Pedal Misapplication Research Articles

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.

Virtual Driving Simulation for Pedal Error Study

This paper is about the development of a virtual driving simulation for the pedal error study among Malaysian drivers. The project is in collaboration with the Malaysian Institute of Road Safety (MIROS) and The New Car Assessment Program for Southeast Asia (ASEAN NCAP) research grant. Instead of conducting the naturalistic driving test, the virtual driving simulation will be used in the current driving simulator developed for this project. Therefore, the aim of this study is to develop the virtual driving simulation which contain some emergency braking situations, determine the foot placement on the pedal (using video observation) and to measure the total pressure on the pedals during the normal driving and emergency braking situation among Malaysian drivers. This study is focused on automatic transmission car by Malaysian drivers who aged around 20 to 50 years old that have minimum two years driving experience. A questionnaire was also given to participants, asking them about their personal information, their driving behavior, infrastructure, and safety, as well as pedal misapplication. The virtual driving simulator was equipped with some devices such as camera, pressure sensor, screen monitor, steering wheel and driver’s pedal. A study was completed successfully to determine the position of the Malaysian driver's foot on the brake pedal during emergency braking. It has been discovered that roughly 6.67% of participants in a driving research use both legs while driving and use their left foot to hit the brake pedal during emergency braking. The study also found that about 26.67% of participants feel dizzy while driving and around 96.67% of participants were surprised by the obstacles.

Identifying Pedal Misapplication Behavior Using Event Data Recorders

<div class="section abstract"><div class="htmlview paragraph">Pedal misapplication (PM) crashes, i.e., crashes caused by a driver pressing one pedal while intending to press another pedal, have historically been identified by searching unstructured crash narratives for keywords and verified via labor-intensive manual inspection. This study proposes an alternative method to identify PM crashes using event data recorders (EDRs). Since drivers in emergency braking situations are motivated to hit the brake hard, it follows that drivers in emergency braking situations that commit a PM would likewise hit the accelerator hard, likely harder than accelerator pedal application during normal driving. Thus, the time-series accelerator pedal position and the derived accelerator pedal application rate were used to isolate accelerator misapplications. Additional strategic filters were applied based on characteristics observed from previous PM analyses to reduce false positive PM identifications. These include a crash type filter, since PM crashes have been shown to manifest as majority road departure, end departure, rear-end, and forward impact crash types. After analyzing pre-crash EDR data from the National Automotive Sampling System Crashworthiness Data System (NASS/CDS) case years 1997 to 2015, evidence of PM was observed in 4.3% of weighted events. This result was substantially higher than the previously estimated 0.2% PM frequency [<span class="xref">1</span>,<span class="xref">2</span>]. The time-to-collision (TTC) at the point of PM was calculated for each case, and over 50% of cases had a TTC of less than 2.0 seconds. Over one-third of these drivers engaged the accelerator to 99% of pedal stroke or above and over one-eighth of drivers engaged both the brake and the accelerator pedals simultaneously during the recorded pre-crash period.</div></div>

Examination of Methods to Prevent Accidents Caused by Pedal Errors in Automobiles

It is difficult for drivers to prevent pedal misapplications by themselves. In this paper, we propose a system that immediately informs the driver that he/she is pressing the accelerator pedal by means of a tactile vibration of the pedal. An eccentric motor mounted on the back of the pedal generates a constant vibration with a fixed period only when the accelerator pedal is depressed. An experiment has been conducted with a driving simulator to investigate whether the pedal vibration system is effective in preventing pedal misapplication accidents and whether it is accepted by drivers. We induced pedal misapplications on a driving simulator and observed reactions of experiment participants. As a result, it was found that the pedal vibration system allowed drivers to notice pedal misapplication more quickly and to correct their foot position more rapidly. Therefore, the pedal vibration system is effective in preventing accidents caused by pedal misapplications. However, many experimental participants felt discomfort while driving.

Development of Footrest to Reduce Risk of Pedal Misapplication in Automobile Driving

Development of Footrest to Reduce Risk of Pedal Misapplication in Automobile Driving

Finding and understanding pedal misapplication crashes using a deep learning natural language model

Objective The objective of this study was to develop a system which used the BERT natural language understanding model to identify pedal misapplication (PM) crashes from their crash narratives and validate the accuracy of the system. Methods The training dataset used for this study was 11 cases from the NMVCCS study and 952 cases from the North Carolina state crash database. Cases for this study were selected from their respective full datasets using a keyword search algorithm containing terms indicative of a pedal-related mistake. A BERT language model was used to classify each case narrative as either no pedal misapplication, PM by vehicle 1, PM by vehicle 2, or PM by vehicle 3. After training, the language model was used to determine the incidence of pedal misapplication in a test dataset of 8,668 North Carolina and NMVCCS cases and these results were compared to a manual review of the dataset. After manual review, 2,969 cases were pedal misapplications. Results The model’s AUC ROC performance at detecting PM was quantified on the entire testing dataset to evaluate the power of the system to generalize to case narratives unseen at training time. The AUC ROC value was 0.9835, indicating strong generalization to all crash narratives. By choosing the optimal threshold using the ROC curve, the system correctly identified PM in 95.7% of crash narratives. When pedal misapplication was correctly identified, the correct vehicle was identified in 95.9% of cases. A total of 3,062 pedal misapplications were identified. The model labeled cases 353 times faster than a researcher. Conclusions The strong performance of the model suggests that the automated interpretation of case narratives can be used for future research studies without any manual review. This would save time and enable the use of datasets where manual review would be infeasible. The automated extraction of information from crash narratives using deep learning natural language models has not been demonstrated previously in the literature, to the best of the authors’ knowledge. This technique can be applied to large, infrequently used datasets of crash narratives and extended to extract useful vehicle, occupant, or environment information to make these datasets amenable to traditional statistical analyses.

Pedal Error Among Car Drivers: A Review on The Research Approach and Setup


 
 
 The movement of the driver’s foot from one pedal to another is a blind positioning movement. Variability of driver’s foot movement might lead to pedal error or pedal misapplication. In this paper, we reviewed the research focus in the pedal error study, who are the participants involved in the study, what kind of approach or method used to perform the pedal error study, how is the test setup, test condition, and flow of the study, and what are the factors influencing the pedal error accidents. The review searched relevant articles based on five keywords: pedal errors, pedal misapplication, sudden unintended acceleration (SUA), automotive foot pedals, and sudden acceleration accidents. Based on the review, the research focus is focusing on the factors causing the pedal error, understanding the fundamental principles of pedal misapplications, and characteristics of pedal errors among older drivers. The pedal error study has been conducted either using the naturalistic driving, driving simulation, or survey. The pedal error among ASEAN drivers is essential since there is no study related to this topic has been conducted in any ASEAN countries yet.
 
 

Age-related differences in correction behavior for unintended acceleration.

Although unintended acceleration caused by pedal misapplication is a cause of traffic accidents, fatal accidents may be avoided if drivers realize their error immediately and quickly correct how they are stepping on the pedal. This correction behavior may decline with age because the rate of fatal accidents is fairly higher for older adults than for younger adults. To investigate this possibility, the present study recruited older adults (n = 40, age range = 67-81 years) as well as younger adults (n = 40, age range = 18-32 years). In this study, they performed a pedal stepping task during which they were required to stop the simulated vehicle as quickly as possible when a red signal was presented on a monitor. During most trials, the vehicle decelerated/stopped when the brake pedal was applied in a normal manner. In a few trials, however, stepping on the brake pedal resulted in sudden acceleration of the vehicle (i.e., the occurrence of the unintended acceleration); when this occurred, the participants had to release the pedal and re-step on another pedal to decelerate/stop the vehicle as quickly as possible. We focused on the age-related differences of the reaction latencies during three time periods: from the appearance of the red signal on the screen until stepping on the pedal (Period 1), from stepping on the pedal until the release of the pedal (Period 2), and from the release of the pedal until re-stepping of another pedal (Period 3). The results showed that there was no age-related difference in the latency of Period 1, p = .771, whereas those of Periods 2 and 3 were longer for the older adults (ps < .001). The results suggest that there are age-related differences in error detection and correction abilities under unintended situations with foot pedal manipulation.

Pedal Misapplication: Interruption Effects and Age-Related Differences.

ObjectiveThis study aimed to investigate whether pedal misapplication occurs more frequently when a pedal task is interrupted for a longer period of time.BackgroundMisapplication 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.MethodsForty 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).ResultsPedal 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.ConclusionPedal misapplication increases when the pedal task is interrupted for a longer time period, especially for older adults.ApplicationThe findings contribute to our understanding of when and where pedal misapplications tend to occur.

Evaluating Hazard Response Behavior of a Driver Using Physiological Signals and Car-Handling Indicators in a Simulated Driving Environment

Road traffic accidents are a major cause of casualties and costly implications to all the stakeholders. Research focusing on the driver as one of the causal agent of accidents has been studied for centuries and with the advent of modernized driver assistance technologies. This paper sought to evaluate response of a driver using active-driving performance indicators like reaction time and physiological signal response (surface electromyogram), to understand hazard response behavior. Simulation of driving scenes was done using Unity3D engine and VR Head mounted display. The driver was presented with stimulus (collision objects) of different size and distance. From the results, an event scene that the driver considered hazardous was marked with increased electromyography response distinct from non-event scenes. From the results, we noted an increase in pedal misapplication during hazard response. The proposed approach is applicable in a real time driving analysis for on-road risk level classification.

Geospatial analysis of residential parking behaviors using a semantic modeling approach

Pedal misapplications by drivers have received attention as being an underlying factor for the phenomenon known as sudden unintended acceleration (SUA) in vehicles. This research investigates behaviors during a common task for drivers, namely residential parking. Parking has been identified as a maneuver that is often linked with SUA mishaps. Using driving trajectories data from a set of four couples collected as part of a naturalistic driving study, we investigate whether consistent behaviors can be detected when parking at home from a geospatial perspective, i.e., whether deceleration and braking occur in a characteristic way at the end of a driving trajectory, and whether these behaviors vary when the geospatial context of parking changes. An ontology-based approach is used to frame the key behaviors of the naturalistic driving, and big data techniques are applied to extract parking-specific behaviors from driving trajectories. Results show that individuals showed relatively consistent parking behaviors under the same geospatial context and the standard deviation of the deceleration threshold has a larger discrepancy between couples parking at different residences than within couples where parking occurs at the same place.

Pedal misapplication in taxi drivers

Pedal misapplication in taxi drivers

G8-3 Relationship between Accelerator/Brake Position and Pedal Misapplication

G8-3 Relationship between Accelerator/Brake Position and Pedal Misapplication

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.

Modeling Types of Pedal Applications Using a Driving Simulator.

The aim of this study was to examine variations in drivers' foot behavior and identify factors associated with pedal misapplications. Few studies have focused on the foot behavior while in the vehicle and the mishaps that a driver can encounter during a potentially hazardous situation. A driving simulation study was used to understand how drivers move their right foot toward the pedals. The study included data from 43 drivers as they responded to a series of rapid traffic signal phase changes. Pedal application types were classified as (a) direct hit, (b) hesitated, (c) corrected trajectory, and (d) pedal errors (incorrect trajectories, misses, slips, or pressed both pedals). A mixed-effects multinomial logit model was used to predict the likelihood of one of these pedal applications, and linear mixed models with repeated measures were used to examine the response time and pedal duration given the various experimental conditions (stimuli color and location). Younger drivers had higher probabilities of direct hits when compared to other age groups. Participants tended to have more pedal errors when responding to a red signal or when the signal appeared to be closer. Traffic signal phases and locations were associated with pedal response time and duration. The response time and pedal duration affected the likelihood of being in one of the four pedal application types. Findings from this study suggest that age-related and situational factors may play a role in pedal errors, and the stimuli locations could affect the type of pedal application.

Pedal Misapplication: Crash Characteristics and Contributing Factors

Pedal Misapplication: Crash Characteristics and Contributing Factors

Sequential Dependencies in Driving

The effect of recent experience on current behavior has been studied extensively in simple laboratory tasks. We explore the nature of sequential effects in the more naturalistic setting of automobile driving. Driving is a safety-critical task in which delayed response times may have severe consequences. Using a realistic driving simulator, we find significant sequential effects in pedal-press response times that depend on the history of recent stimuli and responses. Response times are slowed up to 100 ms in particular cases, a delay that has dangerous practical consequences. Further, we observe a significant number of history-related pedal misapplications, which have recently been noted as a cause for concern in the automotive safety community. By anticipating these consequences of sequential context, driver assistance systems could mitigate the effects of performance degradations and thus critically improve driver safety.

"Unintended Acceleration": Human Factors Engineering Issues and Solutions

In the first few months of 2010 the news media reported numerous instances of “unintended acceleration”. Vehicles were recalled because a floor mat was thought to be snagging the accelerator pedal. However, some vehicles that had gone through the recall still experienced unintended accelerations, indicating that the problem also lay elsewhere. In the 1980s there were recalls of over 100,000 Audi vehicles with automatic transmissions in which drivers had reported unintended accelerations. Earlier cases had also been reported (Mortimer, 2011), so the issue is an old one. As a result of such runaway events, primarily in vehicles with automatic transmissions, automakers equipped them with shift-interlocks, so that the vehicle could not be moved into either a forward or reverse gear after starting the engine unless the driver’s foot was depressing the brake pedal. About 83% of unintended acceleration events were reduced by this device (Schmidt, 1993), confirming the role of driver pedal misapplication when starting out. Other studies found that drivers show pedal confusions also when the vehicle is under way. Those events are not reduced by the shift-interlock. Rogers & Wierwille (1988) found about 0.2% of foot movements resulted in a “serious” pedal misapplication error in a simulator. Tomerlin & Vernoy (1990) found that 1 of 169 of their drivers stepped on the accelerator instead of the brake and continued to do so in a driving test. Such results show that drivers “frequently” make pedal errors, especially when considering that there is about one brake application per mile (Mortimer et al, 1970) in the U.S. The panel members will discuss the human factors issues that cause pedal misapplication in various types of vehicles and their frequency, including crashes that result. The thrust of the discussions will be on how our present knowledge can be used to reduce these hazardous events and to discern what additional information is needed to solve the “unintended acceleration” problem.

Human Factors in Sudden Acceleration Incidents

Numerous governmental studies have established that the primary cause of nearly all sudden acceleration incidents is pedal misapplication. Additional scientific work has further examined the role of pedal control, vehicle design, and other various human factors associated with incidents of this type. As an extension of previous research, we examined various factors that could contribute to these incidents using recent data from the North Carolina Accident Reporting System. While vehicle class was not predictive of a pedal error that led to a sudden acceleration event, the age of the driver was statistically related to the more significant pedal error types. Specifically, we found that over half of accidents involving older drivers occurred while parking and involved them completely missing the brake. Also, young and elderly women were over-represented for these miss-type pedal errors while parking. These data underscore the role of human factors in understanding causes and factors involved in pedal misapp...

Cars Gone Wild: The Major Contributor to Unintended Acceleration in Automobiles is Pedal Error

“Unintended-acceleration” automobile accidents typically begin when the driver first enters the car, starts the engine, and intends to press his/her right foot on the brake while shifting from Park to a drive gear (Drive or Reverse). The driver reports an unintended (uncommanded) full-throttle acceleration, coupled with a loss of braking, until the episode ends in a crash. Pedal misapplications – where the right foot contacts the accelerator instead of the brake that was intended – have been linked to these accidents (Schmidt, 1989, 1993) which, in the 1980s, were thought to occur only at the start of a driving cycle (and/or with the car in Park). But, in 1997, we identified over 200 pedal errors as the cause of accidents reported in the North Carolina database; these crashes occurred during the driving cycle (Schmidt et al., 1997), and/or with the vehicle in a gear other than Park. Our present work provides a more thorough analysis of these North Carolina Police Accident Reports from 1979 to 1995. The vast majority of pedal misapplications (over 92%) (a) occurred during the driving cycle, (b) were generally in “unhurried” conditions, and (c) were categorically separate from those events referred to as unintended-acceleration episodes at start-up. These ideas are explanatory for the recent (2009–2010) surge of unintended-acceleration reports, perhaps even suggesting that all of these crashes are caused by pedal errors, and that none of them are based on some vehicle defect(s).