729 research outputs found
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Effects of Voluntary Handheld vs. Speech-Based Text Entry on Driving Performance in (Un)Predictable Critical Situations
No full textIt is often suggested that speech-based entry systems for text messages might provide a solution for the safety problems that arise because of handheld texting. However, although such systems have the advantage of allowing drivers to keep their eyes on the road, there is still a considerable portion of cognitive load associated with texting, which might impair the processing of relevant information. At the same time, drivers do not tend to text always and everywhere, but rather only in situations, they consider “suitable”. The selection of relevant test scenarios, and the free choice to (not) text in these scenarios are key aspects in the investigation of the effects of texting that have often been neglected. The aim of this experiment was to investigate the consequences of voluntary visual-manual and speech-based text messaging on reaction time and crashes in critical situations that might or might not be anticipated with the help of an environmental cue. We conducted a driving simulator study in which at one point, a child crossed the road, sometimes preceded by a ball rolling across, sometimes not. Participants (82, three groups: handheld writing, speech-based entry, control group) were free to (not) engage in a texting task while driving. While the pre-information had a positive impact on brake reaction time, there were no significant differences between the different groups in either crash rate or brake reaction time. The results highlight the role the design of test scenarios plays for the effects of texting on driving performance
Drivers' Assessment of Hazard Perception
No full textEncountering dangerous situations while driving is ubiquitous. Existing research suggest that specific populations such as, novice drivers are more prone to errors in detecting and responding to driving hazards. Hazard perception training programs have been developed in attempts to improve or accelerate the acquisition of such skills. However, drivers’ attitudes and knowledge regarding vulnerable populations and hazard perception training programs remain largely unknown. Three-hundred-five participants completed an online survey assessing their beliefs about influential factors affecting hazard detection and response, perceived usefulness and preferred types of training programs, and self-assessment of driving skills. Although many existing training programs are computer-based, participants preferred on-road hazard perception training. Such findings may assist in improving existing programs, which currently fail to show near- and far-transfer effects. Similarly, novice drivers reported being most likely to engage in training programs – possibly linked to their reported high value of the usefulness of such programs and awareness of their vulnerability to commit errors. Although autonomous vehicles should mitigate these errors, researchers and government officials suggest automated vehicles will not be commercially available for 10 years. Therefore, the results of the present study provide insight into drivers’ beliefs about dangerous situations, which may prove useful in developing and improving training programs aimed at mitigating crash risk
Driving with Foresight - Evaluating the Effect of Cognitive Distraction and Experience on Anticipating Events in Traffic
No full textDriving with foresight is essential for road safety. Anticipating upcoming events and intended maneuvers of other traffic participants requires the perception and processing of meaningful and valid cues. To provide insights into the cognitive mechanisms of anticipation, we investigated the effect of cognitive load, experience and cue characteristic on the anticipation of upcoming lane changes in urban driving scenarios. A two-step reaction method gathered low and high certainty anticipatory reactions of student and ambulance drivers. Results indicated that different anticipatory cues affected anticipatory performance. Target cues highly associated with the intended behavior of another traffic participant increased while context cues in the surrounding environment seemed to hamper anticipatory reactions. Furthermore, high cognitive load prolonged the latencies of low certainty anticipation but did not affect the performance quality. This initial intuition of an upcoming lane change was indicated earlier by experienced than by inexperienced drivers. These findings enhance the understanding of the human process of anticipation in dynamic uncritical traffic situations
Using Markov Chains to Understand the Sequence of Drivers' Gaze Transitions During Lane-Changes in Automated Driving
No full textThis paper reports the results of a driving simulator study, which analyzed differences in drivers’ raw gaze transition patterns during different stages of a lane-change maneuver, measured during manual, partially and conditionally automated driving. To understand whether the different levels of automation affected behaviour, and particularly how visual attention was distributed during a lane-change maneuver, a Markov chains approach was used to compare gaze transitions between the different information sources available in the surrounding road and cockpit environment, for each of the three drives. Results showed that drivers initiated fewer safety-related inspections (for example to the wing mirrors) during partial automation, throughout the whole lane change maneuver, possibly because they were focusing on how to the transition of control from automation. Drivers in this condition also had a higher probability of checking the system’s HMI, to verify the automation’s status. In contrast, during conditional automation, the lack of a need for vehicle control by the driver resulted in more gaze transitions between information sources, and fewer gazes to locations where a potential hazard could be present, when compared to manual. Finally, drivers generally only deviated their gaze towards information related to aspects of vehicle control they were responsible for, which we conclude could make them susceptible to missing hazards during both routine and safety-critical take-overs
A Survey Study Measuring People's Preferences Towards Automated and Non-Automated Ridesplitting
No full textRidesplitting is both common and important as it facilitates daily transportation needs. Alongside an increase in ridesplitting is the introduction of automated driving systems, which together, bring out the possibility of automated ridesplitting. However, previous studies have identified resistance in the acceptance of automated driving systems. In light of past research on automated driving systems, we used a survey to compare people’s preferences of automated ridesplitting to non-automated ridesplitting. Statistical and text mining techniques were leveraged to analyze the results. We found similarities in the numeric responses of important factors concerning automated and non-automated ridesplitting whereas there were large differences between automated and nonautomated ridesplitting in the text responses. Additionally, people prioritized cost and time in both automated and non-automated ridesplitting. These results can be used in the design of future ridesplitting services, especially with respect to increasing acceptance of and trust in automated ridesplitting services
Effect of Alert Presentation Mode and Hazard Direction on Driver Takeover from an Autonomous Vehicle
No full textAutonomous vehicles are becoming increasingly common. Although the level of automation varies between vehicles even the most advanced occasionally require driver input when the driving situation is complex, or the quality of the sensory data is poor. If driver input is needed the system must alert drivers that they will have to take over but these alerts may vary in their effectiveness in prompting rapid driver takeover (time to grip the steering wheel, percentage of appropriate takeover maneuvers) and situational awareness (driver attention to the threat that necessitated take over and understanding for why take over is necessary). In this study, we used a driving simulator operating in autonomous mode to compare 2 alert types (audio-visual, and audio alone) in 3 different takeover scenarios where hazards emerged from the front (a construction zone) or the left or right side (erratic behaviour in another driver: a rogue vehicle heading toward the drivers’ lane). We found that the takeover-time was faster after the audio-visual alert than the audio alert and situation awareness was better. The nature and direction of the hazard also had an effect. Situation awareness was poorer for hazards in front of the vehicle (a looming construction zone) as compared to the left and right of the driver (rogue vehicles heading toward the driver). These findings have important implications for interface design in autonomous vehicles
Is Driving Simulation a Viable Method for Examining Drivers' Ethical Choices? An Exploratory Study
No full textAdvanced vehicle technologies promise improved road safety but may still be subjected to situations where choices have to be made regarding safety impact to other road users. There is debate about the principles that should guide the programming of choices into automation algorithms, and an acknowledgment that choices made by automation may be subject to more scrutiny than those by humans. To better understand the landscape of decisions that human drivers encounter, it is important to examine the rationale, calculus, and motivations behind such choices. While there are various methods to examine human decision making, doing so in an ecologically valid manner is challenging, especially in this context of driving. To that end, this study was conducted to examine if driving simulation could help understand drivers’ ethical choices. Participants drove a route in a driving simulator that was programmed to end in a crash situation, one that placed the driver in a position of choosing between two crash outcomes. Participants were asked, after the fact, about their perceptions of the simulation and their decisions. Results indicate that drivers generally accepted simulation as realistic, but their post-experiment choices did not align with their actual decisions during the drive. Findings may have implications for the experimental study of ethical behaviors
How Demanding is "Just Driving?" A Cognitive Workload - Psychophysiological Reference Evaluation
No full textPhysiological arousal, measured as heart rate and skin conductance level, was recording during single-task highway driving (just driving), while driving and interacting with several voice-based and visual-manual infotainment user interfaces, while driving and engaging in multiple levels of a cognitive workload reference task (n-back), and while engaging in the same cognitive workload reference task under single-task (non-driving) conditions. Single-task highway driving was found to produce a level of physiological arousal in the same range as that of the relatively highly demanding 2-back task under non-driving conditions. While continuing innovations such as automatic transmission, power steering, as well as climate control, sound proofing and other comfort features, have reduced the overt demands of driving, these findings suggest that the remaining demand on resources during what has been thought of as “just driving” may be higher than many realize. The extent to which various implementations of longitudinal and lateral control driver assistance features being introduced change this dynamic is largely an open question
The Effect of Turn Signal Onset on Lateral Performance Measures When Overtaking a Lead Vehicle - Using Naturalistic Driving Environment
No full textLane changes occur very frequently on freeways. For the development of automated vehicles (AV), the detection of the other vehicles’ lane change maneuvers is an important task. Practically, turn signal is the most direct indicator to show the driver’s intention to change lanes. This study explored the Safety Pilot field-operational-test (SPFOT) database to investigate the use of turn signal and the relationship between the turn signal onset time and lane change performance measures, in order to assist AV anticipating other road users’ maneuvers. Driving data from 130 instrumented vehicles were extracted and 31,211 overtaking events were selected. It was found that the turn signal was used for about 70% of lane changes, and during half of those the turn signal was activated after the initiation of the lane change maneuver. Results showed that leftward overtaking maneuvers had longer lane change duration with slower lateral speed and lateral acceleration than rightward ones when the turn signal was not used. It was further found that the lane change duration can be estimated by the turn signal onset time. The shortest lane change durations of 5.33 s and 4.66 s occurred during those maneuvers when the turn signal was activated at 4.5 s and 5 s before the start of the leftward and rightward lane changes, respectively
An Investigation of Measuring Driver Anger with Electromyography
No full textThis research explores a novel approach to measuring driver anger using facial electromyography (EMG) while completing a navigation task on a driving simulator. Participants’ anger was induced by traffic events that were frustrating in nature as well as time pressure while having to follow navigational directions. Participants’ feeling of anger was assessed multiple times via subjective self-reports while being continuously monitored through a facial EMG. Participants’ trait driving anger was assessed using the Driving Anger Scale. Results showed that, compared to baseline measures, participants had significantly higher facial EMG activation values and subjective feelings of anger upon experiencing frustrating events, suggesting facial EMG as a reliable physiological measurement for inferring drivers’ feelings of anger. This experimental protocol can be used to assess anger in navigational contexts in future studies