Relationships between driving simulator performance and driving test results

This article is considered relevant because: 1) car driving is an everyday and safety-critical task; 2) simulators are used to an increasing extent for driver training (related topics: training, virtual reality, human – machine interaction); 3) the article addresses relationships between performance in the simulator and driving test results–a relevant topic for those involved in driver training and the virtual reality industries; 4) this article provides new insights about individual differences in young drivers' behaviour. Simulators are being used to an increasing extent for driver training, allowing for the possibility of collecting objective data on driver proficiency under standardised conditions. However, relatively little is known about how learner drivers' simulator measures relate to on-road driving. This study proposes a theoretical framework that quantifies driver proficiency in terms of speed of task execution, violations and errors. This study investigated the relationships between these three measures of learner drivers' (n = 804) proficiency during initial simulation-based training and the result of the driving test on the road, occurring an average of 6 months later. A higher chance of passing the driving test the first time was associated with making fewer steering errors on the simulator and could be predicted in regression analysis with a correlation of 0.18. Additionally, in accordance with the theoretical framework, a shorter duration of on-road training corresponded with faster task execution, fewer violations and fewer steering errors (predictive correlation 0.45). It is recommended that researchers conduct more large-scale studies into the reliability and validity of simulator measures and on-road driving tests.     

Relationships between driving simulator performance and driving test results

This article is considered relevant because: 1) car driving is an everyday and safety-critical task; 2) simulators are used to an increasing extent for driver training (related topics: training, virtual reality, human-machine interaction); 3) the article addresses relationships between performance in the simulator and driving test results--a relevant topic for those involved in driver training and the virtual reality industries; 4) this article provides new insights about individual differences in young drivers' behaviour. Simulators are being used to an increasing extent for driver training, allowing for the possibility of collecting objective data on driver proficiency under standardised conditions. However, relatively little is known about how learner drivers' simulator measures relate to on-road driving. This study proposes a theoretical framework that quantifies driver proficiency in terms of speed of task execution, violations and errors. This study investigated the relationships between these three measures of learner drivers' (n=804) proficiency during initial simulation-based training and the result of the driving test on the road, occurring an average of 6 months later. A higher chance of passing the driving test the first time was associated with making fewer steering errors on the simulator and could be predicted in regression analysis with a correlation of 0.18. Additionally, in accordance with the theoretical framework, a shorter duration of on-road training corresponded with faster task execution, fewer violations and fewer steering errors (predictive correlation 0.45). It is recommended that researchers conduct more large-scale studies into the reliability and validity of simulator measures and on-road driving tests.     

Using Queuing Network and Logistic Regression to Model Driving with a Visual Distraction Task

Computational dual-task models of driving with a secondary task can help compute, simulate, and predict driving behavior in dual task situations. These models can thus help improve the process of developing in-vehicle devices by reducing or eliminating the need for conducting driver experiments in the early stage of the development. Further, these models can help improve traffic flow simulation. This article develops a dual-task model of driving with a visual distraction task using the Queuing Network model of driver lateral control and a logistic regression model. The comparison between the model simulation data and the human data from drivers in a driving simulator shows that this computational model can perform driving with a secondary visual task well and its performance is consistent with the driver data.     

A comparison of the cell phone driver and the drunk driver

OBJECTIVE: The objective of this research was to determine the relative impairment associated with conversing on a cellular telephone while driving. BACKGROUND: Epidemiological evidence suggests that the relative risk of being in a traffic accident while using a cell phone is similar to the hazard associated with driving with a blood alcohol level at the legal limit. The purpose of this research was to provide a direct comparison of the driving performance of a cell phone driver and a drunk driver in a controlled laboratory setting. METHOD: We used a high-fidelity driving simulator to compare the performance of cell phone drivers with drivers who were intoxicated from ethanol (i.e., blood alcohol concentration at 0.08% weight/volume). RESULTS: When drivers were conversing on either a handheld or hands-free cell phone, their braking reactions were delayed and they were involved in more traffic accidents than when they were not conversing on a cell phone. By contrast, when drivers were intoxicated from ethanol they exhibited a more aggressive driving style, following closer to the vehicle immediately in front of them and applying more force while braking. CONCLUSION: When driving conditions and time on task were controlled for, the impairments associated with using a cell phone while driving can be as profound as those associated with driving while drunk. APPLICATION: This research may help to provide guidance for regulation addressing driver distraction caused by cell phone conversations.     

Distraction from multiple in-vehicle secondary tasks: vehicle performance and mental workload implications

This study investigates the impact of multiple in-vehicle information systems on the driver. It was undertaken using a high fidelity driving simulator. The participants experienced, paced and unpaced single tasks, multiple secondary tasks and an equal period of ‘normal’ driving. Results indicate that the interaction with secondary tasks led to significant compensatory speed reductions. Multiple secondary tasks were shown to have a detrimental affect on vehicle performance with significantly reduced headways and increased brake pressure being found. The drivers reported interaction with the multiple in-vehicle systems to significantly impose more subjective mental workload than either a single secondary task or ‘normal driving’. The implications of these findings and the need to integrate and manage complex in-vehicle information systems are discussed.     

Haptic gas pedal feedback

Active driver support systems either automate a control task or present warnings to drivers when their safety is seriously degraded. In a novel approach, utilising neither automation nor discrete warnings, a haptic gas pedal (accelerator) interface was developed that continuously presents car-following support information, keeping the driver in the loop. This interface was tested in a fixed-base driving simulator. Twenty-one drivers between the ages of 24 and 30 years participated in a driving experiment to investigate the effects of haptic gas pedal feedback on car-following behaviour. Results of the experiment indicate that when haptic feedback was presented to the drivers, some improvement in car-following performance was achieved, while control activity decreased. Further research is needed to investigate the effectiveness of the system in more varied driving conditions. Haptics is an under-used modality in the application of human support interfaces, which usually draw on vision or hearing. This study demonstrates how haptics can be used to create an effective driver support interface.     

On the highway measures of driver glance behavior with an example automobile navigation system

An over-the-road study of visual-manual destination entry using an example original equipment GPS-based navigation system was accomplished in traffic on urban streets and motorways. The evaluation used typical drivers, and a vehicle instrumented to record driver eye glances and fixations, driver control inputs, and lateral lane position. The primary task was to drive in a safe manner, in traffic, while maintaining speed and lateral lane position. As a secondary task, the drivers entered successive destinations while driving, using a touch screen, and at their own pace. They were told there was no need to enter the destination quickly. Results are shown for driver glance behavior, lane keeping performance, and subjective ratings. Overall, the drivers were able to accomplish the destination entry tasks with acceptably short glance durations, acceptable total task times, and with satisfactory subjective ratings for ease of entry.     

Haptic gas pedal feedback

Active driver support systems either automate a control task or present warnings to drivers when their safety is seriously degraded. In a novel approach, utilising neither automation nor discrete warnings, a haptic gas pedal (accelerator) interface was developed that continuously presents car-following support information, keeping the driver in the loop. This interface was tested in a fixed-base driving simulator. Twenty-one drivers between the ages of 24 and 30 years participated in a driving experiment to investigate the effects of haptic gas pedal feedback on car-following behaviour. Results of the experiment indicate that when haptic feedback was presented to the drivers, some improvement in car-following performance was achieved, while control activity decreased. Further research is needed to investigate the effectiveness of the system in more varied driving conditions. Haptics is an under-used modality in the application of human support interfaces, which usually draw on vision or hearing. This study demonstrates how haptics can be used to create an effective driver support interface.     

Distraction from multiple in-vehicle secondary tasks: vehicle performance and mental workload implications

This study investigates the impact of multiple in-vehicle information systems on the driver. It was undertaken using a high fidelity driving simulator. The participants experienced, paced and unpaced single tasks, multiple secondary tasks and an equal period of 'normal' driving. Results indicate that the interaction with secondary tasks led to significant compensatory speed reductions. Multiple secondary tasks were shown to have a detrimental affect on vehicle performance with significantly reduced headways and increased brake pressure being found. The drivers reported interaction with the multiple in-vehicle systems to significantly impose more subjective mental workload than either a single secondary task or 'normal driving'. The implications of these findings and the need to integrate and manage complex in-vehicle information systems are discussed.     

Assessment and monitoring of mental workload in subway train operations using physiological,subjective, and performance measures

Subway train operation is a complex, sociotechnical system that involves a variety of cognitively demanding tasks. The train operators are responsible for continuously monitoring the surrounding environment, maintaining awareness, processing information, and making decisions under risk. The resulting mental strain on operators can negatively affect their performance and the interaction of the human–machine system. The objective of this study was to evaluate if physiological, subjective, and performance measures could identify the level of mental workloads arising from routine and nonroutine operations in the subway system. A total of 11 subway train operators underwent different driving scenarios in a high‐fidelity simulator. The simulated tasks were divided into two categories: routine operations (preparing to drive and driving between stations without interruptions or emergencies) and nonroutine operation (responding to a tunnel fire, dealing with a high density of passengers, encountering a passenger/technician on the track, and responding to train failure). The mental workload was monitored and evaluated in these tasks using an electrocardiogram, subjective self‐rating scales, and driving performance. Both heart rate variability and performance measures (including reaction time and error rate) detected mental workload variations in the different operations. On the other hand, the subjective ratings (including NASA‐TLX) assessed the overall mental workload associated with a task, without explaining the mental demand variations within the task over time. Subway train drivers experienced different levels of mental workload during routine and nonroutine driving conditions. The findings of this study can be used to extract mental workload limits to optimize workload levels during train operations.     

The validity of driving simulation for assessing differences between in-vehicle informational interfaces: A comparison with field testing

Data from on-road and simulation studies were compared to assess the validity of measures generated in the simulator. In the on-road study, driver interaction with three manual address entry methods (keypad, touch screen and rotational controller) was assessed in an instrumented vehicle to evaluate relative usability and safety implications. A separate group of participants drove a similar protocol in a medium fidelity, fixed-base driving simulator to assess the extent to which simulator measures mirrored those obtained in the field. Visual attention and task measures mapped very closely between the two environments. In general, however, driving performance measures did not differentiate among devices at the level of demand employed in this study. The findings obtained for visual attention and task engagement suggest that medium fidelity simulation provides a safe and effective means to evaluate the effects of in-vehicle information systems (IVIS) designs on these categories of driver behaviour.

Statement of Relevance: Realistic evaluation of the user interface of IVIS has significant implications for both user acceptance and safety. This study addresses the validity of driving simulation for accurately modelling differences between interface methodologies by comparing results from the field with those from a medium fidelity, fixed-base simulator.     

Influence of age and proximity warning devices on collision avoidance in simulated driving

OBJECTIVE: We conducted a set of experiments to examine the utility of several different uni- and multimodal collision avoidance systems (CASs) on driving performance of young and older adult drivers in a high-fidelity simulator. BACKGROUND: Although previous research has examined the efficacy of different CASs on collision avoidance, there has been a dearth of studies that have examined such devices in different driving situations with different populations of drivers. METHOD: Several different CAS warnings were examined in varying traffic and collision configurations both without (Experiment 1a) and with (Experiment 2) a distracting in-vehicle task. RESULTS: Overall, collision avoidance performance for both potential forward and side object collisions was best for an auditory/visual CAS, which alerted drivers using both modalities. Interestingly, older drivers (60-82 years of age) benefited as much as younger drivers from the CAS, and sometimes they benefited more. CONCLUSION: These data suggest that CASs can be beneficial across a number of different driving scenarios, types of collisions, and driver populations. APPLICATION: These results have important implications for the design and implementation of CASs for different driver populations and driving conditions.     

Driving and side task performance: the effects of display clutter, separation, and modality

In-vehicle technologies (IVTs) create additional tasks for the driver. To the extent that these devices degrade driving performance, there will be safety concerns. This study examines the effects of display clutter from overlay, display separation, and modality on driving and IVT task performance. In a fixed-base simulator, 22 drivers drove different routes and responded to infrequent, unexpected road hazards while engaging in a phone number task presented by different displays. Visual displays were located on a head-up (overlaid on the visual horizon or adjacently, just above the vehicle hood) or head-down display (HDD) located near the midconsole. Alternatively, digits were presented auditorily. In general, there were no differences in performance for the adjacent and overlay displays; however, there were costs associated with the HDD and auditory display for some measures. In particular, responses to hazard events were slowed when drivers used the HDD. Overall, the adjacent display best supported performance on all relevant tasks. Potential applications of this research include the design of IVTs with respect to location and modality.     

Effects of advertising billboards during simulated driving

There is currently a great deal of interest in the problem of driver distraction. Most research focuses on distractions from inside the vehicle, but drivers can also be distracted by objects outside the vehicle. Major roads are increasingly becoming sites for advertising billboards, and there is little research on the potential effects of this advertising on driving performance. The driving simulator experiment presented here examines the effects of billboards on drivers, including older and inexperienced drivers who may be more vulnerable to distractions. The presence of billboards changed drivers’ patterns of visual attention, increased the amount of time needed for drivers to respond to road signs, and increased the number of errors in this driving task.     

Warn me now or inform me later: Drivers' acceptance of real-time and post-drive distraction mitigation systems

Vehicle crashes caused by driver distraction are of increasing concern. One approach to reduce the number of these crashes mitigates distraction by giving drivers feedback regarding their performance. For these mitigation systems to be effective, drivers must trust and accept them. The objective of this study was to evaluate real-time and post-drive mitigation systems designed to reduce driver distraction. The real-time mitigation system used visual and auditory warnings to alert the driver to distracting behavior. The post-drive mitigation system coached drivers on their performance and encouraged social conformism by comparing their performance to peers. A driving study with 36 participants between the ages of 25 and 50 years old (M=34) was conducted using a high-fidelity driving simulator. An extended Technology Acceptance Model captured drivers' acceptance of mitigation systems using four constructs: perceived ease of use, perceived usefulness, unobtrusiveness, and behavioral intention to use. Perceived ease of use was found to be the primary determinant and perceived usefulness the secondary determinant of behavioral intention to use, while the effect of unobtrusiveness on intention to use was fully mediated by perceived ease of use and perceived usefulness. The real-time system was more obtrusive and less easy to use than the post-drive system. Although this study included a relatively narrow age range (25 to 50 years old), older drivers found both systems more useful. These results suggest that informing drivers with detailed information of their driving performance after driving is more acceptable than warning drivers with auditory and visual alerts while driving.     

The use of expert knowledge in the development of simulations for train driver training

The current study was undertaken to inform the development of simulations for improving train driver’s decision making under degraded track conditions. Trains are sophisticated heavy machinery and their performance is ever increasing resulting in the driving task becoming more complex and progressively dominated by cognitive and perceptual skills. A critical part of reducing the potential for train driver error and of increasing performance lies in the appropriate design of simulation training. In the current study a cognitive task analysis, using the critical decision method (CDM) was undertaken using a focus group research design. The process resulted in increased knowledge of expert train driver decision-making processes. Across four major incidents analyzed 11 decision points, 17 cues, 30 essential responsive actions and 45 possible errors where identified. The use of these results for supporting the design of simulation training and associated performance measures is discussed.     

Speech-based E-mail and driver behavior: effects of an in-vehicle message system interface

As mobile office technology becomes more advanced, drivers have increased opportunity to process information "on the move." Although speech-based interfaces can minimize direct interference with driving, the cognitive demands associated with such systems may still cause distraction. We studied the effects on driving performance of an in-vehicle simulated "E-mail" message system; E-mails were either system controlled or driver controlled. A high-fidelity, fixed-base driving simulator was used to test 19 participants on a car-following task. Virtual traffic scenarios varying in driving demand. Drivers compensated for the secondary task by adopting longer headways but showed reduced anticipation of braking requirements and shorter time to collision. Drivers were also less reactive when processing E-mails, demonstrated by a reduction in steering wheel inputs. In most circumstances, there were advantages in providing drivers with control over when E-mails were opened. However, during periods without E-mail interaction in demanding traffic scenarios, drivers showed reduced braking anticipation. This may be a result of increased cognitive costs associated with the decision making process when using a driver-controlled interface when the task of scheduling E-mail acceptance is added to those of driving and E-mail response. Actual or potential applications of this research include the design of speech-based in-vehicle messaging systems.     

The role of intervening variables in driver–ACC cooperation

This paper analyzes the behavior of drivers using Adaptive Cruise Control (ACC) within the theoretical framework of Human–Machine Cooperation. The study was carried out on a driving simulator. Driving task performance data and responses to a trust questionnaire were analyzed in order to examine the relationship between driver reliance on ACC and such intervening variables as trust, perceived workload and perceived risk. The participants were divided a posteriori into two groups according to their use of the ACC device during the experimental run. The results show that high-use drivers seemed to cooperate more with ACC than low-use drivers, who tended to perceive more risk and a higher workload. These findings are discussed in the light of Riley's theory of operator reliance on automation.     

Shared steering control: How strong and how prompt should the intervention be for a better driving experience?

The lane keeping assistance system, a representative advanced driver assistance system, comprises a shared control that cooperates with the driver to achieve a common goal. The steering experience of the driver may vary significantly depending on the auto-steering control strategy of the system. In this study, we examined the driving experience with various steering control strategies. Nine control strategies (three torque amounts × three deviations in starting control) were established as prototypes. Eighteen drivers participated in the evaluation of each strategy in a highway environment on a driving simulator. A two-way repeated measure ANOVA was used to assess the effects of the system. Both the objective measures (standard deviation of lane position, steering reversal rate, and root mean square of lateral speed) and subjective measures (pleasure and arousal of emotion, trust, disturbance, and satisfaction) were evaluated and analyzed. The results showed that a torque amount of 3 Nm evoked feelings of high disturbance and negative emotional responses. A deviation in starting control (DEV) of 0.80 m yielded unstable lane keeping performances and evoked negative effects on pleasure, trust, and satisfaction. A regression model for the driver satisfaction recommended a torque of 2.32 Nm and a DEV of 0.27 m as the optimal design parameters. This proposed strategy is expected to improve the experience design of lateral semi-autonomous vehicles.     

The impact of cognitive workload on physiological arousal in young adult drivers: a field study and simulation validation

Physiological measures provide a continuous and relatively non-invasive method of characterising workload. The extent to which such measures provide sensitivity beyond that provided by driving performance metrics is more open to question. Heart rate and skin conductance were monitored during actual highway driving in response to systematically increased levels of cognitive demand using an auditory delayed digit recall task. The protocol was consistent with an earlier simulator study, providing an opportunity to assess the validity of physiological measures recorded during driving simulation. The pattern of change in heart rate with increased cognitive demand was highly consistent between field and simulator. The findings meet statistical criteria for both relative and absolute validity, although there was a trend for absolute levels to be higher under actual driving conditions. For skin conductance level, the pattern in both environments was also quite similar and a reasonable case for overall relative validity can be made.

Statement of Relevance: Growing complexity and multiple demands on modern drivers’ attention highlight the significance of determining whether physiological measures provide increased sensitivity in workload detection. Better understanding, including whether simulator assessments provide valid measures of real-world response patterns, has implications in evaluating and refining interface designs and for developing advanced workload managers.