Alarm mistrust in automobiles: how collision alarm reliability affects driving

Attentional warnings caused by driver monitoring systems: How often do they appear and how well are they understood?

The present study investigated the effects of a driver monitoring system that triggers attention warnings in case distraction is detected. Based on the EuroNCAP protocol, distraction could either be long glances away from the forward roadway (≥3s) or visual attention time sharing (>10 cumulative seconds within a 30 s time interval). In a series of manual driving simulator drives, 30 participants completed both driving related tasks (e.g., changing multiple lanes in dense traffic) and non-driving related tasks (e.g., infotainment operations). Results of warning frequencies revealed that visual attention time sharing warnings occurred more frequently than long distraction warnings. Moreover, there was a large number of attention warnings during driving related tasks. Results also revealed that participants' mental models tended to be less accurate when it came to understanding of the visual attention time sharing warnings as compared to the long distraction warnings, which were understood more accurately. Based on these observations, the work discusses the applicability and design of driver monitoring warnings.

A Closer Look at Warning Cues on the Sustained Attention to Response Task Performance

OBJECTIVES

We investigated the effects of auditory cues of varying reliability levels on response inhibition performance using a target detection task to determine if external cues offer performance benefits. Further, we examined how the slope of the speed accuracy trade-off changes as a function of auditory cue reliability and used the trade-off to understand where any performance gains may be realized.

BACKGROUND

Researchers have proposed that the sustained attention to response task (SART) can be used to study the mechanisms causing failures of response inhibition. External cues may mitigate the results of motor inhibition failure. The extent to which external cues can effectively aid performance depends on the level of cue reliability.

METHOD

Ninety-one participants performed three SARTs with auditory cue assistance at three different levels of reliability (i.e. 0%, 60% and 100% reliable at cueing imminent No-Go stimuli).

RESULTS

We observed fewer errors of commission and faster reaction time in conditions with higher cue reliability. The slope of speed-accuracy trade-off relationship was impacted by cue reliability and was not a simple linear function.

CONCLUSION

Reliable auditory cues aid performance by reducing reaction time and errors of commission. Auditory cues also impact the relationship between speed and accuracy trade-off.

APPLICATION

Insights of cue effectiveness at different reliability levels help people make informed decisions in developing automation interfaces or sensors based on expected performance. Reliable cues mitigate the risk of impulsive errors; however, the reliability has to be high to have a noticeable impact on the speed-accuracy trade-off.

Reliable and transparent in-vehicle agents lead to higher behavioral trust in conditionally automated driving systems

Trust is critical for human-automation collaboration, especially under safety-critical tasks such as driving. Providing explainable information on how the automation system reaches decisions and predictions can improve system transparency, which is believed to further facilitate driver trust and user evaluation of the automated vehicles. However, what the optimal level of transparency is and how the system communicates it to calibrate drivers' trust and improve their driving performance remain uncertain. Such uncertainty becomes even more unpredictable given that the system reliability remains dynamic due to current technological limitations. To address this issue in conditionally automated vehicles, a total of 30 participants were recruited in a driving simulator study and assigned to either a low or a high system reliability condition. They experienced two driving scenarios accompanied by two types of in-vehicle agents delivering information with different transparency types: "what"-then-wait (on-demand) and "what + why" (proactive). The on-demand agent provided some information about the upcoming event and delivered more information if prompted by the driver, whereas the proactive agent provided all information at once. Results indicated that the on-demand agent was more habitable, or naturalistic, to drivers and was perceived with faster system response speed compared to the proactive agent. Drivers under the high-reliability condition complied with the takeover request (TOR) more (if the agent was on-demand) and had shorter takeover times (in both agent conditions) compared to those under the low-reliability condition. These findings inspire how the automation system can deliver information to improve system transparency while adapting to system reliability and user evaluation, which further contributes to driver trust calibration and performance correction in future automated vehicles.

"Slow down. Rail crossing ahead. Look left and right at the crossing": In-vehicle auditory alerts improve driver behavior at rail crossings

Even though the rail industry has made great strides in reducing accidents at crossings, train-vehicle collisions at Highway-Rail Grade Crossings (HRGCs) continue to be a major issue in the US and across the world. In this research, we conducted a driving simulator study (N = 35) to evaluate a hybrid in-vehicle auditory alert (IVAA), composed of both speech and non-speech components, that was selected after two rounds of subjective evaluation studies. Participants drove through a simulated scenario and reacted to HRGCs with and without the IVAA present and through different music conditions and crossing devices. Driver simulator testing results showed that the inclusion of the hybrid IVAA significantly improved driving behavior near HRGCs in terms of gaze behavior, braking reaction, and approach speed to the crossing. The driving simulator study also showed the effects of background music and warning device types on driving performance. The study contributes to the large-scale implementation of IVAAs at HRGCs, as well as the development of guidelines toward a more standardized approach for IVAAs at HRGCs.

Can non-crash naturalistic driving data be an alternative to crash data for use in virtual assessment of the safety performance of automated emergency braking systems?

INTRODUCTION

Developers of in-vehicle safety systems need to have data allowing them to identify traffic safety issues and to estimate the benefit of the systems in the region where it is to be used, before they are deployed on-road. Developers typically want in-depth crash data. However, such data are often not available. There is a need to identify and validate complementary data sources that can complement in-depth crash data, such as Naturalistic Driving Data (NDD). However, few crashes are found in such data. This paper investigates how rear-end crashes that are artificially generated from two different sources of non-crash NDD (highD and SHRP2) compare to rear-end in-depth crash data (GIDAS).

METHOD

Crash characteristics and the performance of two conceptual automated emergency braking (AEB) systems were obtained through virtual simulations - simulating the time-series crash data from each data source.

RESULTS

Results show substantial differences in the estimated impact speeds between the artificially generated crashes based on both sources of NDD, and the in-depth crash data; both with and without AEB systems. Scenario types also differed substantially, where the NDD have many fewer scenarios where the following-vehicle is not following the lead vehicle, but instead catches-up at high speed. However, crashes based on NDD near-crashes show similar pre-crash criticality (time-to-collision) to in-depth crash data.

CONCLUSIONS

If crashes based on near-crashes are to be used in the design and assessment of preventive safety systems, it has to be done with great care, and crashes created purely from small amounts of everyday driving NDD are not of much use in such assessment.

PRACTICAL APPLICATIONS

Researchers and developers of in-vehicle safety systems can use the results from this study: (a) when deciding which data to use for virtual safety assessment of such systems, and (b) to understand the limitations of NDD.

Effect of mapping characteristic on audiovisual warning: Evidence from a simulated driving study

Advanced driver assistance systems (ADAS) can enhance road safety by sending warning signals to drivers. Multimodal signals are gaining attention in ADAS warning design because they offer redundant information that facilitates human-system communication. However, no consensus has been reached on which multimodal design offers optimal benefit to road safety. Icons iconically map the real world and are associated with fast recognition and response time. Therefore, this study aims to investigate whether visual and auditory icons will benefit the effectiveness of audiovisual multimodal warnings. Thirty-two participants (16 females) experienced four types of unimodal warnings (high and low mapping visual warnings and high and low mapping auditory warnings) and four types of audiovisual warnings (high mapping visual + high mapping auditory warning, low mapping visual + low mapping auditory warning, high mapping visual + low mapping auditory warning, and low mapping visual + high mapping auditory warning) in simulated driving conditions. Visual warnings are presented in a head-up display. Results showed that multimodal warnings outperformed unimodal warnings (i.e., modality effect). We found mapping effect in audiovisual warnings, but only high mapping auditory constituents benefited warning effectiveness. Eye movement results revealed that the high mapping constituents might distract drivers from the road. This study adds evidence that multimodal warnings can offer extra benefits to drivers and high mapping auditory signals should be included in multimodal warning design to achieve better driving performance.

Communication of Hazards in Mixed-Reality Telerobotic Systems: The Usage of Naturalistic Avoidance Cues in Driving Tasks

OBJECTIVE

This study investigates the effect of naturalistic visual cues on human avoidance behavior for a potential use in telerobotic user interfaces incorporating mixed-reality environments (e.g., augmented reality).

BACKGROUND

Telerobotic systems used in hazardous environments require interfaces that draw operators' attention to potential dangers. Existing means of hazard notification can often distract or induce stress in operators. In the design and implementation of such interfaces, visual semiotics plays a critical role in creating more effective interfaces. Naturalistic visual cues such as Aposematism or Kindchenschema have proven effective to communicate danger or caution in nature, but the application of these cues in visual systems have yet to be thoroughly investigated.

METHOD

A study was conducted where 40 volunteering participants were asked to control a remote vehicle in a simulated environment. The environment contained a set of neutral and visually augmented obstacles that were designed to provoke avoidance behavior.

RESULTS

The use of visual cues triggered greater avoidance behaviors in participants compared to neutral obstacles. The distance of avoidance was correlated with the type of cue present, with obstacles augmented by Aposematism (Cue A) having a greater participant-obstacle distance than Kindchenschema (Cue K).

CONCLUSIONS

This study shows the potential for the incorporation of naturalistic visual cues as a means to designate warning or caution in telerobotic environments.

APPLICATIONS

The findings can offer practical guidelines for the design of visual cues in telerobotic interfaces. The further incorporation of such cues may reduce operator stress and the amount of human errors in telerobotic operations.

An Experimental Validation of Masking in IEC 60601-1-8:2006-Compliant Alarm Sounds

OBJECTIVE

This research investigated whether the psychoacoustics of simultaneous masking, which are integral to a model-checking-based method, previously developed for detecting perceivability problems in alarm configurations, could predict when IEC 60601-1-8-compliant medical alarm sounds are audible.

BACKGROUND

The tonal nature of sounds prescribed by IEC 60601-1-8 makes them potentially susceptible to simultaneous masking: where concurrent sounds render one or more inaudible due to human sensory limitations. No work has experimentally assessed whether the psychoacoustics of simultaneous masking accurately predict IEC 60601-1-8 alarm perceivability.

METHOD

In two signal detection experiments, 28 nursing students judged whether alarm sounds were present in collections of concurrently sounding standard-compliant tones. The first experiment used alarm sounds with single-frequency (primary harmonic) tones. The second experiment's sounds included the additional, standard-required frequencies (often called subharmonics). T tests compared miss, false alarm, sensitivity, and bias measures between masking and nonmasking conditions and between the two experiments.

RESULTS

Miss rates were significantly higher and sensitivity was significantly lower for the masking condition than for the nonmasking one. There were no significant differences between the measures of the two experiments.

CONCLUSION

These results validate the predictions of the psychoacoustics of simultaneous masking for medical alarms and the masking detection capabilities of our method that relies on them. The results also show that masking of an alarm's primary harmonic is sufficient to make an alarm sound indistinguishable.

APPLICATION

Findings have profound implications for medical alarm design, the international standard, and masking detection methods.

The effects of warning characteristics on driver behavior in connected vehicles systems with missed warnings

With emerging new technologies, the vehicles in the future with connected vehicle systems (CVS) will be equipped with the ability to communicate with each other and aim to provide drivers with information in a timely and reliable way to improve driver safety. This study was designed to investigate the interaction effects of warning lead time (2.5 s vs. 4.5 s), warning reliability (73% vs. 89%), and speech warning style (command vs. notification) on driver performance and subjective evaluation of warnings in CVS. A driving simulator study with thirty-two participants was designed to simulate a connected vehicle environment with missed warnings due to failures in the communication network of the CVS. With regard to the response types, the results showed that notification warnings led to a lower probability of braking response and a higher probability of braking and steering response compared with command warnings. The results showed command warnings led to a smaller collision rate compared to notification warnings with the warning lead time of 2.5 s, whereas no significant difference of collision rates was found between two warning styles when the warning lead time is 4.5 s. These results suggest notification warnings should be selected when the warning lead time is longer and the warning systems are highly reliable, which resulted in higher safety benefits and higher subjective rating. Command warnings could be selected when the warning lead time is shorter since they led to more safety benefits, but such selection has to be made with caution since command warnings may limit drivers' response type and were perceived as less helpful than notification warnings.

Susceptibility to audio signals during autonomous driving

We investigate how susceptible human drivers are to auditory signals in three situations: when stationary, when driving, or when being driven by an autonomous vehicle. Previous research has shown that human susceptibility is reduced when driving compared to when being stationary. However, it is not known how susceptible humans are under autonomous driving conditions. At the same time, good susceptibility is crucial under autonomous driving conditions, as such systems might use auditory signals to communicate a transition of control from the automated vehicle to the human driver. We measured susceptibility using a three-stimulus auditory oddball paradigm while participants experienced three driving conditions: stationary, autonomous, or driving. We studied susceptibility through the frontal P3 (fP3) Electroencephalography Event-Related Potential response (EEG ERP response). Results show that the fP3 component is reduced in autonomous compared to stationary conditions, but not as strongly as when participants drove themselves. In addition, the fP3 component is further reduced when the oddball task does not require a response (i.e., in a passive condition, versus active). The implication is that, even in a relatively simple autonomous driving scenario, people's susceptibility of auditory signals is not as high as would be beneficial for responding to auditory stimuli.

Validation of Essential Acoustic Parameters for Highly Urgent In-Vehicle Collision Warnings

Objective The aim of this study was to validate the importance of key acoustic criteria for use as in-vehicle forward collision warning (FCW) systems. Background Despite recent advances in vehicle safety, automobile crashes remain one of the leading causes of death. As automation allows for more control of noncritical functions by the vehicle, the potential for disengagement and distraction from the driving task also increases. It is, therefore, as important as ever that in-vehicle safety-critical interfaces are intuitive and unambiguous, promoting effective collision avoidance responses upon first exposure even under divided-attention conditions. Method The current study used a driving simulator to assess the effectiveness of two warnings, one that met all essential acoustic parameters, one that met only some essential parameters, and a no-warning control in the context of a lead vehicle-following task in conjunction with a cognitive distractor task and collision event. Results Participants receiving an FCW comprising five essential acoustic components had improved collision avoidance responses relative to a no-warning condition and an FCW missing essential elements on their first exposure. Responses to a consistently good warning (GMU Prime) improved with subsequent exposures, whereas continued exposure to the less optimal FCW (GMU Sub-Prime) resulted in poorer performance even relative to receiving no warning at all. Conclusions This study provides support for previous warning design studies and for the validity of five key acoustic parameters essential for the design of effective in-vehicle FCWs. Application Results from this study have implications for the design of auditory FCWs and in-vehicle display design.

Driver compliance to take-over requests with different auditory outputs in conditional automation

Conditionally automated driving (CAD) systems are expected to improve traffic safety. Whenever the CAD system exceeds its limit of operation, designers of the system need to ensure a safe and timely enough transition from automated to manual mode. An existing visual Human-Machine Interface (HMI) was supplemented by different auditory outputs. The present work compares the effects of different auditory outputs in form of (1) a generic warning tone and (2) additional semantic speech output on driver behavior for the announcement of an upcoming take-over request (TOR). We expect the information carried by means of speech output to lead to faster reactions and better subjective evaluations by the drivers compared to generic auditory output. To test this assumption, N=17 drivers completed two simulator drives, once with a generic warning tone ('Generic') and once with additional speech output ('Speech+generic'), while they were working on a non-driving related task (NDRT; i.e., reading a magazine). Each drive incorporated one transition from automated to manual mode when yellow secondary lanes emerged. Different reaction time measures, relevant for the take-over process, were assessed. Furthermore, drivers evaluated the complete HMI regarding usefulness, ease of use and perceived visual workload just after experiencing the take-over. They gave comparative ratings on usability and acceptance at the end of the experiment. Results revealed that reaction times, reflecting information processing time (i.e., hands on the steering wheel, termination of NDRT), were shorter for 'Speech+generic' compared to 'Generic' while reaction time, reflecting allocation of attention (i.e., first glance ahead), did not show this difference. Subjective ratings were in favor of the system with additional speech output.

Injury mitigation estimates for an intersection driver assistance system in straight crossing path crashes in the United States

OBJECTIVE

Accounting for one fifth of all crashes and one sixth of all fatal crashes in the United States, intersection crashes are among the most frequent and fatal crash modes. Intersection advanced driver assistance systems (I-ADAS) are emerging vehicle-based active safety systems that aim to help drivers safely navigate intersections. The objective of this study was to estimate the number of crashes and number of vehicles with a seriously injured driver (Maximum Abbreviated Injury Scale [MAIS] 3+) that could be prevented or reduced if, for every straight crossing path (SCP) intersection crash, one of the vehicles had been equipped with an I-ADAS.

METHODS

This study retrospectively simulated 448 U.S. SCP crashes as if one of the vehicles had been equipped with I-ADAS. Crashes were reconstructed to determine the path and speeds traveled by the vehicles. Cases were then simulated with I-ADAS. A total of 30 variations of I-ADAS were considered in this study. These variations consisted of 5 separate activation timing thresholds, 3 separate computational latency times, and 2 different I-ADAS response modalities (i.e., a warning or autonomous braking). The likelihood of a serious driver injury was computed for every vehicle in every crash using impact delta-V. The results were then compiled across all crashes in order to estimate system effectiveness.

RESULTS

The model predicted that an I-ADAS that delivers an alert to the driver has the potential to prevent 0-23% of SCP crashes and 0-25% of vehicles with a seriously injured driver. Conversely, an I-ADAS that autonomously brakes was found to have the potential to prevent 25-59% of crashes and 38-79% of vehicles with a seriously injured driver. I-ADAS effectiveness is a strong function of design. Increasing computational latency time from 0 to 0.5 s was found to reduce crash and injury prevention estimates by approximately one third. For an I-ADAS that delivers an alert, crash/injury prevention effectiveness was found to be very sensitive to changes in activation timing (warning delivered 1.0 to 3.0 s prior to impact). If autonomous braking was used, system effectiveness was found to largely plateau for activation timings greater than 1.5 s prior to impact. In general, the results of this study suggest that I-ADAS will be 2-3 times more effective if an autonomous braking system is utilized over a warning-based system.

CONCLUSIONS

This study highlights the potential effectiveness of I-ADAS in the U.S. vehicle fleet, while also indicating the sensitivity of system effectiveness to design specifications. The results of this study should be considered by designers of I-ADAS and evaluators of this technology considering a future I-ADAS safety test.

Influence of lane departure warnings onset and reliability on car drivers' behaviors

Lane departures represent an important cause of road crashes. The objective of the present study was to assess the effects of an auditory Lane Departure Warning System (LDWS) for partial and full lane departures (onset manipulation) combined with missed warnings (reliability manipulation: 100% reliable, 83% reliable and 66% reliable) on drivers' performances and acceptance. Several studies indicate that LDWS improves drivers' performances during lane departure episodes. However, little is known about the effects of the warning onset and reliability of LDWS. Results of studies which looked at forward collision warning systems show that early warnings tend to improve drivers' performances and receive a better trust judgement from the drivers when compared to later warnings. These studies also suggest that reliable assistances are more effective and trusted than unreliable ones. In the present study, lane departures were brought about by means of a distraction task whilst drivers simulated driving in a fixed-base simulator with or without an auditory LDWS. Results revealed steering behaviors improvements with LDWS. More effective recovery maneuvers were found with partial lane departure warnings than with full lane departure warnings and assistance unreliability did not impair significantly drivers' behaviors. Regarding missed lane departure episodes, drivers were found to react later and spend more time out of the driving lane when compared to properly warned lane departures, as if driving without assistance. Subjectively, LDWS did not reduce mental workload and partial lane departure warnings were judged more trustworthy than full lane departure ones. Data suggests the use of partial lane departure warnings when designing LDWS and that even unreliable LDWS may draw benefits compared to no assistance.

A formal approach to discovering simultaneous additive masking between auditory medical alarms

The failure of humans to respond to auditory medical alarms has resulted in numerous patient injuries and deaths and is thus a major safety concern. A relatively understudied source of response failures has to do with simultaneous masking, a condition where concurrent sounds interact in ways that make one or more of them imperceptible due to physical limitations of human perception. This paper presents a method, which builds on a previous implementation, that uses a novel combination of psychophysical modeling and formal verification with model checking to detect masking in a modeled configuration of medical alarms. Specifically, the new method discussed here improves the original method by adding the ability to detect additive masking while concurrently improving method usability and scalability. This paper describes how these additions to our method were realized. It then demonstrates the scalability and detection improvements via three different case studies. Results and future research are discussed.

Effects of Alarm Modality and Alarm Reliability on Workload, Trust, and Driving Performance

As roads are getting more congested, the rate of automobile crashes due to driver error is also rising. Driving is an attention demanding task. The automobile industry has developed collision avoidance warning systems to increase situation awareness and roadway safety. Different modalities of alarms could be used to increase drivers’ situation awareness. The current study is a preliminary analysis of the effects of alarm reliability (70% & 90%) and alarm modality (auditory & tactile) on driver performance, trust in alarms, and perceived workload. Participants ( n=5) drove in a simulated environment. The results showed that drivers had fewer collisions in the tactile condition than the auditory condition. The findings of this research can inform which alarm modality is effective in improving driver performance and how practitioners can use this information to improve collision avoidance warning systems to increase roadway safety.

The impact of false warnings on partial and full lane departure warnings effectiveness and acceptance in car driving

In the past, lane departure warnings (LDWs) were demonstrated to improve driving behaviours during lane departures but little is known about the effects of unreliable warnings. This experiment focused on the influence of false warnings alone or in combination with missed warnings and warning onset on assistance effectiveness and acceptance. Two assistance unreliability levels (33 and 17%) and two warning onsets (partial and full lane departure) were manipulated in order to investigate interaction. Results showed that assistance, regardless unreliability levels and warning onsets, improved driving behaviours during lane departure episodes and outside of these episodes by favouring better lane-keeping performances. Full lane departure and highly unreliable warnings, however, reduced assistance efficiency. Drivers' assistance acceptance was better for the most reliable warnings and for the subsequent warnings. The data indicate that imperfect LDWs (false warnings or false and missed warnings) further improve driving behaviours compared to no assistance. Practitioner Summary: This study revealed that imperfect lane departure warnings are able to significantly improve driving performances and that warning onset is a key element for assistance effectiveness and acceptance. The conclusion may be of particular interest for lane departure warning designers.

Cooperative warning systems: The impact of false and unnecessary alarms on drivers' compliance

Cooperative warning systems have a great potential to prevent traffic accidents. However, because of their predictive nature, they might also go along with an increased frequency of incorrect alarms that could limit their effectiveness. To better understand the consequences associated with incorrect alarms, a driving simulator study with N=80 drivers was conducted to investigate how situational context and warning urgency jointly influence drivers' compliance with an unreliable advisory warning system (AWS). The participants encountered several critical urban driving situations and were either assisted by a 100% reliable AWS, a 60% reliable AWS that generated false alarms (without obvious reason) or a 60% reliable AWS that generated unnecessary alarms (with plausible reason). A baseline drive without any assistance was also introduced to the study. The warnings were presented either only visually or visual-auditory. In line with previous research, drivers' compliance and effectiveness of the AWS was reduced by false alarms but not by unnecessary alarms. However, this so-called cry wolf effect (Breznitz, 1984) was only found in the visual-auditory condition, whereas there was no effect of warning reliability in the condition with visual AWS. Furthermore, false but not unnecessary alarms caused the participants to rate the AWS less favourably during a follow-up interview. In spite of these negative effects of false alarms, a reduction in the frequency of safety-critical events (SCEs) and an earlier braking onset were evident in all assisted drives compared with that of non-assisted driving, even when the AWS was unreliable. The results may thus lower concerns about the negative consequences of warning drivers unnecessarily about upcoming traffic conflicts if the reasons of these alarms are comprehensible. From a perspective of designing AWS, we recommend to use less urgent warnings to prevent the cry wolf effect.

Management of Multiple Uavs with Imperfect Automation

Forty-two participants manipulated two or four unmanned aerial vehicles (UAVs) while monitoring an adjacent display for camouflaged tanks. They were sometimes supported in the tank-detection task by an automated target recognition system that operated at either a reliability of .9 with a threshold designed to provide an equal number of false-alarms and misses, .6 with a low threshold producing more automation false alarms, or .6 with a high threshold producing more automation misses. As taskload doubled, performance on the UAV task was significantly reduced. The effect was not mediated by the presence of automated aids, though the aids did influence performance in the tank-detection task. Tank detection was improved by both the highly-reliable aid and (to a lesser extent) by the miss-prone aid, but was not improved (and sometimes hurt) by the false-alarm prone condition. The results support the independence model of reliance and compliance proposed by Meyer (2001).

Predicting crash-relevant violations at stop sign-controlled intersections for the development of an intersection driver assistance system

OBJECTIVE

Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent.

METHODS

Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop-that is, required deceleration parameter (RDP) and brake application-were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities.

RESULTS

A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed some time for detecting violations but was able to substantially reduce false alarms to only 3.3% of all nonviolating approaches. Given good surface conditions (maximum braking capabilities = 0.8 g) and maximum effort, most drivers (55.3-71.1%) would be able to stop the vehicle regardless of the detection algorithm. However, given poor surface conditions (maximum braking capabilities = 0.4 g), few drivers (10.5-26.3%) would be able to stop the vehicle. Automatic emergency braking (AEB) would allow for early braking prior to driver reaction. If equipped with an AEB system, the results suggest that, even for the poor surface conditions scenario, over one half (55.3-65.8%) of the vehicles could have been stopped.

CONCLUSIONS

This study demonstrates the potential of I-ADAS to incorporate a stop sign violation detection algorithm. Repeating the analysis on a larger, more extensive data set will allow for the development of a more comprehensive algorithm to further validate the findings.

A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Understanding Autonomy in Future Systems

OBJECTIVE

We used meta-analysis to assess research concerning human trust in automation to understand the foundation upon which future autonomous systems can be built.

BACKGROUND

Trust is increasingly important in the growing need for synergistic human-machine teaming. Thus, we expand on our previous meta-analytic foundation in the field of human-robot interaction to include all of automation interaction.

METHOD

We used meta-analysis to assess trust in automation. Thirty studies provided 164 pairwise effect sizes, and 16 studies provided 63 correlational effect sizes.

RESULTS

The overall effect size of all factors on trust development was ḡ = +0.48, and the correlational effect was [Formula: see text]  = +0.34, each of which represented medium effects. Moderator effects were observed for the human-related (ḡ  = +0.49; [Formula: see text] = +0.16) and automation-related (ḡ = +0.53; [Formula: see text] = +0.41) factors. Moderator effects specific to environmental factors proved insufficient in number to calculate at this time.

CONCLUSION

Findings provide a quantitative representation of factors influencing the development of trust in automation as well as identify additional areas of needed empirical research.

APPLICATION

This work has important implications to the enhancement of current and future human-automation interaction, especially in high-risk or extreme performance environments.

THE EFFECTS ON DRIVING SPEED OF A HEAD-UP DISPLAY OF ROAD WARNINGS (1)

This study investigated the superimposition of the projected markings on the road with head-up display, as well as their effects on the driver's speed. Two experiments were conducted. In Exp. 1, driving operations were simulated with a desktop computer to assess 18 deceleration markings (from the factors position, shape, and color) and determined the factors and levels influencing driving speeds. Based on the results of Exp. 1, six deceleration markings (from the factors shape and color) were selected in the driving simulator for conducting Exp. 2. The results of Exp. 1 showed that markings at the sides were better than the markings in the center. In Exp. 2, there was no significant difference between the effects of the arrangement of markings and the change of shape and color on driving stability. Yellow and white colors had no significant effect on speed; however, bar markings were better than zigzag markings. The results indicated that the projection of markings on a head-up display was helpful for indicating necessary deceleration.

Car Gestures - Advisory warning using additional steering wheel angles

Advisory warning systems (AWS) notify the driver about upcoming hazards. This is in contrast to the majority of currently deployed advanced driver assistance systems (ADAS) that manage emergency situations. The target of this study is to investigate the effectiveness, acceptance, and controllability of a specific kind of AWS that uses the haptic information channel for warning the driver. This could be beneficial, as alternatives for using the visual modality can help to reduce the risk of visual overload. The driving simulator study (N=24) compared an AWS based on additional steering wheel angle control (Car Gestures) with a visual warning presented in a simulated head-up display (HUD). Both types of warning were activated 3.5s before the hazard object was reached. An additional condition of unassisted driving completed the experimental design. The subjects encountered potential hazards in a variety of urban situations (e.g. a pedestrian standing on the curbs). For the investigated situations, subjective ratings show that a majority of drivers prefer visual warnings over haptic information via gestures. An analysis of driving behavior indicates that both warning approaches guide the vehicle away from the potential hazard. Whereas gestures lead to a faster lateral driving reaction (compared to HUD warnings), the visual warnings result in a greater safety benefit (measured by the minimum distance to the hazard object). A controllability study with gestures in the wrong direction (i.e. leading toward the hazard object) shows that drivers are able to cope with wrong haptic warnings and safety is not reduced compared to unassisted driving as well as compared to (correct) haptic gestures and visual warnings.

Population distributions of time to collision at brake application during car following from naturalistic driving data

PROBLEM

Forward collision warning (FCW) systems are designed to mitigate the effects of rear-end collisions. Driver acceptance of these systems is crucial to their success, as perceived "nuisance" alarms may cause drivers to disable the systems. In order to make customizable FCW thresholds, system designers need to quantify the variation in braking behavior in the driving population. The objective of this study was to quantify the time to collision (TTC) that drivers applied the brakes during car following scenarios from a large scale naturalistic driving study (NDS).

METHODS

Because of the large amount of data generated by NDS, an automated algorithm was developed to identify lead vehicles using radar data recorded as part of the study. Using the search algorithm, all trips from 64 drivers from the 100-Car NDS were analyzed. A comparison of the algorithm to 7135 brake applications where the presence of a lead vehicle was manually identified found that the algorithm agreed with the human review 90.6% of the time.

RESULTS

This study examined 72,123 trips that resulted in 2.6 million brake applications. Population distributions of the minimum, 1st, and 10th percentiles were computed for each driver in speed ranges between 3 and 60 mph in 10 mph increments. As speed increased, so did the minimum TTC experience by drivers as well as variance in TTC. Younger drivers (18-30) had lower TTC at brake application compared to older drivers (30-51+), especially at speeds between 40 mph and 60 mph.

DISCUSSION

This is one of the first studies to use large scale NDS data to quantify braking behavior during car following. The results of this study can be used to design and evaluate FCW systems and calibrate traffic simulation models.

Dynamic vibrotactile signals for forward collision avoidance warning systems

OBJECTIVE

Four experiments were conducted in order to assess the effectiveness of dynamic vibrotactile collision-warning signals in potentially enhancing safe driving.

BACKGROUND

Auditory neuroscience research has demonstrated that auditory signals that move toward a person are more salient than those that move away. If this looming effect were found to extend to the tactile modality, then it could be utilized in the context of in-car warning signal design.

METHOD

The effectiveness of various vibrotactile warning signals was assessed using a simulated car-following task. The vibrotactile warning signals consisted of dynamic toward-/away-from-torso cues (Experiment 1), dynamic versus static vibrotactile cues (Experiment 2), looming-intensity- and constant-intensity-toward-torso cues (Experiment 3), and static cues presented on the hands or on the waist, having either a low or high vibration intensity (Experiment 4).

RESULTS

Braking reaction times (BRTs) were significantly faster for toward-torso as compared to away-from-torso cues (Experiments 1 and 2) and static cues (Experiment 2). This difference could not have been attributed to differential responses to signals delivered to different body parts (i.e., the waist vs. hands; Experiment 4). Embedding a looming-intensity signal into the toward-torso signal did not result in any additional BRT benefits (Experiment 3).

CONCLUSION

Dynamic vibrotactile cues that feel as though they are approaching the torso can be used to communicate information concerning external events, resulting in a significantly faster reaction time to potential collisions.

APPLICATION

Dynamic vibrotactile warning signals that move toward the body offer great potential for the design of future in-car collision-warning system.

Tactile warning signals for in-vehicle systems

The last few years have seen growing interest in the design of tactile warning signals to direct driver attention to potentially dangerous road situations (e.g. an impending crash) so that they can initiate an avoidance maneuver in a timely manner. In this review, we highlight the potential uses of such warning signals for future collision warning systems and compare them with more traditional visual and auditory warnings. Basic tactile warning signals are capable of promoting driver alertness, which has been demonstrated to be beneficial for forward collision avoidance (when compared to a no warning baseline condition). However, beyond their basic alerting function, directional tactile warning signals are now increasingly being utilized to shift the attention of the driver toward locations of interest, and thus to further facilitate their speeded responses to potential collision events. Currently, many researchers are focusing their efforts on the development of meaningful (iconic) tactile warning signals. For instance, dynamic tactile warnings (varying in their intensity and/or location) can potentially be used to convey meaningful information to drivers. Finally, we highlight the future research that will be needed in order to explore how to present multiple directional warnings using dynamic tactile cues, thus forming an integrated collision avoidance system for future in-vehicle use.

Comparison of Expected Crash and Injury Reduction from Production Forward Collision and Lane Departure Warning Systems

OBJECTIVES

The U.S. New Car Assessment Program (NCAP) now tests for forward collision warning (FCW) and lane departure warning (LDW). The design of these warnings differs greatly between vehicles and can result in different real-world field performance in preventing or mitigating the effects of collisions. The objective of this study was to compare the expected number of crashes and injured drivers that could be prevented if all vehicles in the fleet were equipped with the FCW and LDW systems tested under the U.S. NCAP.

METHODS

To predict the potential crashes and serious injury that could be prevented, our approach was to computationally model the U.S. crash population. The models simulated all rear-end and single-vehicle road departure collisions that occurred in a nationally representative crash database (NASS-CDS). A sample of 478 single-vehicle crashes from NASS-CDS 2012 was the basis for 24,822 simulations for LDW. A sample of 1,042 rear-end collisions from NASS-CDS years 1997-2013 was the basis for 7,616 simulations for FCW. For each crash, 2 simulations were performed: (1) without the system present and (2) with the system present. Models of each production safety system were based on 54 model year 2010-2014 vehicles that were evaluated under the NCAP confirmation procedure for LDW and/or FCW. NCAP performed 40 LDW and 45 FCW tests of these vehicles.

RESULTS

The design of the FCW systems had a dramatic impact on their potential to prevent crashes and injuries. Between 0 and 67% of crashes and 2 and 69% of moderately to fatally injured drivers in rear-end impacts could have been prevented if all vehicles were equipped with the FCW systems. Earlier warning times resulted in increased benefits. The largest effect on benefits, however, was the lower operating speed threshold of the systems. Systems that only operated at speeds above 20 mph were less than half as effective as those that operated above 5 mph with similar warning times. The production LDW systems could have prevented between 11 and 23% of drift-out-of-lane crashes and 13 and 22% of seriously to fatally injured drivers. A majority of the tested LDW systems delivered warnings near the point when the vehicle first touched the lane line, leading to similar benefits. Minimum operating speed also greatly affected LDW effectiveness.

CONCLUSIONS

The results of this study show that the expected field performance of FCW and LDW systems are highly dependent on the design and system limitations. Systems that delivered warnings earlier and operated at lower speeds may prevent far more crashes and injuries than systems that warn late and operate only at high speeds. These results suggest that future FCW and LDW evaluation should prioritize early warnings and full-speed range operation. A limitation of this study is that additional crash avoidance features that may also mitigate collisions-for example, brake assist, automated braking, or lane-keeping assistance-were not evaluated during the NCAP tests or in our benefits models. The potential additional mitigating effects of these systems were not quantified in this study.

Augmented reality cues to assist older drivers with gap estimation for left-turns

The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15% miss rate) did not appear to affect performance or driver ratings.

Learning three sets of alarms for the same medical functions: a perspective on the difficulty of learning alarms specified in an international standard

Three sets of eight alarms supporting eight functions specified in an international medical equipment standard (IEC 60601-1-8) were tested for learnability using non-anaesthetist participants. One set consisted of the tonal alarms specified in the standard. A second set consisted of a set of abstract alarms randomly selected from a database of abstract alarm sounds held by the authors. A third set of alarms was designed as indirect metaphors of the functions. Participants were presented with the alarms and then asked to identify them across ten blocks of eight trials. The results indicated a significant difference in learnability across the three sets of alarms. The indirect metaphors were learned significantly better than both other sets of alarms, and the randomly selected abstract alarms were learned significantly better than the alarms specified in the standard. The results suggest therefore that there are more readily learnable possible designs than those proposed in the standard. The use of auditory icons in particular should be given serious consideration as potential alarms for this application.

Age and gender differences in time to collision at braking from the 100-Car Naturalistic Driving Study

OBJECTIVE

Forward collision warning (FCW) is an active safety system that aims to mitigate the effect of forward collisions by warning the driver of objects in front of the vehicle. Success of FCW relies on how drivers react to the alerts. Drivers who receive too many warnings that they deem as unnecessary-that is, nuisance alarms-may grow to distrust and turn the system off. To reduce the perception of nuisance alarms, FCW systems can be tailored to individual driving styles, but these driving styles must first be characterized. The objective of this study was to characterize differences in braking behavior between age and gender groups in car-following scenarios using data from the 100-Car Naturalistic Driving Study.

METHODS

The data source for this study was the 100-Car Naturalistic Driving Study, which recorded the driving of 108 primary drivers for approximately a year. Braking behavior was characterized in terms of time to collision (TTC) at brake application, a common metric used in the design of warning thresholds of FCW. Because of the large volume of data analyzed, the TTC at which drivers braked during car-following situations was collected via an automated search algorithm. The minimum TTC for each vehicle speed 10 mph increment from 10 mph to 80 mph was recorded for each driver. Mixed model analysis of variance was used to examine the differences between age and gender groups.

RESULTS

In total, 527,861 brake applications contained in 11,503 trips were analyzed. Differences in TTC at braking were statistically significant for age and gender (P<.01 for both cases). Males age 18-20 (n=7) had the lowest average minimum TTC at braking of 2.5±0.8 s, and females age 31-50 (n=6) had the highest average minimum TTC at braking of 6.4±0.9 s. On average, women (n=32) braked at a TTC 1.3 s higher than men (n=52). Age was a statistically significant factor for TTC at braking between participants under 30 (n=42) and participants over 30 (n=42), with the latter braking 1.7 s on average before the former. No statistical significance was found between ages 18-20 (n=15) and 21-30 (n=27) or between ages 31-50 (n=23) and 50+(n=19).

CONCLUSIONS

There are clear statistical differences in TTC at braking for both gender and those over 30 vs. those under 30. Designers of FCW systems can use the data found in this study to tailor alert timings to the target demographic of a vehicle when designing forward collision warning systems. Appropriate alert timings for FCW systems will maximize effectiveness in collision reduction and mitigation.

Human performance in a multiple-task environment: effects of automation reliability on visual attention allocation

Diagnostic automation has been posited to alleviate the high demands of multiple-task environments; however, mixed effects have been found pertaining to performance aid success. To better understand these effects, attention allocation must be studied directly. We developed a multiple-task environment to study the effects of automation on visual attention. Participants interacted with a system providing varying levels of automation and automation reliability and then were transferred to a system with no support. Attention allocation was measured by tracking the number of times each task was viewed. We found that participants receiving automation allocated their time according to the task frequency and that tasks that benefited most from automation were most harmed when it was removed. The results suggest that the degree to which automation affects multiple-task performance is dependent on the relative attributes of the tasks involved. Moreover, there is an inverse relationship between support and cost when automation fails.

Augmented reality cues and elderly driver hazard perception

OBJECTIVE

The aim of this study was to evaluate the effectiveness of augmented reality (AR) cues in improving driving safety among elderly drivers who are at increased crash risk because of cognitive impairments.

BACKGROUND

Cognitively challenging driving environments pose a particular crash risk for elderly drivers. AR cuing is a promising technology to mitigate risk by directing driver attention to roadway hazards. We investigate whether AR cues improve or interfere with hazard perception in elderly drivers with age-related cognitive decline.

METHOD

A total of 20 elderly (M = 73 years, SD = 5) licensed drivers with a range of cognitive abilities measured by a speed-of-processing (SOP) composite participated in a 1-hr drive in an interactive, fixed-base driving simulator. Each participant drove through six straight, 6-mile-long, rural roadway scenarios following a lead vehicle. AR cues directed attention to potential roadside hazards in three of the scenarios, and the other three were uncued (baseline) drives. Effects of AR cuing were evaluated with respect to (a) detection of hazardous target objects, (b) interference with detecting nonhazardous secondary objects, and (c) impairment in maintaining safe distance behind a lead vehicle.

RESULTS

AR cuing improved the detection of hazardous target objects of low visibility. AR cues did not interfere with detection of nonhazardous secondary objects and did not impair ability to maintain safe distance behind a lead vehicle. SOP capacity did not moderate those effects.

CONCLUSION

AR cues show promise for improving elderly driver safety by increasing hazard detection likelihood without interfering with other driving tasks, such as maintaining safe headway.

Medical audible alarms: a review

OBJECTIVES

This paper summarizes much of the research that is applicable to the design of auditory alarms in a medical context. It also summarizes research that demonstrates that false alarm rates are unacceptably high, meaning that the proper application of auditory alarm design principles are compromised.

TARGET AUDIENCE

Designers, users, and manufacturers of medical information and monitoring systems that indicate when medical or other parameters are exceeded and that are indicated by an auditory signal or signals.

SCOPE

The emergence of alarms as a 'hot topic'; an outline of the issues and design principles, including IEC 60601-1-8; the high incidence of false alarms and its impact on alarm design and alarm fatigue; approaches to reducing alarm fatigue; alarm philosophy explained; urgency in audible alarms; different classes of sound as alarms; heterogeneity in alarm set design; problems with IEC 60601-1-8 and ways of approaching this design problem.

Effectiveness and acceptance of the intelligent speeding prediction system (ISPS)

BACKGROUND

The intelligent speeding prediction system (ISPS) is an in-vehicle speed assistance system developed to provide quantitative predictions of speeding. Although the ISPS's prediction of speeding has been validated, whether the ISPS can regulate a driver's speed behavior or whether a driver accepts the ISPS needs further investigation. Additionally, compared to the existing intelligent speed adaptation (ISA) system, whether the ISPS performs better in terms of reducing excessive speeds and improving driving safety needs more direct evidence.

OBJECTIVES

An experiment was conducted to assess and compare the effectiveness and acceptance of the ISPS and the ISA.

METHOD

We conducted a driving simulator study with 40 participants. System type served as a between-subjects variable with four levels: no speed assistance system, pre-warning system developed based on the ISPS, post-warning system ISA, and combined pre-warning and ISA system. Speeding criterion served as a within-subjects variable with two levels: lower (posted speed limit plus 1 mph) and higher (posted speed limit plus 5 mph) speed threshold. Several aspects of the participants' driving speed, speeding measures, lead vehicle response, and subjective measures were collected.

RESULTS

Both pre-warning and combined systems led to greater minimum time-to-collision. The combined system resulted in slower driving speed, fewer speeding exceedances, shorter speeding duration, and smaller speeding magnitude.

CONCLUSIONS

The results indicate that both pre-warning and combined systems have the potential to improve driving safety and performance.

The effects of external motivation and real-time automated feedback on speeding behavior in a naturalistic setting

OBJECTIVE

In this field experiment, the authors tested an alerting system and a monetary incentive system with the objective of reducing speeding more than 5 mph faster than the posted speed limit.

BACKGROUND

Speeding is a factor in a significant number of traffic fatalities. The systems tested in this project have been evaluated outside but not within the United States. These studies indicated that similar systems led to reductions in speeding.

METHOD

For this study, eight vehicles were instrumented such that vehicle speed and speed limits were linked in real time. A total of 50 participants drove assigned vehicles for 4 weeks. Week 1 was a baseline period; during Week 2 or Week 3, 40 participants experienced the alerting system that issued auditory and visual advisory signals when drivers exceeded the limit by 5 mph or more. Of these 40 individuals, 20 experienced the monetary incentive system during Weeks 2 and 3; Week 4 was a return-to-baseline period. A control group of 10 drivers experienced neither system during the study.

RESULTS

Results indicated that the incentive system resulted in significant reductions in driving faster than the posted limit, and the feedback system led to modest changes in speeding. In the condition in which drivers experienced the feedback and incentive, reductions in speeding were similar to those found during the incentive-only condition.

CONCLUSION

The technology tested in this study has potential to benefit traffic safety by reducing the incidence of driving faster than the posted limit, which should lead to a reduction in speed-related crashes.

APPLICATION

Insurers provide incentive-based discounts on premiums. Combining this technology with such a discount program may improve traffic safety significantly.

Impact of totally and partially predictive alert in distracted and undistracted subjects: An event related potential study

Rear-end collisions represent about 30% of all car crashes and generate a significant economic cost for society. Driver inattention has been identified as the most important contributing factor in rear-end collisions. One possible countermeasure is the use of systems that warn drivers of potential collisions. Nevertheless, because of technical constraints, the conception of perfect warning systems is difficult to achieve and technical literature shows that these kinds of systems can be prone to false alerts or misses. The main objective of this study is to assess the impact of such a warning system on the processing of a relevant driving visual cue while taking into account the reliability of the system and the attentional state of the participants. For this, we designed a laboratory experiment during which we recorded behavioral data and brain activity (event related potential, ERP) following the detection of a visual target. Three warning conditions were designed: (1) no alert was presented before the visual target; (2) an auditory alert was presented before each target; (3) an alert was presented before the target in 70% of the trials (15% only had the alert without the target, and 15% only had the target without the alert). In addition, participants had to perform this visual detection task either alone (simple task) or with a concurrent problem-solving task (dual task). Behavioral and electrophysiological data contribute to revealing (1) that there is a behavioral gain induced by the alert and (2) that this gain is at least linked with a time-saving aspect at both the sensory and cognitive stages of neural information processing. Nevertheless, this impact depends on the attentional states of the participant and on the reliability of the alert.

Response preparation in a lane change task

Anticipation of future events is crucial for driving performance and safety. The aim of this study is to assess the relevance of theoretical frameworks of response preparation (response priming, movement integration theory) for driving. In a customised lane change task, valid and invalid primes were used to indicate the direction of the forthcoming lane changes. Reaction time (RT) and phase durations from steering movements served as dependent measures. In agreement with the theoretical considerations, we found a clear effect of validity on RT and steering kinematics. RTs were faster and the duration of the initial steering phase was shorter with valid than with invalid advance information. The experimental outcomes suggest that the theoretical considerations about benefits and costs of response preparation can be generalised to driving manoeuvres. Therefore, response priming paradigms might be well suited to investigate preparatory effects of advance information, e.g. in the context of advanced driving assistance systems.

PRACTITIONER SUMMARY

Benefits and costs of response preparation were assessed in the context of driving. The findings suggest that the understanding of preparatory processes is of relevance to enhance driving performance and safety. It is possible to derive some implications that may be useful for the design of assistance and information systems.

Directing driver attention with augmented reality cues

This simulator study evaluated the effects of augmented reality (AR) cues designed to direct the attention of experienced drivers to roadside hazards. Twenty-seven healthy middle-aged licensed drivers with a range of attention capacity participated in a 54 mile (1.5 hour) drive in an interactive fixed-base driving simulator. Each participant received AR cues to potential roadside hazards in six simulated straight (9 mile long) rural roadway segments. Drivers were evaluated on response time for detecting a potentially hazardous event, detection accuracy for target (hazard) and non-target objects, and headway with respect to the hazards. Results showed no negative outcomes associated with interference. AR cues did not impair perception of non-target objects, including for drivers with lower attentional capacity. Results showed near significant response time benefits for AR cued hazards. AR cueing increased response rate for detecting pedestrians and warning signs but not vehicles. AR system false alarms and misses did not impair driver responses to potential hazards.

Adapting ISA system warnings to enhance user acceptance

Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road section with singular characteristics that require a lower safe speed than the current speed. In spite of the extensive tests performed using ISA systems, few works show how warnings can be adapted to the driver. This paper describes a method to adapt warning parameters (safe speed on curves, zone of influence of a singular stretch, deceleration process and reaction time) to normal driving behavior. The method is based on a set of tests with and without the ISA system. This adjustment, as well as the analysis of driver acceptance before and after the adaptation and changes in driver behavior (changes in speed and path) resulting from the tested ISA regarding a driver's normal driving style, is shown in this paper. The main conclusion is that acceptance by drivers increased significantly after redefining the warning parameters, but the effect of speed homogenization was not reduced.

Cross-modal warnings for orienting attention in older drivers with and without attention impairments

Older adults are overrepresented in fatal crashes on a per-mile basis. Those with useful field of view (UFOV) reductions show a particularly elevated crash risk that might be mitigated with vehicle-based warnings. To evaluate cross-modal cues that could be used in these warnings, we applied a variation of Posner's orienting of attention paradigm. Twenty-nine older drivers with UFOV impairments and 32 older drivers without impairments participated. Cues were presented in either a single modality or a combination of modalities (visual, auditory, haptic). Drivers experienced three cue types (valid spatial information, invalid spatial information, neutral) and an uncued baseline. Following each cue, drivers discriminated the direction of a target (a Landolt square with a gap facing up or down) in the visual panorama. Drivers with and without UFOV impairments showed comparable response times (RTs) across the different cue modalities and cue types. Both groups benefited most from auditory and auditory/haptic cues. Redundant visual cues, when paired with auditory cues, undermined performance rather than enhanced it. Overall, drivers responded faster to targets with valid spatial information followed by neutral, invalid, and uncued targets. Cues provide the greatest benefit in alerting rather than orienting the driver. The cue expected to be most effective at orienting attention - the extra-vehicular cue - performs most poorly when the spatial information is either invalid or neutral. Even when the spatial information is valid the extra-vehicular cue underperforms the auditory cues. The results suggest that temporal information dominates spatial information in the ability of cues to speed responses to targets. This study represents a first step in assessing whether combining a cognitive science paradigm and a driving simulator environment can quickly assess how different warning signals alert and orient drivers.

Detection of new in-path targets by drivers using Stop & Go Adaptive Cruise Control

This paper reports on the design and evaluation of in-car displays used to support Stop & Go Adaptive Cruise Control. Stop & Go Adaptive Cruise Control is an extension of Adaptive Cruise Control, as it is able to bring the vehicle to a complete stop. Previous versions of Adaptive Cruise Control have only operated above 26 kph. The greatest concern for these technologies is the appropriateness of the driver's response in any given scenario. Three different driver interfaces were proposed to support the detection of modal, spatial and temporal changes of the system: an iconic display, a flashing iconic display, and a representation of the radar. The results show that drivers correctly identified more changes detected by the system with the radar display than with the other displays, but higher levels of workload accompanied this increased detection.

Looming auditory collision warnings for driving

OBJECTIVE

A driving simulator was used to compare the effectiveness of increasing intensity (looming) auditory warning signals with other types of auditory warnings.

BACKGROUND

Auditory warnings have been shown to speed driver reaction time in rear-end collision situations; however, it is not clear which type of signal is the most effective. Although verbal and symbolic (e.g., a car horn) warnings have faster response times than abstract warnings, they often lead to more response errors.

METHOD

Participants (N=20) experienced four nonlooming auditory warnings (constant intensity, pulsed, ramped, and car horn), three looming auditory warnings ("veridical," "early," and "late"), and a no-warning condition. In 80% of the trials, warnings were activated when a critical response was required, and in 20% of the trials, the warnings were false alarms. For the early (late) looming warnings, the rate of change of intensity signaled a time to collision (TTC) that was shorter (longer) than the actual TTC.

RESULTS

Veridical looming and car horn warnings had significantly faster brake reaction times (BRT) compared with the other nonlooming warnings (by 80 to 160 ms). However, the number of braking responses in false alarm conditions was significantly greater for the car horn. BRT increased significantly and systematically as the TTC signaled by the looming warning was changed from early to veridical to late.

CONCLUSION

Looming auditory warnings produce the best combination of response speed and accuracy.

APPLICATION

The results indicate that looming auditory warnings can be used to effectively warn a driver about an impending collision.