| 1. |
- Dozza, Marco, 1978, et al.
(författare)
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How do drivers negotiate intersections with pedestrians? Fractional factorial design in an open-source driving simulator
- 2017
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Ingår i: Proceeding of the Road Safety and Simulation International Conference, RSS2017, 17-19 October 2017.
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Konferensbidrag (refereegranskat)abstract
- Forward collision warning (FCW) and autonomous emergency braking (AEB) systems are increasingly available and promise to prevent or mitigate collisions by alerting the driver or autonomously braking the vehicle. Threat-assessment and decision-making algorithms for FCW and AEB aim to find the best compromise for safety by intervening at the “right” time: neither too early, potentially upsetting the driver, nor too late, possibly missing opportunities to avoid the collision.Today, the extent to which intervention times for FCW and AEB should depend on factors such as pedestrian speed and lane width is unknown. To guide the design of FCW and AEB intervention time, we employed a fractional factorial design, and determined how seven factors (crossing side, car speed, pedestrian speed, crossing angle, pedestrian size, zebra presence, and lane width) affect the driver’s response process and comfort zone when negotiating an intersection with a pedestrian. Ninety-four volunteers drove through an intersection in a fixed-base driving simulator, which was based on open-source software (OpenDS). Several parameters, including pedestrian time-to-arrival and driver response time, were calculated to describe the driver response process and define driver comfort boundaries.Linear mixed-effect models showed that driver responses depended mainly on pedestrian time-to-arrival and visibility, whereas factors such as pedestrian size, zebra presence, and lane width did not significantly influence the driver response process. Some drivers changed their negotiation strategy to minimize driving effort over the course of the experiment. Experienced drivers changed more than less experienced drivers; nevertheless, all drivers behaved similarly, independent of driving experience. The flexible and customizable driving environment provided by OpenDS proved to be a viable solution for behavioural experiments in driving simulators.Results from this study suggest that visibility and pedestrian time-to-arrival are the most important factors for defining the earliest acceptable FCW and AEB activations. Fractional factorial design effectively compared the influence of several factors on driver behaviour within a single experiment; however, this design did not allow in-depth data analysis. In the future, OpenDS may became a standard platform, enabling crowdsourcing and favouring repeatability across studies in traffic safety. Finally, this study may guide future design and evaluation of FCW and AEB by highlighting which factors deserve further investigation and which ones do not.
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| 2. |
- Dozza, Marco, 1978, et al.
(författare)
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How do drivers negotiate intersections with pedestrians? The importance of pedestrian time-to-arrival and visibility
- 2020
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 141:June 2020
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Tidskriftsartikel (refereegranskat)abstract
- Forward collision warning (FCW) and autonomous emergency braking (AEB) systems are increasingly available and prevent or mitigate collisions by alerting the driver or autonomously braking the vehicle. Threat-assessment and decision-making algorithms for FCW and AEB aim to find the best compromise for safety by intervening at the “right” time: neither too early, potentially upsetting the driver, nor too late, possibly missing opportunities to avoid the collision. Today, the extent to which activation times for FCW and AEB should depend on factors such as pedestrian speed and lane width is unknown. To guide the design of FCW and AEB intervention time, we employed a fractional factorial design, and determined how seven factors (crossing side, car speed, pedestrian speed, crossing angle, pedestrian size, zebra-crossing presence, and lane width) affect the driver’s response process and comfort zone when negotiating an intersection with a pedestrian. Ninety-four volunteers drove through an intersection in a fixed-base driving simulator, which was based on open-source software (OpenDS). Several parameters, including pedestrian time-to-arrival and driver response time, were calculated to describe the driver response process and define driver comfort boundaries. Linear mixed-effect models showed that driver responses depended mainly on pedestrian time-to-arrival and visibility, whereas factors such as pedestrian size, zebra-crossing presence, and lane width did not significantly influence the driver response process. Some drivers changed their negotiation strategy (proportion of pedal braking to engine braking) to minimize driving effort over the course of the experiment. Experienced drivers changed more than less experienced drivers; nevertheless, all drivers behaved similarly, independent of driving experience. The flexible and customizable driving environment provided by OpenDS may be a viable platform for behavioural experiments in driving simulators. Results from this study suggest that visibility and pedestrian time-to-arrival are the most important variables for defining the earliest acceptable FCW and AEB activations. Fractional factorial design effectively compared the influence of several factors on driver behaviour within a single experiment; however, this design did not allow in-depth data analysis. In the future, OpenDS might become a standard platform, enabling crowdsourcing and favouring repeatability across studies in traffic safety. Finally, this study advises future design and evaluation procedures (e.g. new car assessment programs) for FCW and AEB by highlighting which factors deserve further investigation and which ones do not.
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| 3. |
- Åkerberg Boda, Christian-Nils, 1989, et al.
(författare)
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Modelling discomfort: How do drivers feel when cyclists cross their path?
- 2020
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 146
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Even as worldwide interest in bicycling continues to grow, cyclists constitute a large part of road fatalities. A major part of the fatalities occurs when cyclists cross a vehicle path. Active safety systems and automated driving systems may already account for these interactions in their control algorithms. However, the driver behaviour models that these systems use may not be optimal in terms of driver acceptance. If the systems could estimate driver discomfort, their acceptance might be improved. Method: This study investigated the degree of discomfort experienced by drivers when cyclists crossed their travel path. Participants were instructed to drive through an intersection in a fixed-base simulator or on a test track, following the same experimental protocol. The effects of demographic variables (age, gender, driving frequency, and yearly mileage), controlled variables (car speed, bicycle speed, and bicycle-car configuration), and a visual cue (car’s time-to-arrival at the intersection when the bicycle appears; TTAvis) on self-reported discomfort were analysed using cumulative link mixed models (CLMM). Results: Results showed that demographic variables had a significant effect on the discomfort felt by drivers—and could explain the variability observed between drivers. Across both experimental environments, the controlled variables were shown to significantly influence discomfort. TTAvis was shown to have a significant effect on discomfort as well; the closer to zero TTAvis was (i.e., the more critical the situation), the more likely the driver red great discomfort. The prediction accuracies of the CLMM with controlled variables and the CLMM with the visual cue were similar, with an average accuracy between 40 and 50%. Surprise trials in the simulator experiment, in which the bicycle appeared unexpectedly, improved the prediction accuracy of the models, more notably the CLMM including TTAvis. Conclusions: The results suggest that the discomfort was mainly driven by the visual cue rather than the deceleration cues. Thus, it is suggested that an algorithm that estimates driver discomfort be included in active safety systems and autonomous driving systems. The CLMM including TTAvis was presented as a potential candidate to serve this purpose.
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| 4. |
- Åkerberg Boda, Christian-Nils, 1989, et al.
(författare)
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Modelling how drivers respond to a bicyclist crossing their path at an intersection: How do test track and driving simulator compare?
- 2018
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 111, s. 238-250
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Tidskriftsartikel (refereegranskat)abstract
- Bicyclist fatalities are a great concern in the European Union. Most of them are due to crashes between motorized vehicles and bicyclists at unsignalised intersections. Different countermeasures are currently being developed and implemented in order to save lives. One type of countermeasure, active safety systems, requires a deep understanding of driver behaviour to be effective without being annoying. The current study provides new knowledge about driver behaviour which can inform assessment programmes for active safety systems such as Euro NCAP. This study investigated how drivers responded to bicyclists crossing their path at an intersection. The influences of car speed and cyclist speed on the driver response process were assessed for three different crossing configurations. The same experimental protocol was tested in a fixed-base driving simulator and on a test track. A virtual model of the test track was used in the driving simulator to keep the protocol as consistent as possible across testing environments. Results show that neither car speed nor bicycle speed directly influenced the response process. The crossing configuration did not directly influence the braking response process either, but it did influence the strategy chosen by the drivers to approach the intersection. The point in time when the bicycle became visible (which depended on the car speed, the bicycle speed, and the crossing configuration) and the crossing configuration alone had the largest effects on the driver response process. Dissimilarities between test-track and driving-simulator studies were found; however, there were also interesting similarities, especially in relation to the driver braking behaviour. Drivers followed the same strategy to initiate braking, independent of the test environment. On the other hand, the test environment affected participants' strategies for releasing the gas pedal and regulating deceleration. Finally, a mathematical model, based on both experiments, is proposed to characterize driver braking behaviour in response to bicyclists crossing at intersections. This model has direct implications on what variables an in-vehicle safety system should consider and how tests in evaluation programs should be designed.
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| 5. |
- Arikere, Adithya, 1987, et al.
(författare)
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On the Potential of Accelerating an Electrified Lead Vehicle to Mitigate Rear-End Collisions
- 2015
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Ingår i: Proceedings of the 3rd International Symposium on Future Active Safety Technology Towards zero traffic accidents, 2015. ; , s. 377-384
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Konferensbidrag (refereegranskat)abstract
- This paper analyzes the potential safety benefit from autonomous acceleration of an electrified lead vehicle to mitigate or prevent being struck from behind. Safety benefit was estimated based on the expected reduction in relative velocity at impact in combination with injury risk curves. Potential issues and safety concerns with the operation and implementation of such a system in the real world are discussed from an engineering and human factors stand point. In particular, the effect of the pre-collision acceleration in reducing whiplash injury risk due to change in head posture and reduction of crash severity is also discussed. In general, this study found that autonomously accelerating an electrified lead vehicle can mitigate and prevent rear-end collisions and significantly increase the safety benefits from existing systems such as autonomous emergency braking.
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| 6. |
- Bärgman, Jonas, 1972, et al.
(författare)
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Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems
- 2017
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 0001-4575. ; 102, s. 165-180
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Tidskriftsartikel (refereegranskat)abstract
- As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash avoidance and mitigation have rapidly increased in the last decades, the need to evaluate their prospective safety benefits before introduction has never been higher. Counterfactual simulations using relevant mathematical models (for vehicle dynamics, sensors, the environment, ISS algorithms, and models of driver behavior) have been identified as having high potential. However, although most of these models are relatively mature, models of driver behavior in the critical seconds before a crash are still relatively immature. There are also large conceptual differences between different driver models. The objective of this paper is, firstly, to demonstrate the importance of the choice of driver model when counterfactual simulations are used to evaluate two ISS: Forward collision warning (FCW), and autonomous emergency braking (AEB). Secondly, the paper demonstrates how counterfactual simulations can be used to perform sensitivity analyses on parameter settings, both for driver behavior and ISS algorithms. Finally, the paper evaluates the effect of the choice of glance distribution in the driver behavior model on the safety benefit estimation. The paper uses pre-crash kinematics and driver behavior from 34 rear-end crashes from the SHRP2 naturalistic driving study for the demonstrations. The results for FCW show a large difference in the percent of avoided crashes between conceptually different models of driver behavior, while differences were small for conceptually similar models. As expected, the choice of model of driver behavior did not affect AEB benefit much. Based on our results, researchers and others who aim to evaluate ISS with the driver in the loop through counterfactual simulations should be sure to make deliberate and well-grounded choices of driver models: the choice of model matters.
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| 7. |
- Bärgman, Jonas, 1972, et al.
(författare)
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Using manual measurements on event recorder video and image processing algorithms to extract optical parameters.
- 2013
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Ingår i: Proceedings of the Seventh International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design. ; , s. 177-183
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Konferensbidrag (refereegranskat)abstract
- Vehicle kinematics and optical parameters such as optical angle, optical expansion rate, and tau are thought to underlie drivers’ ability to avoid and handle critical traffic situations. Analyses of these parameters in naturalistic driving data with video, such as commercial event recordings of near-crashes and crashes, can provide insight into driver behavior in critical traffic situations. This paper describes a pair of methods, one for the range to a lead vehicle and one for its optical angle, that are derived from image processing mathematics and that provide driver behavior researchers with a relatively simple way to extract optical parameters from video-based naturalistic data when automatic image processing is not possible. The methods begin with manual measurements of the size of other road users on a video on a screen. To develop the methods, 20 participants manually measured the width of a lead vehicle on 14 images where the lead vehicle was placed at different distances from the camera. An on-market DriveCam Event Recorder was used to capture these images. A linear model that corrects distortion and modeling optics was developed to transform the on-screen measurements distance (range) to and optical angle of the vehicle. The width of the confidence interval for predicted range is less than 0.1m when the actual distance is less than 10m and the lead-vehicle width estimate is correct. The methods enable driver behavior researchers to easily and accurately estimate useful kinematic and optical parameters from videos (e.g., of crashes and near-crashes) in event-based naturalistic driving data.
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| 8. |
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| 9. |
- Dozza, Marco, 1978, et al.
(författare)
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BikeCOM – A cooperative safety application supporting cyclists and drivers at intersections
- 2013
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Ingår i: Proceedings of the 3rd Conference of Driver Distraction and Inattention, Gothenbrug, 4-6 September, 2013.
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Konferensbidrag (refereegranskat)abstract
- In 2009, 2334 cyclists died while riding bicycles in Europe. Many of those accidents occurred at road intersections, typically involved one vehicle and one bicycle, and were caused by distraction of either of the driver or the cyclist.This study describes the development and verification of a cooperative application able to prevent this type of accidents by warning both the driver and the cyclist in case of an imminent threat. This application runs on Android smartphones and relies on bicycle-to-vehicle communication to exchange safety relevant information.Naturalistic cycling data from the BikeSAFE and BikeSAFER projects was used to identify the safety critical situation to be addressed. This safety critical situation was described with use cases to envision different application scenarios and derive technical and functional requirements. After the prototype implementation, a pilot test was performed to 1) test the application, 2) develop a data analysis tools, and 3) design the protocol for a larger experiment. Both a bicycle and a car were used in this larger experiment to recreate the safety critical situation in a controlled real-traffic scenario.Results from this experiment show that cooperative applications based on smartphones and connecting bicycles and cars are feasible and desirable, however present limitations on positioning and latency strongly limit their reliability.
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| 10. |
- Dozza, Marco, 1978, et al.
(författare)
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Using Wireless Communication to Control Road-user Interactions in the Real World
- 2017
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Ingår i: Proceeding of the Road Safety and Simulation International Conference, RSS2017, 17-19 October 2017.
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Konferensbidrag (refereegranskat)abstract
- Autonomous vehicles promise to conquer the road network, revolutionize transportation, and improve traffic safety in the near future. However, before they can take over, they will be sharing the infrastructure with manned vehicles, and will be expected to behave like those vehicles do in traffic. In other words, the first autonomous vehicles will have to remain within human comfort boundaries so as not to surprise, confuse, or scare any road users.For safety reasons, comfort boundaries in critical situations can only be measured in driving simulators or on test tracks. In less critical situations, field and naturalistic studies provide the most realistic estimations of comfort boundaries. In fact, naturalistic data is collected in the real world by drivers following their daily routines; thus they capture realistic driver behavior. However, when we want to assess comfort boundaries in specific scenarios — such as intersections — with complex interactions, even large databases may offer limited data with great variability.This study presents and verifies a new experimental methodology to diminish variability in naturalistic and field data collection without compromising ecological validity. This methodology controls the environment in real time, depending on the behavior of study participants to produce specific driving situations in the real world. Recreating similar driving conditions over and over increases data consistency, enabling data to be averaged across participants and repetitions. This paper estimates comfort-zone boundaries at intersections from naturalistic data. Potential applications for this methodology include the development and evaluation of advanced driving assistance systems, as well as the design of test procedures for active safety and cooperative systems.
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