” The analysis of the responses indicate that, of the 45 questions that were asked about the 33 traffic control devices, approximately half (23) had correct and partially correct response rates of over 80 percent. Approximately a third (15) had correct response rates of over 80 percent. Many of the devices with lower comprehension levels among Mexican drivers are the same devices that have lower comprehension levels among Texas drivers.
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GAO, JIAN, and ZHIGANG ZHENG. "PHASE SYNCHRONIZATION IN DOUBLY DRIVEN CHAOTIC OSCILLATORS." International Journal of Modern Physics B 18, no. 20n21 (2004): 2945–52. http://dx.doi.org/10.1142/s021797920402535x.
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Phase synchronization of a chaotic oscillator that is driven by two chaotic signals is investigated. The anti-biased PS in the presence of biased coupling is found, i.e., the response oscillator can be phase synchronized by the drive with a weaker coupling rather than the stronger driver. The mechanism for this behavior is explored. In the non-PS region, alternating phase-locking is observed.
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Unrau, Daniel, and Jean Andrey. "Driver Response to Rainfall on Urban Expressways." Transportation Research Record: Journal of the Transportation Research Board 1980, no. 1 (2006): 24–30. http://dx.doi.org/10.1177/0361198106198000105.
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Quiroga, R. Quian, J. Arnhold, and P. Grassberger. "Learning driver-response relationships from synchronization patterns." Physical Review E 61, no. 5 (2000): 5142–48. http://dx.doi.org/10.1103/physreve.61.5142.
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Bu, Shou L., I.-Min Jiang, and Ming C. Ho. "Distinguishing a driver from a response system." Chaos: An Interdisciplinary Journal of Nonlinear Science 18, no. 1 (2008): 013130. http://dx.doi.org/10.1063/1.2896093.
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Kelly, Priscilla N. "Metabolism as a driver of immune response." Science 363, no. 6423 (2019): 137.10–139. http://dx.doi.org/10.1126/science.363.6423.137-j.
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Drakopoulos, Aris, and Richard W. Lyles. "Driver Age as a Factor in Comprehension of Left-Turn Signals." Transportation Research Record: Journal of the Transportation Research Board 1573, no. 1 (1997): 76–85. http://dx.doi.org/10.3141/1573-13.
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An experiment to measure driver comprehension of left-turn signal and sign configurations was conducted as part of a study to investigate the performance of left-turn signals used in various signal strategies. The responses of 191 individuals to 81 stimuli simulating left-turn signal phases were analyzed for the effect of signal message on driver comprehension. Stimuli included 17 left-turn signal displays used for permitted, protected, and protected/permitted left-turn strategies as well as left turns during nighttime or emergency flashing signal operations. Comprehension in the original study was based on a correct versus incorrect dichotomy: if the subject’s response agreed with a predetermined subset of possible answers, the answer was correct; all other answers were considered incorrect. These data are reanalyzed with three principal variations: ( a) individuals’ answers are based on a three-level correctness concept whereby answers considered incorrect in the previous study were further categorized into minor errors and serious errors depending on whether subjects incorrectly chose to “give away” their right-of-way or to violate other drivers’ right-of-way, respectively; ( b) signal message is introduced in the analysis as an explanatory variable of driver comprehension; and ( c) emphasis is placed on older drivers. Youngest, oldest, and female subjects were found to drive fewer kilometers per year than middle-aged males. Comprehension was found to deteriorate with driver age in terms of both higher serious error rates and lower correct answer rates. Flashing signals were the least well understood, whereas change and red interval stimuli were understood best by all age groups.
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Jurecki, Rafał, Miloš Poliak, and Marek Jaśkiewicz. "Young Adult Drivers: Simulated Behaviour in a Car-following Situation." PROMET - Traffic&Transportation 29, no. 4 (2017): 381–90. http://dx.doi.org/10.7307/ptt.v29i4.2305.
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This paper provides a description of driver testing in a simulator. As young drivers are more susceptible to collisions, this was done to determine how young drivers behaved in simulated road situations on a motorway. One of the traffic safety concerns is the failure to keep a proper distance from the vehicle in front, which may result in a rearend collision. The tests simulated car-following situations in which the preceding vehicle performed emergency braking. The experiments were conducted for two scenario variants using different distances from the vehicle in front. The drivers could perform the following emergency manoeuvres: braking with steering away or only braking. The driver response times were compared and analysed statistically. The results were used to determine the emergency manoeuvres performed by the drivers in the simulated road situations. The study reveals that the vehicle surroundings may have a considerable influence on the type of emergency manoeuvres and the driver response time.
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Summala, Heikki, Jarkko Hietamäki, Antero Lehikoinen, and Jukka Vierimaa. "Patrol Car Reduces Driver Reaction Times." Proceedings of the Human Factors Society Annual Meeting 32, no. 15 (1988): 919–22. http://dx.doi.org/10.1518/107118188786761802.
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This research showed that when having passed a patrol car on the road side, drivers' responses to a cyclist coming from a side road occur at a shorter latency. When stopped and interviewed afterwards, the drivers were not able to veridically estimate the time available for their response.
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Mole, Callum, Jami Pekkanen, William Sheppard, et al. "Predicting takeover response to silent automated vehicle failures." PLOS ONE 15, no. 11 (2020): e0242825. http://dx.doi.org/10.1371/journal.pone.0242825.
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Current and foreseeable automated vehicles are not able to respond appropriately in all circumstances and require human monitoring. An experimental examination of steering automation failure shows that response latency, variability and corrective manoeuvring systematically depend on failure severity and the cognitive load of the driver. The results are formalised into a probabilistic predictive model of response latencies that accounts for failure severity, cognitive load and variability within and between drivers. The model predicts high rates of unsafe outcomes in plausible automation failure scenarios. These findings underline that understanding variability in failure responses is crucial for understanding outcomes in automation failures.
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Noyce, David A., and Christopher R. Smith. "Driving Simulators for Evaluation of Novel Traffic-Control Devices: Protected–Permissive Left-Turn Signal Display Analysis." Transportation Research Record: Journal of the Transportation Research Board 1844, no. 1 (2003): 25–34. http://dx.doi.org/10.3141/1844-04.
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A study evaluated drivers’ comprehension of several experimental five-section protected–permissive left-turn (PPLT) signal displays. A full-scale driving simulator and static driver study were used. Study methods were compared while evaluating drivers’ comprehension and response to various combinations of five-section PPLT signal-display arrangements (horizontal, vertical, and cluster) and permissive left-turn indications (green ball, flashing red ball, flashing yellow ball, flashing red arrow, and flashing yellow arrow). The results showed that the type of five-section PPLT signal display arrangement has very little effect on driver comprehension of the permissive left-turn maneuver. The type of permissive indication used in five-section PPLT signal displays had a significant effect on driver comprehension, since the green ball, flashing yellow ball, and flashing yellow arrow were the best understood. When combining five-section PPLT signal-display arrangements and permissive indications, the five-section horizontal arrangement with a flashing-yellow-ball permissive indication had the highest level of driver comprehension. The lack of surrounding driving cues in the static driver study led to significantly higher fail-critical (serious) response rates. The green-ball permissive indication had a driver comprehension rate over 30% lower in the static study, clearly showing that drivers do not correctly comprehend the meaning of the green ball (assume it is protected) and use other information to make left-turn decisions while driving. The findings of this research show that driving simulation provides an effective study method and effectively replicates the actual driving environment. Simulators should be considered when conducting driver comprehension analyses.
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Bayıroğlu, H., G. F. Alışverişçi, and G. Ünal. "Nonlinear Response of Vibrational Conveyers with Nonideal Vibration Exciter: Superharmonic and Subharmonic Resonance." Mathematical Problems in Engineering 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/717543.
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Vibrational conveyers with a centrifugal vibration exciter transmit their load based on the jumping method. Common unbalanced-mass driver oscillates the trough. The motion is strictly related to the vibrational parameters. The transition over resonance of a vibratory system, excited by rotating unbalances, is important in terms of the maximum vibrational amplitude produced and the power demand on the drive for the crossover. The mechanical system is driven by the DC motor. In this study, the working ranges of oscillating shaking conveyers with nonideal vibration exciter have been analyzed analytically for superharmonic and subharmonic resonances by the method of multiple scales and numerically. The analytical results obtained in this study agree well with the numerical results.
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Tuplin, S., M. C. Best, and M. A. Passmore. "Improvement of perceived vehicle performance through adaptive electronic throttle control." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 217, no. 2 (2003): 97–106. http://dx.doi.org/10.1177/095440700321700203.
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With the advent of production electronic throttle control there is scope for increased customer satisfaction through the optimization of the throttle pedal demand map to individual drivers. The aim of this study is to develop algorithms to identify, from variables measured in real time on a test vehicle, the requirement for and the direction of adaptation of throttle pedal progression. An on-line appraisal procedure has been developed to identify the individual ‘ideal’ progression (IIP) for any driver. During the appraisal the subject is exposed to a series of pedal progressions, and their verbal response to each change is used to converge to their optimal setting. Vehicle data acquired on these appraisal drives have been regressed against IIP in a full factorial study, and the most statistically significant driver model established. A preliminary implementation of the model is used to demonstrate that throttle progression adapts appropriately towards IIP, thereby matching vehicle performance feel to driver expectations.
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Stan, L. Joanne. "Muriel Driver Memorial Lecture Discours Commémoratif Muriel Driver." Canadian Journal of Occupational Therapy 54, no. 4 (1987): 165–72. http://dx.doi.org/10.1177/000841748705400406.
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This paper explores the impact of a changing health care environment on the organization, management, and delivery of occupational therapy services in Canada. Political, economic, and other societal forces are having a profound effect on the demand for and the practice of occupational therapy. The influence of such forces on occupational therapy is discussed within the context of the profession's internal organization, external image, educational continuum, and practice directions. The paper reviews the profession's past response to such forces and develops approaches that occupational therapists individually and collectively can pursue to be more strategically positioned within the changing health care scene.
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Richardson, T. B., P. M. Forster, T. Andrews, et al. "Drivers of Precipitation Change: An Energetic Understanding." Journal of Climate 31, no. 23 (2018): 9641–57. http://dx.doi.org/10.1175/jcli-d-17-0240.1.
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The response of the hydrological cycle to climate forcings can be understood within the atmospheric energy budget framework. In this study precipitation and energy budget responses to five forcing agents are analyzed using 10 climate models from the Precipitation Driver Response Model Intercomparison Project (PDRMIP). Precipitation changes are split into a forcing-dependent fast response and a temperature-driven hydrological sensitivity. Globally, when normalized by top-of-atmosphere (TOA) forcing, fast precipitation changes are most sensitive to strongly absorbing drivers (CO2, black carbon). However, over land fast precipitation changes are most sensitive to weakly absorbing drivers (sulfate, solar) and are linked to rapid circulation changes. Despite this, land-mean fast responses to CO2 and black carbon exhibit more intermodel spread. Globally, the hydrological sensitivity is consistent across forcings, mainly associated with increased longwave cooling, which is highly correlated with intermodel spread. The land-mean hydrological sensitivity is weaker, consistent with limited moisture availability. The PDRMIP results are used to construct a simple model for land-mean and sea-mean precipitation change based on sea surface temperature change and TOA forcing. The model matches well with CMIP5 ensemble mean historical and future projections, and is used to understand the contributions of different drivers. During the twentieth century, temperature-driven intensification of land-mean precipitation has been masked by fast precipitation responses to anthropogenic sulfate and volcanic forcing, consistent with the small observed trend. However, as projected sulfate forcing decreases, and warming continues, land-mean precipitation is expected to increase more rapidly, and may become clearly observable by the mid-twenty-first century.
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Shen, Sijun, and David M. Neyens. "Assessing drivers' response during automated driver support system failures with non-driving tasks." Journal of Safety Research 61 (June 2017): 149–55. http://dx.doi.org/10.1016/j.jsr.2017.02.009.
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Viaene, Angela N., Iraklis Petrof, and S. Murray Sherman. "Synaptic Properties of Thalamic Input to Layers 2/3 and 4 of Primary Somatosensory and Auditory Cortices." Journal of Neurophysiology 105, no. 1 (2011): 279–92. http://dx.doi.org/10.1152/jn.00747.2010.
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We studied the synaptic profile of thalamic inputs to cells in layers 2/3 and 4 of primary somatosensory (S1) and auditory (A1) cortices using thalamocortical slices from mice age postnatal days 10–18. Stimulation of the ventral posterior medial nucleus (VPM) or ventral division of the medial geniculate body (MGBv) resulted in two distinct classes of responses. The response of all layer 4 cells and a minority of layers 2/3 cells to thalamic stimulation was Class 1, including paired-pulse depression, all-or-none responses, and the absence of a metabotropic component. On the other hand, the majority of neurons in layers 2/3 showed a markedly different, Class 2 response to thalamic stimulation: paired-pulse facilitation, graded responses, and a metabotropic component. The Class 1 and Class 2 response characteristics have been previously seen in inputs to thalamus and have been described as drivers and modulators, respectively. Driver input constitutes a main information bearing pathway and determines the receptive field properties of the postsynaptic neuron, whereas modulator input influences the response properties of the postsynaptic neuron but is not a primary information bearing input. Because these thalamocortical projections have comparable properties to the drivers and modulators in thalamus, we suggest that a driver/modulator distinction may also apply to thalamocortical projections. In addition, our data suggest that thalamus is likely to be more than just a simple relay of information and may be directly modulating cortex.
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Jones, Carissa, Rebecca Lachs, Emma Sturgill, et al. "Impact of immune checkpoint inhibitor (CPI) and EGFR tyrosine kinase inhibitor (TKI) sequence on time to treatment failure (TTF) among EGFR plus NSCLC treated in a community-based cancer research network." Journal of Clinical Oncology 39, no. 15_suppl (2021): 9099. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.9099.
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9099 Background: The development of CPIs and driver-targeted TKIs has transformed the treatment of NSCLC and increased survival rates. However, the role of CPIs in patients with oncogenic-driven NSCLC remains an area of investigation. We sought to examine the impact of CPI sequence on treatment response among patients with oncogenic-driver mutation-positive NSCLC. Methods: Patients with NSCLC being treated within the Sarah Cannon Research Institute network were identified through Genospace, Sarah Cannon’s clinico-genomic analytics platform. Advanced stage oncogenic-driven tumors (driver+) were defined as those with a record of receiving an FDA-approved TKI targeting EGFR, ALK, RET, ROS1, NTRK, MET, or BRAF. Kaplan-Meier estimates were used to examine TTF (defined as time from therapy start to start of next therapy, death, or loss to follow-up) and overall survival (OS). Results: We identified 12,352 patients with lung cancer and available therapy data (2005-2020), including 2,270 (18%) driver+ patients. Eleven percent (N=245) of driver+ patients received a CPI, including 120 (49%) with CPI prior to TKI, 122 (50%) with CPI post TKI, and 3 (1%) who received CPI both pre and post TKI. The CPI TTF was significantly longer for those who received CPI post TKI compared to those who received it prior (Table). EGFR+ tumors accounted for 82% (N=1,867) of driver+ patients, 10% of whom (N=188) received a CPI. Of the EGFR+/CPI+ patients, 78 patients (41%) received CPI prior to TKI, 107 (57%) received CPI post TKI, and 3 (2%) received CPI both pre and post TKI. EGFR+ tumors exposed to a CPI post TKI had a longer CPI TTF compared to patients who received it prior (Table). In contrast, there was no difference in length of benefit from TKI if it was received pre vs. post CPI (Table). There was also no difference in OS based on sequence of TKI and CPI (p=0.88). Larger sample sizes are needed for analysis of additional driver-stratified cohorts. Conclusions: Patients with oncogenic-driven NSCLC benefited from CPI longer when it was administered after TKI compared to before. Importantly, therapy sequence only affected length of benefit from CPIs and did not affect length of benefit from TKIs. This effect was present in EGFR+ NSCLC, but sample sizes were too small to determine if the same is true for other oncogenic-drivers. Therapy sequence had no impact on OS, indicating the presence of additional clinical, therapeutic, and/or genomic factors contributing to disease progression. Continued research is needed to better understand markers of CPI response in driver+ NSCLC.[Table: see text]
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Jashami, Hisham, David S. Hurwitz, Christopher Monsere, and Sirisha Kothuri. "Evaluation of Driver Comprehension and Visual Attention of the Flashing Yellow Arrow Display for Permissive Right Turns." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 8 (2019): 397–407. http://dx.doi.org/10.1177/0361198119843093.
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This research explored driver comprehension and behaviors in Oregon with respect to right-turn signal displays focusing on the Flashing Yellow Arrow (FYA) in a driving simulator. A counterbalanced, factorial design was chosen to explore three independent variables: signal indication type and active display, length of the right-turn bay, and presence of pedestrians. Driver decision-making and visual attention were considered. Data were obtained from 46 participants (21 women, 25 men) turning right 736 times in 16 experimental scenarios. A Mixed-effects Ordered Probit Model and a Linear mixed model were used to examine the influence of driver demographics on observed performance. Results suggest that the FYA indication improves driver comprehension and behavioral responses to the permissive right-turn condition. When presented with the FYA indication in the presence of pedestrians, nearly all drivers exhibited caution while turning and yielding to pedestrians and stopping when necessary. For the same turning maneuver, drivers presented with a circular green (CG) indication were less likely to exhibit correct behavior. At least for Oregon drivers, another clear finding was a general lack of understanding of the steady red arrow (SRA) display for right turns. Most drivers assume the SRA indication requires a different response than the circular red (CR) and remain stopped during the entire red interval, thus resulting in efficiency losses. These findings suggest that transportation agencies could potentially improve driver yielding behavior and pedestrian safety at signalized intersections with high volumes of permissive right turns from exclusive right-turn lanes by using the FYA display in lieu of a steady CG display.
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Dinakar, Swaroop, Jeffrey Muttart, Jeffrey Suway, et al. "Driver Response Times to Side Road Path Intrusions from SHRP-2 Naturalistic Database." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 1525–29. http://dx.doi.org/10.1177/1071181320641365.
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In an age where all major manufacturers are trying to get a better understanding of when an emergency response should be triggered, it becomes imperative to learn how humans respond to emergency events. If one can understand driver behavior, systems can be designed around the user to either assist drivers where they fail to perform well or completely eliminate them from the accident avoidance maneuver. In this study, 169 crash and near crash events from the SHRP2 dataset were analyzed. The response behavior of drivers was measured in events where the through drivers’ path was intruded upon by another vehicle perpendicular to its path. Overall, drivers responded significantly faster when the other vehicle failed to stop, and at intersection locations.
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So, Jaehyun Jason, Sungho Park, Jonghwa Kim, Jejin Park, and Ilsoo Yun. "Investigating the Impacts of Road Traffic Conditions and Driver’s Characteristics on Automated Vehicle Takeover Time and Quality Using a Driving Simulator." Journal of Advanced Transportation 2021 (June 23, 2021): 1–13. http://dx.doi.org/10.1155/2021/8859553.
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This study investigates the impacts of road traffic conditions and driver’s characteristics on the takeover time in automated vehicles using a driving simulator. Automated vehicles are barely expected to maintain their fully automated driving capability at all times based on the current technologies, and the automated vehicle system transfers the vehicle control to a driver when the system can no longer be automatically operated. The takeover time is the duration from when the driver requested the vehicle control transition from the automated vehicle system to when the driver takes full control of the vehicle. This study assumes that the takeover time can vary according to the driver’s characteristics and the road traffic conditions; the assessment is undertaken with various participants having different characteristics in various traffic volume conditions and road geometry conditions. To this end, 25 km of the northbound road section between Osan Interchange and Dongtan Junction on Gyeongbu Expressway in Korea is modeled in the driving simulator; the experiment participants are asked to drive the vehicle and take a response following a certain triggering event in the virtual driving environment. The results showed that the level of service and road curvature do not affect the takeover time itself, but they significantly affect the stabilization time, that is, a duration for a driver to become stable and recover to a normal state. Furthermore, age affected the takeover time, indicating that aged drivers are likely to slowly respond to a certain takeover situation, compared to the younger drivers. With these findings, this study emphasizes the importance of having effective countermeasures and driver interface to monitor drivers in the automated vehicle system; therefore, an early and effective alarm system to alert drivers for the vehicle takeover can secure enough time for stable recovery to manual driving and ultimately to achieve safety during the takeover.
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Baskov, V. N., D. A. Krasnikova, and E. I. Isaeva. "Effect of Driver Behaviour on Traffic Jams." World of Transport and Transportation 17, no. 4 (2020): 272–81. http://dx.doi.org/10.30932/1992-3252-2019-17-4-272-281.
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Driving in a traffic flow implies involvement in difficult traffic situations that adversely affects response time of a driver, which in turn is considered when estimating stopping distance of a vehicle and determines road safety. This relationship shows the effect of driver behaviour in traffic flow on the road traffic situation. The objective of the study was to study behavioural factors that influence driver’s decisions. The study used methods of driver behaviour modelling, mathematical modelling, experimental studies of the mental and psychological functions of drivers. Modelling the driver’s behaviour, considering various combinations of many behavioural and other factors, leads to a large number of options for mathematical description of driver behaviour, which makes it difficult to use this approach to describe behaviour of drivers under the conditions of a real street-road network. The research has analysed several works devoted to the study of control action of drivers, using unknown coefficients, describing a model of movement of vehicles considering accuracy of their control. Driving through an unregulated intersection is considered as the most complex and informative version of driver’s behaviour. It is found that when modelling a traffic flow, it is necessary to take into account the degree of resoluteness of drivers (through determination of a coefficient of resoluteness which is a random variable that takes into account the probability distribution of the coefficient’s value in conjunction with the probability distribution of the function of traffic flow intensity). The distribution of the coefficient of resoluteness of drivers, obtained from experimental data, was subject to analysis. It is determined that the driving style affects formation of traffic congestion. The assessment of the driving style is made through conditional classification of driver behaviour on the road, namely marked by manifestation of aggression and timidity. When studying the behaviour of timid and aggressive drivers, several pairs of trajectories and the dynamics of the corresponding traffic flow density, were considered and calculated based on Edie’s model. It has been confirmed that traffic congestion has the greatest negative effect on choleric drivers and sanguine drivers. Besides, there is a relationship between the response time of a driver and the change in his functional condition. It is concluded that to improve road safety thanks to a more accurate assessment of possible risks of formation of congestion situations, it is necessary to consider behavioural characteristics and temperaments of the drivers.
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Broen, Nancy L., and Dean P. Chiang. "Braking Response Times for 100 Drivers in the Avoidance of an Unexpected Obstacle as Measured in a Driving Simulator." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 18 (1996): 900–904. http://dx.doi.org/10.1177/154193129604001807.
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This study examined the effect of brake and accelerator pedal configuration on braking response time to an unexpected obstacle. One hundred subjects drove in the Dynamic Research, Inc, (DRI) Interactive Driving Simulator through a simulated neighborhood 21 times, each time with a different pedal configuration. Each subject was presented with an unexpected obstacle only one time, for one of three previously selected pedal configurations, to which he or she was instructed to brake as quickly as possible. Foot movements were recorded with a video camera mounted above the pedals. Data were analyzed manually, using time and course location information superimposed on the video data. Response times were analyzed using ANOVA to determine effects of pedal configuration and various driver factors. Response times ranged from 0.81 sec to 2.44 sec with a mean of 1.33 sec and a standard deviation of 0.27 sec. There was no significant effect of pedal configuration on response time. Driver age was significant, with increased age corresponding to increased response time. Car normally driven, gender, driver height, and shoe size had no significant effect.
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Hanowski, Richard J., and Barry H. Kantowitz. "Driver Memory Retention of In-Vehicle Information System Messages." Transportation Research Record: Journal of the Transportation Research Board 1573, no. 1 (1997): 8–16. http://dx.doi.org/10.3141/1573-02.
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Memory retention of drivers was tested for traffic- and traveler-related messages displayed on an in-vehicle information system (IVIS). Three research questions were asked: ( a) How does in-vehicle visual message format affect comprehension? ( b) How does message format affect memory retention? and ( c) What impact does driver age have on recall of in-vehicle visual messages? Nine younger (less than 30 years old) and nine older (65 years old or older) drivers participated in the experiment. As subjects steered the Battelle Automobile Simulator, an IVIS presented traveler-related messages. Two types of messages, symbols and text, were presented. Message recognition was tested immediately or 50 sec after the message left the IVIS. Except for low comprehension symbols, driver recognition scores on both text and symbol messages were similar. Younger drivers scored higher than older drivers in identifying the meaning of messages, particularly in the 50-sec question delay condition. Latency to respond to the questions and confidence in the responses were also affected by question delay, with longer response latencies and lower self-rated confidence scores for the longer delay conditions. Message presentation did not degrade vehicle control.
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Husain, M., J. Mattingley, C. Rorden, C. Kennard, and J. Driver. "Response from Husain, Mattingley, Rorden, Kennard and Driver." Trends in Cognitive Sciences 2, no. 5 (1998): 164–66. http://dx.doi.org/10.1016/s1364-6613(98)01168-1.
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Seppelt, Bobbie D., and John D. Lee. "Modeling Driver Response to Imperfect Vehicle Control Automation." Procedia Manufacturing 3 (2015): 2621–28. http://dx.doi.org/10.1016/j.promfg.2015.07.605.
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Jerome, Christian J., H. C. Neil Ganey, Mustapha Mouloua, and Peter A. Hancock. "Driver Workload Response to In-Vehicle Device Operations." International Journal of Occupational Safety and Ergonomics 8, no. 4 (2002): 539–46. http://dx.doi.org/10.1080/10803548.2002.11076543.
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