Modeling Types of Pedal Applications Using a Driving Simulator

The effect of an occlusion-induced delay on braking behavior in critical situations: A driving simulator study

OBJECTIVE

To share results of an experiment that used visual occlusion for a new purpose: inducing a waiting time.

BACKGROUND

Senders was a leading figure in human factors. In his research on the visual demands of driving, he used occlusion techniques.

METHODS

In a simulator experiment, we examined how drivers brake for different levels of urgency and different visual conditions. In three blocks (1 = brake lights, 2 = no brake lights, 3 = occlusion), drivers followed a vehicle at 13.4 or 33.4 m distance. At certain moments, the lead vehicle decelerated moderately (1.7 m/s2) or strongly (6.5 m/s2). In the occlusion condition, the screens blanked for 0.4 s (if 6.5 m/s2) or 2.0 s (if 1.7 m/s2) when the lead vehicle started to decelerate. Participants were instructed to brake only after the occlusion ended.

RESULTS

The lack of brake lights caused a delayed response. In the occlusion condition, drivers adapted to the instructed late braking by braking harder. However, adaptation was not always possible: In the most urgent condition, most participants collided with the lead vehicle because the ego-vehicle's deceleration limits were reached. In non-urgent conditions, some drivers braked unnecessarily hard. Furthermore, while waiting until the occlusion cleared, some drivers lightly touched the brake pedal.

CONCLUSION

This experimental design demonstrates how drivers (sometimes fail to) adjust their braking behavior to the criticality of the situation.

APPLICATION

The phenomena of biomechanical readiness and (inappropriate) dosing of the brake pedal may be relevant to safety, traffic flow, and ADAS design.

Electric Bus Pedal Misapplication Detection Based on Phase Space Reconstruction Method

Due to the environmental protection of electric buses, they are gradually replacing traditional fuel buses. Several previous studies have found that accidents related to electric vehicles are linked to Unintended Acceleration (UA), which is mostly caused by the driver pressing the wrong pedal. Therefore, this study proposed a Model for Detecting Pedal Misapplication in Electric Buses (MDPMEB). In this work, natural driving experiments for urban electric buses and pedal misapplication simulation experiments were carried out in a closed field; furthermore, a phase space reconstruction method was introduced, based on chaos theory, to map sequence data to a high-dimensional space in order to produce normal braking and pedal misapplication image datasets. Based on these findings, a modified Swin Transformer network was built. To prevent the model from overfitting when considering small sample data and to improve the generalization ability of the model, it was pre-trained using a publicly available dataset; moreover, the weights of the prior knowledge model were loaded into the model for training. The proposed model was also compared to machine learning and Convolutional Neural Networks (CNN) algorithms. This study showed that this model was able to detect normal braking and pedal misapplication behavior accurately and quickly, and the accuracy rate on the test dataset is 97.58%, which is 9.17% and 4.5% higher than the machine learning algorithm and CNN algorithm, respectively.

Application and Evaluation of a Non-Accident-Based Approach to Road Safety Analysis Based on Infrastructure-Related Human Factors

Too often the identification of critical road sites is made by “accident-based” methods that consider the occurred accidents’ number. Nevertheless, such a procedure may encounter some difficulties when an agency does not have reliable and complete crash data at the site level (e.g., accidents contributing factors not clear or approximate accident location) or when crashes are underreported. Furthermore, relying on accident data means waiting for them to occur with the related consequences (possible deaths and injuries). A non-accident-based approach has been proposed by PIARC. This approach involves the application of the Human Factors Evaluation Tool (HFET), which is based on the principles of Human Factors (HF). The HFET can be applied to road segments by on-site inspections and provides a numerical performance measure named Human Factors Scores (HFS). This paper analyses which relationship exists between the results of the standard accident-based methods and those obtainable with HFET, based on the analysis of self-explaining and ergonomic features of the infrastructure. The study carried out for this purpose considered 23 km of two-way two-lane roads in Italy. A good correspondence was obtained, meaning that high risky road segments identified by the HFS correspond to road segments already burdened by a high number of accidents. The results demonstrated that the HFET allows for identifying of road segments requiring safety improvements even if accident data are unavailable. It allows for improving a proactive NSS, avoiding waiting for accidents to occur.

Pedal Misapplication: Interruption Effects and Age-Related Differences

OBJECTIVE

This study aimed to investigate whether pedal misapplication occurs more frequently when a pedal task is interrupted for a longer period of time.

BACKGROUND

Misapplication of a vehicle's brake and accelerator pedals can cause severe traffic accidents, especially for older drivers. The present study provides empirical support for the hypothesis that pedal misapplication occurs more frequently when drivers are interrupted for longer periods of time and is demonstrated more prominently in older drivers.

METHODS

Forty younger participants and 40 older participants were asked to perform a pedal choice response task (stepping on either a brake or accelerator pedal) that had been preceded by an interruption task (i.e., touch number task).

RESULTS

Pedal misapplications occurred more frequently when the pedal choice response task was preceded by the touch number task for a longer interval (about 120 s) than for a shorter interval (about 30 s). Furthermore, the time-related increase in pedal misapplications was greater for older participants.

CONCLUSION

Pedal misapplication increases when the pedal task is interrupted for a longer time period, especially for older adults.

APPLICATION

The findings contribute to our understanding of when and where pedal misapplications tend to occur.

Blueprint for a Simulation Framework to Increase Driver Training Safety in North America: Case Study

Despite numerous recent advances in the classroom and in-vehicle driver training and education over the last quarter-century, traffic accidents remain a leading cause of mortality for young adults—particularly, those between the ages of 16 and 19. Obviously, despite recent advances in conventional driver training (e.g., classroom, in-vehicle, Graduated Driver Licensing programs), this remains a critical public safety and public health concern. As advanced vehicle technologies continue to evolve, so too does the unintended potential for mechanical, visual, and/or cognitive driver distraction and adverse safety events on national highways. For these reasons, a physics-based modeling and high-fidelity simulation have great potential to serve as a critical supplementary component of a near-future teen-driver training framework. Here, a case study is presented that examines the specification, development, and deployment of a “blueprint” for a simulation framework intended to increase driver training safety in North America. A multi-measure assessment of simulated driver performance was developed and instituted, including quantitative (e.g., simulator-measured), qualitative (e.g., evaluator-observed), and self-report metrics. Preliminary findings are presented, along with a summary of novel contributions through the deployment of the training framework, as well as planned improvements and suggestions for future directions.

Effects of aging on foot pedal responses to visual stimuli

BACKGROUND

Car accidents due to unexpected forward or backward runaway by older drivers are a serious social problem. Although the cause of these accidents is often attributed to stepping on the accelerator instead of the brake, it is difficult to induce such pedal application errors systematically with usual drive simulators. We developed a simple personal computer system that induces the pedal errors, and investigate the effects of age on the error behaviors.

METHODS

The system consisted of a laptop computer and a three-pedal foot mouse. It measured response time, accuracy, and flexibility of pedal operation to visual stimuli. The system displayed two open circles on the computer display, lighting one of the circles in a random order and interval. Subjects were instructed to press the foot pedal with their right foot as quickly as possible when the circle was lit; the ipsilateral pedal to the lit circle in a parallel mode and the contralateral pedal in a cross mode. When the correct pedal was pressed, the light went off immediately, but when the wrong pedal was pressed, the buzzer sounded and the light remained on until the correct pedal was pressed. During a 6-min trial, the mode was switched between parallel and cross every 2 min. During the cross mode, a cross mark appears on the display. The pedal responses were evaluated in 52 subjects divided into young (20-29 years), middle-aged (30-64 years), and older (65-84 years) groups. Additionally, the repeatability of the pedal response characteristic indicators was examined in 14 subjects who performed this test twice.

RESULTS

The mean response time was 95 ms (17%) longer in the older group than in the young group. More characteristically, however, the older group showed 2.1 times more frequent pedal errors, fell into long hesitations (response freezing > 3 s) 16 times more often, and took 1.8 times longer period to correct the wrong pedal than the young groups. The indicators of pedal response characteristics showed within-individual repeatability to the extent that can identify the age-dependent changes.

CONCLUSIONS

Hesitations and extended error correction time can be associated with increased crash risk due to unexpected runaway by older drivers. The system we have developed may help to uncover and evaluate physiological characteristics related to crash risk in the elderly population.

Evaluating variability in foot to pedal movements using functional principal components analysis

There are reasons why the driver's foot may not be applied to the correct pedal while driving and this can lead to unintended consequences. In this study, we seek to capture common and unique patterns of variations in drivers' foot movements using functional principal components analysis (FPCA). This analysis technique was used to analyze three categories of pedal response types (direct hits, corrected trajectories, and pedal errors) based on the various foot to pedal trajectories. Data from a driving simulator study with video data of foot movements for 45 drivers was used for analyses. Most foot movements show common patterns associated with direct hits and corrected trajectories with some level of variation. However, those foot movements associated with unique patterns might be early indicators of pedal errors. The findings of this study can be used with collision mitigation systems to provide early detection of foot trajectories that are more likely to result in a pedal error.

Foot placement during error and pedal applications in naturalistic driving

Data from a naturalistic driving study was used to examine foot placement during routine foot pedal movements and possible pedal misapplications. The study included four weeks of observations from 30 drivers, where pedal responses were recorded and categorized. The foot movements associated with pedal misapplications and errors were the focus of the analyses. A random forest algorithm was used to predict the pedal application types based the video observations, foot placements, drivers' characteristics, drivers' cognitive function levels and anthropometric measurements. A repeated multinomial logit model was then used to estimate the likelihood of the foot placement given various driver characteristics and driving scenarios. The findings showed that prior foot location, the drivers' seat position, and the drive sequence were all associated with incorrect foot placement during an event. The study showed that there is a potential to develop a driver assistance system that can reduce the likelihood of a pedal error.