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SUMMARY REPORT
This summary report is an archived publication and may contain dated technical, contact, and link information
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Publication Number:  FHWA-HRT-17-025    Date:  December 2017
Publication Number: FHWA-HRT-17-025
Date: December 2017

 

Cooperative Adaptive Cruise Control Human Factors Study

Chapter 2. Workload, Distraction, Arousal, Trust, and Crash Avoidance

This chapter presents an overview of the experiment assessing workload, arousal, distraction, trust, and crash avoidance.

Method

Four groups drove the simulated vehicle over the same 39-mi stretch of limited-access roadway. Three of the four groups drove a CACC-equipped vehicle in a platoon with other CACC-equipped vehicles, but the nature of the event that occurred at the end of the drive differed. The fourth group manually controlled its following distance within a platoon in which all of the other vehicles used CACC. For most of the distance traveled, the roadway and the behavior of other vehicles was the same for all groups.

Workload Assessment

Driver workload was assessed by administration of the National Aeronautics and Space Administration Task Load Index (NASA-TLX).(12) Workload was assessed four times. The first assessment was during a practice drive and was intended to familiarize participants with providing verbal responses to the NASA-TLX protocol. The second workload administration was 5 min into the main scenario, just after a vehicle merged into the platoon between the participant’s vehicle and the vehicle the participant had been directly behind. This NASA-TLX administration was intended to assess the workload imposed by a vehicle halving the following distance between the participant and the vehicle ahead. The third assessment was 15 min into the drive and was intended to assess the workload associated with driving in a CACC platoon when no changes in the platoon had occurred for 10 min and 11.7 mi of uneventful driving. The final assessment was near the end of the drive and immediately followed the events that varied between groups. The second and third workload assessments enabled comparison of workload between the three CACC groups (which should not have differed from each other at these points) and the control group (which had to manually maintain gap).

Physiological Arousal

Physiological arousal was assessed by measuring eyelid closure, pupil diameter, and skin conductance. These measures were assessed at five 30-s periods during the drive. These measures were intended to assess changes in arousal as a result of an initial merge event, after 10 min of uneventful driving, and as a result of the final events.

Distraction

Automation has generally been intended to reduce driver workload. A positive result of automation would be a more relaxing and rewarding driving experience. A less positive result might be that the driver felt free to engage in more nondriving tasks that might subsequently result in less attention to the driving task. Participants were allowed to play the radio, use their cell phone, or otherwise engage in nondriving-related activities. Engagement in nondriving activities was neither encouraged nor discouraged. Participants were instructed to drive as they normally would with the exception of CACC usage and gap maintenance. The extent to which participants engaged in voluntary nondriving activities and how these correlated with physiological arousal and crash avoidance was observed. Aside from assessing these correlations, no attempt was made to measure the extent, if any, to which these activities might be distracting.

Crash Avoidance

At 34.6 mi from the start, the behavior of other vehicles varied between groups. Two groups experienced a non-CACC-equipped vehicle cutting in front of the platoon and overturning. Of these two groups, one was using CACC with a 1.1-s gap, and the other, the control group, was manually maintaining a 1.1-s gap. This manipulation was intended to test whether CACC-equipped drivers would be more or less likely to avoid a crash when sudden hard braking was required. If the convenience of CACC induced drivers to become complacent, distracted, or unaware or to have a very low level of arousal, then it might be expected that the CACC group would experience more crashes than the control group, which, because it was forced to monitor gap distance manually, might be expected to be more aware, aroused, and attentive. However, the CACC system had partial braking up to 0.4 g, and in this scenario, braking was initiated before the brake lights of the lead car activated. Also, when the CACC system began to brake, there was a loud series of beeps intended to alert the driver of the need to take longitudinal control. This beeping carried a meaning similar to that of a forward collision warning. With the automated assistance of the CACC system, it was theorized that the CACC group might gain the slight reaction time advantage. This test of crash avoidance would be specific to the warning and brake response programmed into the system, and thus, the results could not be expected to generalize to all potential CACC implementations. Nonetheless, they should give a clue whether similar CACC systems would be more likely to be a boon or detriment to safety and might provide a starting point for exploration of CACC warning parameters and the effects of automated braking.

Equipment and Materials

The following subsections describe the equipment and materials used for this experiment.

The Driving Simulator

The experiment was conducted in the FHWA Highway Driving Simulator. The simulator’s screen consisted of a 200-degree portion of a cylinder with a radius of 8.9 ft. The design eye point of the simulator was 9.5 ft from the screen. The stimuli were projected onto the screen by five projectors with resolutions of 2,048 horizontal by 1,536 vertical pixels. Participants sat in a compact sedan. The car’s instrument panel, brake, and accelerator pedal all functioned in a manner similar to real-world compact cars.

Eye-Tracking System

The simulator was equipped with a four-camera dashboard-mounted eye-tracking system that sampled at 120 Hz. The system tracked horizontal gaze direction from approximately the right outside mirror to the left outside mirror and vertical gaze direction from the bottom of the instrument panel to the top of the windscreen. In this study, the eye-tracking system was primarily used to determine at which vehicle displays the participant was looking. In addition to tracking the direction of gaze, the eye-tracking system computed eyelid opening and pupil diameter.

Multifunction Display

The model of sedan used for the simulator was not originally equipped with cruise control controls or displays. For this experiment, a 7-inch diagonal liquid crystal display touch screen was mounted on the center console above the radio. For the CACC conditions, the touch screen was used to toggle the CACC system on and off. Throughout the experiment, the set speed remained 70 mi/h, and the gap target remained 1.1 s. The participants were instructed that the gap and speed setting adjustments were nonfunctional and intended only to assist in explaining the ACC concept. No participants were observed trying to change these settings.

The center console display for the control group was not interactive. A black bar on the colored ribbon displayed the current gap between the control participant’s front bumper and the rear bumper of the vehicle ahead. Control participants were asked to try to maintain a 1.1-s gap and keep the black bar in the green region of the ribbon (i.e., between 0.8 and 1.3 s).

Skin Conductance Sensor

Galvanic skin response (GSR) was measured with silver-chloride salt electrodes placed on the palmar-side base of two fingers on the participant’s left hand. The electrodes were connected to a small sensor with a Bluetooth® transmitter strapped to the left wrist.

The Simulation Scenarios

Participants drove in a dedicated lane on a simulated eight-lane interstate highway (four lanes in each direction). Participants drove in the lane adjacent to the median. This lane was separated from the other lanes by F-type barriers. A typical portion of the roadway is depicted in figure 1. The center dedicated lane was accessed from the left side of the roadway from a ramp with a ramp meter. The simulation began with the participant’s vehicle in the third position within a platoon of four vehicles. When the ramp meter turned green, the platoon accelerated and merged into the CACC lane and cruised at 70 mi/h.

This figure shows a screen capture of a typical section of the simulated roadway. The back end of a gray sport-utility vehicle is shown in the distance in the middle of a single freeway lane. The lane has a yellow edge line on the left and a white edge line on the right. There is a concrete barrier a short distance to the right of the right edge line. To the left of the left edge line is a breakdown lane. To the left of the breakdown lane is a grassy median.

Figure 1. Screen capture. A typical section of the simulated roadway.

For the first 5.8 mi or 5 min, the platoon proceeded as formed. At 5.8 mi, a CACC vehicle merged into the platoon from the left in front of the participant driver. The merge was from a ramp identical to the initial ramp. Initially, the gap between the participant and the merging vehicle was about 0.5 s or 51 ft. At the 34.8 mi point, one of the following critical events occurred:

Calibration of CACC Vehicle Size

In previous testing in the simulator and in pilot testing for this experiment, most individuals showed a reluctance to follow other vehicles with a 1.1-s gap and indicated that they never followed that closely. The literature suggested that a 1.1-s gap was greater than most people considered safe.(13) To examine this phenomenon, trials were conducted in which six drivers from the FHWA research center (Federal employees and contractors) drove an instrumented vehicle in the field while following a full-sized sport-utility vehicle and followed the same simulated vehicle in the driving simulator. The field data collection was conducted on limited‑access managed lanes with minimal traffic. The simulated roadway was the CACC-managed lane used in this experiment. Each of the drivers was asked to follow both the real and simulated vehicles according to the following instructions:

In the field, the participants drove an instrumented luxury sport-utility vehicle that was equipped with ACC. In the simulator, the eye point of the simulator cab was positioned to approximate the eye height as the lead vehicle. The procedures in the field and in the simulator were the same. Participants first drove for 5 to 7 min to accustom themselves to the vehicle/simulator. They then caught up to the lead vehicle, which was traveling with cruise control set to 65 mi/h, and were instructed to follow at a comfortable distance. After following constantly for about 1 min at what the participants said they felt was a comfortable distance, participants were asked to back off a substantial distance (greater than 4 s). Next, the participants were asked to accelerate and follow while maintaining the minimum safe distance (the shortest gap they believed to be safe). This procedure of catching up to follow at comfortable and minimum safe distances was repeated at least twice. After backing off to more than 4 s again, participants were asked to engage the ACC/CACC system that was set to follow with the near setting. The near setting sought a 1.1-s gap. Once they had followed at the near distance for at least 1 min, the system was again disengaged, and the participants backed off to a distance of more than 4 s. The final request was to accelerate to and maintain the same following distance they had driven with the ACC/CACC system engaged. On all trials, steady state following was recorded for approximately 1 min.

With the simulated lead vehicle set to have a visual angle subtended precisely the same as it would be in the real world, participants maintained a following distance about 1.3 times the distance they had maintained in the field. This suggested that the lead vehicle’s size needed to be reduced to induce the same perceived following distance the participants maintained in the field. As a first approximation, the lead vehicle size was reduced to 75 percent of the correct size based on 1:1 visual angle correspondence. Several weeks later, five of the original six participants returned to the simulation laboratory and followed the original procedure but following a reduced size lead vehicle. Participants were not informed about the changes that had been made to the lead vehicle. In the second simulation drive, the participants nearly duplicated the comfortable and minimum safe distances they had driven in the field. The results of this testing are shown in figure 2.

This line graph shows the results of field and simulator gap maintenance testing. The x-axis is labeled “Gap Instruction” with two categories: comfortable and minimum safe. The y-axis is labeled “Mean Time Gap” and ranges from 0.0 to 2.0 s. Three lines are plotted on the graph: field, sim 1:1, and sim 0.75:1. The data points are as follows for each line for comfortable and minimum safe, respectively: field—1.4 and 0.7 s; sim 1:1—1.9 and 0.9 s; and sim 0.75:1—1.4 and 0.8 s.

Sim = Simulation.

Figure 2. Graph. Results of field and simulator gap maintenance testing.

As a result of this testing, it was decided to reduce the size of the other vehicles in the CACC string to 75 percent of the size of a 1:1 depiction. This same size reduction was used in all four experiments reported in this summary.

Procedure

A slideshow presentation with embedded videos was shown to explain the CACC concept. Participants assigned to one of the CACC conditions were presented with the warning tone that was triggered when more braking was needed than the CACC system could provide. The CACC-related instructions were as follows:

Except for these CACC-related instructions, the control group instructions were the same except the control group was instructed as follows:

A practice drive, NASA-TLX practice, eye-tracker calibration, and attachment of the GSR sensor preceded the experimental drive.

The experimental session began with the participant seated in the third vehicle of a string of four vehicles. The string was stopped on a ramp in front of a ramp meter showing a red indication. When the ramp meter turned green, the vehicles ahead began to accelerate down the ramp toward the CACC travel lane. Participants in the CACC conditions were asked to engage the CACC system. With CACC engaged, the participant’s vehicle followed the two preceding vehicles with a 1.1-s gap. Participants in the control condition were asked to follow the preceding vehicles and try to keep the gap close to the 1.1-s target.

About 5 min into the drive, a CACC vehicle came down a ramp on the left and merged into the gap directly in front of the participant’s vehicle, which momentarily cut the gap to half of what it had been. The CACC-equipped vehicles behind the merged vehicle responded by decelerating with engine braking until the gap was again 1.1 s. If necessary, a researcher would remind control participants to return to the 1.1-s following distance. As soon as the platoon stability was reestablished, which generally took about 30 s, the NASA-TLX was administered to assess workload during the merge event (i.e., during the preceding minute or so).

After the conclusion of the NASA-TLX, about 10 min elapsed before another NASA-TLX was administered. This administration was intended to assess workload during uneventful cruising in a CACC platoon (also described as during the last minute or so). The cruise was again uneventful for the next 31 min until the critical event (described previously in the section entitled The Simulation Scenarios). At the conclusion of the critical event, a final NASA-TLX was administered, after which the participant was asked to take the next exit ramp and come to a stop.

After exiting the simulator, participants were asked to complete a final simulator sickness questionnaire, debriefed, and paid for their participation.

Experimental Design

The primary between-group independent variable was whether the participant vehicle was equipped with CACC. The experimental design called for 36 participants to drive with CACC and 12 to drive without cruise control but within a string of simulated CACC vehicles. Participants driving with CACC were assigned to one of three critical events, with 12 participants assigned to each event.

Thus, there were the following four distinct participant groups:

Participants

The participants were 49 licensed drivers recruited from the Washington, DC, metropolitan area. Table 1 shows the age group and gender counts by treatment group for the participants who provided useable data. The mean age of the younger participants was 30.4 years (ranging from 21 to 38). The mean age of the older participants was 60.4 years (ranging from 49 to 76).

Table 1. Demographic breakdown of participants in experiment 1 by treatment group.

Condition

Young Females

Young Males

Older Females

Older Males

Total

Control

3

3

3

3

12

CACC with crash avoidance

3

4

3

3

13

CACC with cut-in

3

3

3

3

12

CACC with communications failure

2

3

3

4

12

Total

11

13

12

13

49

Participants were paid $60 for their participation.

Results

The following subsections describe the results of the experiment for workload, physiological arousal, distraction, gaze location, crash avoidance, minimum time to collision (TTC), reaction time, and trust in the CACC system.

Workload

The mean NASA-TLX scores by condition and period are shown in figure 3. The control group consistently rated workload higher than the CACC groups (F (1, 3) = 14.5, p < 0.001). There was also a significant location-by-condition interaction (F (6, 90) = 27.4, p < 0.001), which was the result of the CACC with crash group rating their workload higher than the other CACC groups after the critical crash event.

This line graph show the overall National Aeronautics and Space Administration Task Load Index (NASA-TLX) score as a function of treatment group and location. Overall NASA-TLX score is on the y-axis from 0 to 100. Location is on the x-axis with three location categories: after merge, mid-cruise, and after final event. There are four lines, one for each participant group: control, cooperative adaptive cruise control (CACC) with crash, CACC with merge, and CACC with system failure. Mean NASA-TLX scores for the control group are 53, 28, and 61 for after merge, mid cruise, and after final event locations, respectively. Mean NASA-TLX scores for the CACC with crash group are 16, 9, and 42 for after merge, mid cruise, and after final event locations, respectively. Mean NASA-TLX scores for the CACC with merge group are 12, 7, and 16 for after merge, mid cruise, and after final event locations, respectively. Mean NASA-TLX scores for the CACC with system fail group are 17, 14, and 24 for after merge, mid cruise, and after final event locations, respectively. Error bars for the 95-percent confidence limits are only shown for the control group. These errors range between 

Note: Error bars represent estimated 95-percent confidence limits of the means.

Figure 3. Graph. NASA-TLX scores as a function of treatment group and location in the scenario.

Physiological Arousal

The physiological measures of arousal were GSR, eyelid opening, and pupil diameter.

GSR

No statistically significant differences in physiological arousal, as measured by standardized GSR, were detected between the control group and the three CACC groups.

Eyelid Opening

The eyelid opening data were quite noisy, and more than half of the data were rejected because the eye-tracking software indicated low confidence in the reported readings. No reliable differences in eyelid opening were identified either between groups or as a function of the time the readings that were taken during the drive.

Pupil Diameter

Pupil diameter measurements for which the eye-tracking software reported less than 75 percent confidence were excluded from analyses. These exclusions resulted in retention of 73.7 percent of the observations. As with GSR and eyelid opening, each participant’s pupil diameter observation across the five 15-s periods was converted to a z-score. The first period was immediately after the first merge event. The second period was after 15 min of uneventful driving. The third period was just before the critical event, and the fourth period was just after the critical event. The z-scores were then submitted to a generalized estimating equation (GEE) model with condition, period, and their interaction as factors. Figure 4 shows the estimated standardized means as a function of condition and period, where the three CACC groups have been collapsed into one CACC condition. The condition-by-period interaction was significant, (χ2 + (12) = 36.12, p < 0.01), as was the main effect of period, (χ2(4) = 74.04, p < 0.01). The source of the main effect was obvious—pupil diameters for all conditions were greater during the first two periods (after 5 min of driving) than in the last three periods (after 15 or more minutes of driving). The interaction does not result from any easily explainable phenomenon; the control group had atypically large pupil diameters in period 2, perhaps related to the larger amount of time spent glancing at the gap display (see Gaze Location results presented later in this section). The CACC with communications failure group had larger pupil diameters than the other groups in period 4. Because all three CACC groups were exposed to the same stimulus conditions until period 5, there was no obvious explanation for the pattern that resulted in the significant interaction.

This graph shows the mean standardized pupil diameters of the control group and the combined mean of the cooperative adaptive cruise control (CACC) groups for each of the first four measurement periods. The y-axis is labeled “Estimated Mean Pupil Diameter (z-score)” and ranges from −1.40 to 1.40. The x-axis is labeled “Period” with values ranging from 1 to 4. The means and confidence limits are as follows: period 1 control group mean = 0.22, −0.01 to 0.45, period 1 CACC group mean = 0.40, .0.27 to 0.54; period 2 control group mean = 0.84, 0.44 to 1.23, period 2 CACC group mean 0.21, 0.07 to 0.35; period 3 control group mean = −0.34, −0.64 to −0.04, period 3 CACC group mean = −0.46, −0.60 to −0.32; period 4 control group mean = −0.35, −0.53 to −0.18, and period 4 CACC group mean = −0.13, −0.32 to −0.06.

Note: Error bars represent estimated 95-percent confidence limits of the means.

Figure 4. Graph. Standardized pupil diameter as a function of condition and period.

Overall, the physiological measures provided no evidence that CACC resulted in a greater reduction in arousal over time than the control condition.

Distraction

The physiological data, which were quite noisy, showed no clear indication of reduced levels of arousal that might lead to inattention errors. However, people can mitigate the tendency toward reduced arousal on long drives by engaging in arousal-stimulating secondary activities. In this experiment, participants were not discouraged from engaging in these activities. While care was also taken to avoid encouraging these activities, participants were told that they could listen to the car radio or do what they normally did while driving. Because all of the CACC participants were treated the same prior to the critical event, the three CACC groups were collapsed into one group, and their probability of engaging in observable diversions before the critical event was compared with the control group. The estimated mean probability of control group members engaging in diversions (0.36) was less than the estimated mean probability of CACC group members engaging in diversions (0.52). This difference was statistically significant (p < 0.05).

Gaze Location

The control group spent considerably more time gazing in the direction of the multifunction display than did the CACC groups. Gaze time in the direction of the multifunction display came at the expense of monitoring the road ahead. It should be noted that the road ahead classification included any recorded gaze direction other than at the defined objects (e.g., multi-purpose display or rear-view mirror) and within the 200- by 40-degree area of the projection screen.

Because the only difference in treatment of the CACC groups occurred in observation period 5, the data for the three CACC groups were collapsed into a single CACC group for periods 1 through 4. A GEE model with negative binomial response distribution and log link function was used to analyze the gaze distribution among objects in periods 1 through 4 and CACC group versus control group. This model revealed a significant main effect of period (χ2(3) = 19.5, p < 0.01) and condition (χ2(1) = 24.6, p < 0.01). These effects are shown in figure 5. For the CACC participants, gaze time in the direction of the display in periods 2 and 4 may have resulted from the need of some participants to reengage the CACC system. The large percentage of time that the control group spent gazing in the direction of the multi-purpose display in period 2 was likely the result of the changes in gap caused by the cut-in vehicle in that period.

This graph shows the mean standardized pupil diameters of the control group and the combined mean of the cooperative adaptive cruise control (CACC) groups for each of the first four measurement periods. The y-axis is labeled “Estimated Mean Pupil Diameter (z-score)” and ranges from −1.40 to 1.40. The x-axis is labeled “Period” with values ranging from 1 to 4. The means and confidence limits are as follows: period 1 control group mean = 0.22, −0.01 to 0.45, period 1 CACC group mean = 0.40, .0.27 to 0.54; period 2 control group mean = 0.84, 0.44 to 1.23, period 2 CACC group mean 0.21, 0.07 to 0.35; period 3 control group mean = −0.34, −0.64 to −0.04, period 3 CACC group mean = −0.46, −0.60 to −0.32; period 4 control group mean = −0.35, −0.53 to −0.18, and period 4 CACC group mean = −0.13, −0.32 to −0.06.

Note: Error bars represent estimated 95-percent confidence limits of the means.

Figure 5. Graph. GEE estimated mean percentage of time gazing at the multifunction display as a function of condition and period.

Crash Avoidance

None of the participants in the CACC group with cut-in or CACC group with system failure collided with another vehicle. This was not the case for participants in the crash avoidance condition in which the lead vehicle of the platoon decelerated to a stop from 70 mi/h at a rate of 32.2 ft/s2. As shown in table 2, five control group members crashed into the vehicle ahead, but only one member of the CACC with crash avoidance group crashed. The difference in crash rates was significant by Fisher’s Exact Test (p < 0.02).

Table 2. Crash counts for the two groups that were exposed to the crash avoidance event.

Group

Crashed

Avoided

Total

Control

5

6

11

CACC with crash avoidance

1

12

13

Crashes have often been considered the ultimate measure of highway safety. However, crashes are a rather crude safety measure because they are rare outside driving simulations and are generally reported in terms of number of crashes per million miles driven. TTC has been used as a surrogate for crashes because the frequency of near misses (i.e., very short TTCs) has been thought to be highly correlated with crash frequency but easier to observe.(14) To further evaluate the probability of a crash in scenarios like those in the simulation, TTC was analyzed.

Minimum TTC

To enable analysis of TTC even when collisions occurred, Brown’s adjusted minimum TTC was used.(15) The adjusted minimum TTC takes into account velocity at the time of collision. The adjusted minimum TTC thus reflects the severity of the crash or near-crash event regardless of whether collision avoidance was successful. If a collision does not occur, the minimum TTC is the same as the traditional TTC measure and represents the amount of additional time the driver had to respond. If a collision does occur, then minimum TTC is negative and represents the difference between the time available and the time the driver needed to avoid the collision.(15) One CACC with crash avoidance participant showed no reaction to the rapid deceleration of the lead vehicle. When the following vehicle fails to decelerate, the adjusted TTC goes to negative infinity, and minimum TTC becomes meaningless, at least in terms of computing mean TTC. Therefore, this participant was excluded from the adjusted minimum TTC analysis.

The overall test showed that the mean minimum TTCs between groups were significantly different (Wald χ2 (3) = 9.2, p <0.03). As can be seen in figure 6, the control group TTC was significantly less than that of the three groups that used CACC.

This point graph shows the estimated means of adjusted time to collision (TTC) for the four treatment groups. The y-axis is labeled “Adjusted Minimum TTC” and ranges from −2.0 to 4.0 s. The x-axis is labeled with the names of the four experimental groups: control, cooperative adaptive cruise control (CACC) with crash, CACC with cut-in, and CACC with communications failure. The means and confidence limits are as follows for each of the four groups, respectively: control mean = −0.6 and confidence limits = −1.6 to 0.5, CACC with crash mean = 1.6 and confidence limits = 0.3 to 3.1, CACC with cut-in mean = 2.0 and confidence limits = 0.7 to 3.6, and CACC with communications failure mean = 1.2 and confidence limits = 0.0 to 2.6.

Note: Error bars represent estimated 95-percent confidence limits of the means.

Figure 6. Graph. Estimated adjusted mean TTC.

Reaction Time

Brake reaction time was defined as the time between when the car immediately ahead of the participant began braking and the time the participant first began to depress the brake pedal. One control and two CACC crash avoidance participants were excluded from this analysis because they swerved out of the travel lane before braking or never braked.

There was no significant difference in brake reaction time between the control group and the CACC crash avoidance group. The brake reaction times for these two groups are shown in figure 7. This finding suggests that the better crash avoidance and larger minimum TTCs for the CACC group were the result of the CACC system automatically braking at 0.4 g. Alternatively, the larger CACC TTCs could have resulted if the CACC group had responded with more vigorous braking than the control group (i.e., if the CACC group went from zero to full brake pedal depression faster than the control group). This alternative explanation was rejected because the control group tended, but not significantly so, to brake more vigorously (i.e., reached full brake depression sooner) than the CACC group. Figure 8 shows the time taken to move the brake pedal position from off to full braking. The difference between groups was not significant.

This point graph shows the estimated mean brake reaction times for the control and cooperative adaptive cruise control (CACC) with crash groups. The y axis is labeled “Brake Onset Reaction Time” and ranges from 0 to 4.0 s. The x-axis is labeled with the names of the two groups that were exposed to the crash event: control and CACC with crash. The estimated means and confidence limits are as follows: control mean = 2.6 and confidence limits = 3.4 to 3.5, and CACC with crash mean = 2.8 and confidence limits =

Note: Error bars represent estimated 95-percent confidence limits of the means.

Figure 7. Graph. Estimated mean brake onset reaction times for the two groups that had the crash avoidance final event.

This point graph shows the estimated means for the lag between the onset of braking and when full brake pedal depression occurred. The y-axis is labeled “Full Brake Depression Lag” and ranges from 0 to 1.6 s. The x-axis is labeled with the names of the two groups that were exposed to the crash event: control and cooperative adaptive cruise control (CACC) with crash. The estimated means and confidence limits are as follows: control mean = 0.75 and confidence limits = 0.6 to 1.0, and CACC with crash mean = 1.1 and confidence limits = 0.9 to 1.5.

Note: Error bars represent estimated 95-percent confidence limits of the means.

Figure 8. Graph. Estimated mean time from beginning of brake pedal depression to full braking.

Trust in the CACC System

About 6.8 min into the drive (the moment that ended period 1 and began period 2), a simulated CACC vehicle merged into the gap between the participant’s vehicle and the car ahead, approximately halving the participant’s following gap distance. All participants were exposed to this merge event. One measure of trust in the system was whether the participants in the CACC conditions trusted the system to maintain speed/gap control or intervened by braking to increase the gap or by pressing the accelerator to return to a 1.1-s gap. Only 1 of 36 CACC participants braked during the merge event, and 1 participant pressed the accelerator pedal. By comparison, all of the control condition participants used the brake pedal during the merge event.

Discussion

The first experiment addressed the following questions regarding CACC:

Does CACC Reduce Driver Workload?

As assessed by the NASA-TLX, the CACC system did reduce perceived driver workload in this experiment.

Does CACC Increase the Probability of Driver Distraction?

The CACC group was more likely to listen to the radio or engage in other observable diversionary activities than the control group. It remains to be determined whether this tendency was the result of the CACC system relieving the drivers from the responsibility to continually manage gap or because the control group had the added diversion of monitoring the gap indication of the multi-purpose display. As a result of this finding, an additional experiment was proposed in which the control group was equipped with ACC rather than CACC so that a gap display would not be required.

Does CACC Reduce Driver Arousal?

The attempts to assess the effect of CACC on physiological arousal were largely unsuccessful. The GSR measurements were noisy and inconclusive. The eyelid opening data were also inconclusive, and the eyelid opening quality readings output by the eye-tracking software suggest that researchers should not rely on these readings. The pupil diameter readings were fairly reliable, assuming the eye-tracking software quality ratings are to be believed. The finding that pupil diameter decreased in the second half of the drive suggests all groups were somewhat less aroused during the second half of the drive. There was no indication that arousal differed between groups, but this could be the result of the aforementioned tendency of participants to engage in diversionary activities to keep their arousal at comfortable levels.

Does CACC Reduce Crash Risk?

The results of the crash avoidance event to which the control group and CACC with crash avoidance group were exposed suggest that CACC provided a substantial safety benefit. Half the control group crashed into the car ahead with substantial force, as indicated by negative TTC scores. By contrast, only one CACC participant crashed, and that participant’s response was questionable because he never attempted to brake and proceeded to drive through three of the vehicles ahead.

Because the control group’s brake reaction time and time to reach maximum braking were not significantly different from the CACC group in the crash avoidance scenario, the most likely explanation of the crash avoidance benefit from the CACC system was the 0.4-g braking that the system engaged in soon after the car ahead began braking. This moderate braking enabled the CACC-equipped drivers to brake slightly later and with slightly less force than control drivers while being much less likely to have a collision.

Will Drivers Trust CACC?

The CACC-equipped drivers showed considerable trust in the system. Only 1 of 36 CACC drivers braked when a CACC vehicle merged into the platoon, and only 1 of 36 CACC drivers used the accelerator to close the gap at the end of the merge event when the system slightly overshot the 1.1-s target while slowing to reestablish the set gap. Furthermore, none of the CACC drivers in the CACC with cut-in group braked during the period 5 cut-in event. Although CACC-equipped drivers showed considerable trust in the system, there was no evidence of over trust in the system; all but one CACC driver responded appropriately to the crash avoidance critical event.

 

 

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