Study I: Task-difficulty homeostasis in car following

Study I (Pekkanen et al., 2017) examined experimentally how drivers allocate their attention and adapt their speed during visual distraction when following another car. The experiment’s 18 participants drove in a driving simulator both an unoccluded task, i.e. just followed the car ahead of them, and an occluded task where visual distraction was introduced using aself-paced visual occlusion setting:

the view to the road ahead was occluded, but the participants could remove the occlusion for a brief, 300 millisecond ”glance” by pressing a paddle in the steering wheel. The drivers were instructed to take as few of these glances as possible while still not crashing and avoiding erratic driving (see figure 6).

The occlusion used in this study differs from previous occluded driving studies (Godthelp et al., 1984; Kujala et al., 2015; Senders et al., 1967) in that only view to the part of the scene where the leading vehicle can be seen was blocked (see figure 6), whereas traditionally the whole field of view is occluded. The partial occlusion was decided upon as it allows the participants to estimate their own speed from the peripheral optic flow also during occlusion, which is especially im-portant in a driving simulator where vestibular and somatosensory information about changes in speed are not available. This makes the occluder behavior eas-ier to interpret as the missing visual information is more specific to the leading vehicle’s state and changes in the occlusion durations can be attributed mostly to uncertainty about the distance and speed relative to the leading vehicle, and less to uncertainty in the participant’s own speed.

The participants were encouraged to drive close to leading car but without excessive accelerations by instructing them to minimize fuel consumption, which

Figure 6: Screenshots of unoccluded car following (left) and occluded car following (right). In the occluded car following scenario the driver could request a visual sample

of 300 ms by pressing a paddle in the steering wheel controller.

could be reduced by ”draft saving” that decreased with distance (see Procedure in Pekkanen et al. (2017) for details). Such instruction was given in an effort to make the participants drive at the limit of their capabilities. This is important for the theoretical interpretation of the results: if the drivers change the amount of total effort from the unoccluded to the occluded task, the changes in driving brought by the occlusion can not be solely attributed to decreased amount of visual information, but are confounded with the change in total effort that is difficult to measure.

The driving behavior was indexed using time headway (THW) which is the time that it would take for the driver reach the current location of the leading vehicle. Attention allocation was measured using occlusion duration (OD), which is the time between successive glances, i.e. the duration that the driver drives without seeing the car ahead.

A strong correspondence was found between participants’ average occlusion duration and increase in time headway compared to the unoccluded task (R² = 0.84, see figure 7)⁵, and the relationship was found to be about one-to-one, meaning that for every second of average occlusion duration the average time headway was increased by one second.

Although to my knowledge such exact relationship has not been previously reported, a more general relationship betweentask-demand andtask-capabilityhas been proposed to emerge from thetask-difficulty homeostasisprocess (Fuller, 2005).

The task-difficulty homeostasis has been formalized for car following models by Hoogendoorn et al. (2013) and Saifuzzaman et al. (2015) which both directly relate task-demand to time headway and propose that drivers increase their preferred time headway to compensate for the driving capability drop that is caused by

5The figures here show the participant median, while the original article reports per-participant geometric means. Median was chosen for this text to be directly comparable with Study II. The results are essentially the same with both measures.

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distraction. This should result in a kind of relationship between THW and OD observed here.

While both of the models associate time headway with task-demand, neither provides details on how to quantify task-capability or how this relates to distrac-tion. However, their mathematical formulations can be interpreted to imply how a drop in driving capability should be reflected in the time headway. The im-plied relationships have subtly different forms, which means that the models can be empirically compared with our experimental data. The Hoogendoorn et al.

(2013) model implies a ”baseline dependent” relationship where drivers increase their THWs relative to their non-distracted THWs, meaning that a driver who without distraction drives with a longer THW increases their headway more than a driver with shorter non-distracted THW in reponse to the same level of distrac-tion. In contrast, the model of Saifuzzaman et al. (2015) assumes a ”baseline independent” relationship in which same distraction leads to the same increase of THW regardless of a driver’s non-distracted baseline THW.

Although both formulations lead to a statistically significant explanation of the increase in drivers’ average THWs (Spearman correlation 0.84 (95% CI [0.62, 0.94]) for the baseline independent and 0.57 (95% CI [0.14, 0.82]) for the base-line dependent relationship) the basebase-line independent relationship is statistically significantly in better agreement with our data (95% CI (0.026, 0.66) for differ-ence in the Spearman correlations). Also the strong linear corresponddiffer-ence found with the baseline-independent formulation (figure 7) can be applied to quantita-tively model the drivers’ THW increase when the distraction level can be stated as average occlusion durations.

In addition to the correspondence in the per-participant averages of OD and THW increase, robust covariation was found between instantaneous THWs and ODs, i.e. THW at a ”glance” moment correlates with how long the following occlusion lasts⁶. For 58 of the 61 total occluded trials a positive Spearman cor-relation between the instantaneous OD and THW (Binomial test p= 3×10⁻¹⁴), with median correlation of 0.56 was found.

We interpret this instantaneous THW-OD connection to arise from drivers re-sponding to the more attentionally demanding shorter THW situation by increas-ing their capability by allocatincreas-ing more visual attention to task. Such mechanism is not included in current car following models, but is in line with the more general task-difficulty homeostasis idea, in which the balance between capability and

de-6The correlations are calculated for linearly detrended values to reduce potential spurious cor-relations due to possible fluctuations in the preferred THW. For details see sectionInstantaneous Time Headway and Occlusion Duration in Pekkanen et al. (2017).

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