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- Bianchi Piccinini, Giulio, 1982, et al.
(författare)
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How Do Drivers Respond to Silent Automation Failures? Driving Simulator Study and Comparison of Computational Driver Braking Models
- 2020
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Ingår i: Human Factors. - Chalmers University of Technology, Gothenburg, Sweden.; Volvo Group Trucks Technology, Gothenburg, Sweden.; Virginia Tech Transportation Institute, Blacksburg, USA.; University of Leeds, UK.; VTI, Gothenburg, Sweden. : SAGE Publications. - 1547-8181 .- 0018-7208. ; 62:7, s. 1212-1229
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Tidskriftsartikel (refereegranskat)abstract
- Objective: This paper aims to describe and test novel computational driver models, predicting drivers’ brake reaction times (BRTs) to different levels of lead vehicle braking, during driving with cruise control (CC) and during silent failures of adaptive cruise control (ACC). Background: Validated computational models predicting BRTs to silent failures of automation are lacking but are important for assessing the safety benefits of automated driving. Method: Two alternative models of driver response to silent ACC failures are proposed: a looming prediction model, assuming that drivers embody a generative model of ACC, and a lower gain model, assuming that drivers’ arousal decreases due to monitoring of the automated system. Predictions of BRTs issued by the models were tested using a driving simulator study. Results: The driving simulator study confirmed the predictions of the models: (a) BRTs were significantly shorter with an increase in kinematic criticality, both during driving with CC and during driving with ACC; (b) BRTs were significantly delayed when driving with ACC compared with driving with CC. However, the predicted BRTs were longer than the ones observed, entailing a fitting of the models to the data from the study. Conclusion: Both the looming prediction model and the lower gain model predict well the BRTs for the ACC driving condition. However, the looming prediction model has the advantage of being able to predict average BRTs using the exact same parameters as the model fitted to the CC driving data. Application: Knowledge resulting from this research can be helpful for assessing the safety benefits of automated driving.
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| 2. |
- Itkonen, Teemu, 1985, et al.
(författare)
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Characterisation of Motorway Driving Style Using Naturalistic Driving Data
- 2020
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Ingår i: Transportation Research Part F: Traffic Psychology and Behaviour. - : Elsevier BV. - 1369-8478. ; 69, s. 72-79
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Tidskriftsartikel (refereegranskat)abstract
- The study of measurable differences between drivers has ramifications for several subfields in traffic and transportation research. Better understanding of the variability in individual driving styles would be especially useful for understanding driver preferences, psychological mechanisms for vehicle control and for developing more realistic traffic simulations. In our study based on a large naturalistic data set, we investigated the driving style of 76 individuals driving in a motorway setting. We discovered that the majority of between-driver variation in keeping longitudinal and lateral safety margins, lane changing frequency, acceleration and speed preference, can be reduced to two dimensions, which we interpret as habitualised motives centred around mental effort and expediency.
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| 3. |
- Lehtonen, Esko, 1981, et al.
(författare)
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Gaze doesn't always lead steering
- 2018
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 121, s. 268-278
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Tidskriftsartikel (refereegranskat)abstract
- In car driving, gaze typically leads the steering when negotiating curves. The aim of the current study was to investigate whether drivers also use this gaze-leads-steering strategy when time-sharing between driving and a visual secondary task. Fourteen participants drove an instrumented car along a motorway while performing a secondary task: looking at a specified visual target as long and as much as they felt it was safe to do so. They made six trips, and in each trip the target was at a different location relative to the road ahead. They were free to glance back at the road at any time. Gaze behaviour was measured with an eye tracker, and steering corrections were recorded from the vehicle's CAN bus. Both in-car ‘Fixation’ targets and outside ‘Pursuit’ targets were used. Drivers often used a gaze-leads-steering strategy, glancing at the road ahead 200–600 ms before executing steering corrections. However, when the targets were less eccentric (requiring a smaller change in glance direction relative to the road ahead), the reverse strategy, in which glances to the road ahead followed steering corrections with 0–400 ms latency, was clearly present. The observed use of strategies can be interpreted in terms of predictive processing: The gaze-leads-steering strategy is driven by the need to update the visual information and is therefore modulated by the quality/quantity of peripheral information. Implications for steering models are discussed.
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| 4. |
- Melin, M. C., et al.
(författare)
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Where do people direct their attention while cycling? A comparison of adults and children
- 2018
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Ingår i: Transportation Research Part F: Traffic Psychology and Behaviour. - : Elsevier BV. - 1369-8478. ; 58, s. 292-301
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Tidskriftsartikel (refereegranskat)abstract
- Cycling in urban environments requires the ability to distinguish between relevant and irrelevant targets quickly and reliably, so that potential hazards can be anticipated and avoided. In two experiments, we investigated where adults and children direct their attention when viewing videos filmed from a cyclist's perspective. We wanted to see if there were any differences in the responses given by experienced adult cyclists, inexperienced adult cyclists, and child cyclists. In Experiment 1, 16 adults (19–33 years) were asked to watch ten videos and to point out things they would pay attention to by tapping a touchscreen (pointed out locations). Afterwards, they were asked to explain their answers. In Experiment 2, 17 adults (19–34 years) and 17 children (11–12 years) performed the same task with the same ten videos, but they were not asked to explain their answers afterwards. The data sets from these two experiments were pooled, creating three groups: ten experienced adult cyclists, 23 inexperienced adult cyclists and 17 children. A total of 23 clearly visible, traffic-relevant targets (pre-specified targets) had previously been identified in the videos. We investigated whether the participants’ pointed-out locations matched these targets (and if so, how fast they responded in pointing them out). We also investigated the number and vertical/horizontal dispersion of these pointed-out locations on the touchscreen. Adults pointed out more locations than children, especially pedestrians and cyclists. This result suggests that, while children focussed as well as adults on cars (arguably the most salient hazard), they were less able to identify other hazards (such as pedestrians or other cyclists). The children had also a larger vertical dispersion and a larger between-participant variation than the adults. Adults were faster at tapping the pre-specified targets and they missed them less often. Overall, the results suggest that 11–12 year old-cyclists have worse situation awareness in traffic than adults.
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| 5. |
- Tuske, Vaida, et al.
(författare)
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Hazard perception test development for Lithuanian drivers
- 2019
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Ingår i: IATSS Research. - : Elsevier BV. - 0386-1112. ; 43:2, s. 108-113
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Tidskriftsartikel (refereegranskat)abstract
- Hazard perception tests may not be transferable between different countries, due to differences in traffic culture and infrastructure. Therefore, different instruments might be necessary for assessing hazard perception in various countries. The aim of the current study was to develop the Lithuanian hazard perception test based on static traffic images and test its psychometric properties. Thirty-four experienced drivers participated in a pilot study, and 125 drivers with diverse driving experience took part in the main study. The final test contained 27 static traffic scenes and the participants were asked to respond if they saw a hazard or not. Results demonstrated that the test has satisfactory internal consistency and test-retest reliability. It differentiated between inexperienced and experienced drivers, and between those experienced drivers who had less than three or more than three crashes in their driving history. The test has sufficient psychometric properties for research; still further development is needed in order to apply it for individual testing and decisions about licence provision. (C) 2018 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd.
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| 6. |
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| 7. |
- Åkerberg Boda, Christian-Nils, 1989, et al.
(författare)
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A computational driver model to predict driver control at unsignalised intersections
- 2020
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Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8, s. 104619-104631
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Tidskriftsartikel (refereegranskat)abstract
- The interaction between a cyclist and a driver at unsignalized intersection remains a risky situation which may result in a collision with severe consequences, especially for the cyclist. Crash data show that the number of cyclist fatalities at unsignalized intersections has been stable the last years, indicating that more efforts should be given to improve safety in this specific scenario. Safety systems can help drivers avoid collisions with cyclists. However, systems addressing this conflict scenario are difficult to design, not only because of the technical aspects (e.g., sensor, or control limitations) but because those systems need to predict how drivers will or would control their car to be effective. A handful of studies focused on describing driver behaviour in this traffic scenario, but no computational model that can predict driver control can be found in the literature. The present study presents a driver model based on a biofidelic human sensorimotor control modelling framework predicting driver control in this traffic scenario. Two visual cues were implemented: 1) optical longitudinal looming, and 2) projected post-encroachment time between the bike and the car. The model was optimized using test-track data in which participants were asked to drive through an intersection where a cyclist would cross their travel path. The performances of the model were evaluated by comparing the simulated driver control process with the observed controls for each trial using a leave-one-out crossvalidation process. The results showed that the model performed rather well by reproducing similar braking controls, and kinematics, compared to the observations. The extent to which the model could be used by safety systems’ threat-assessment algorithms was discussed. Future research to improve the model performances was suggested.
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