Driver's Foot Research Articles

An Intelligent Cockpit Tailored Carpet for Human‐Vehicle Interaction Enhancement and Driving Intention Recognition

AbstractIn the realm of intelligent cockpits, the predominant emphasis on enhancing driving safety and comfort through human‐vehicle interaction and driving behavior monitoring has conventionally centered on the upper body of the driver. Regrettably, the wealth of information inherent in the lower half of the driver's body, particularly the feet, tends to be systematically underestimated by researchers. A specialized intelligent carpet tailored for automotive cockpits that integrates sponge‐based triboelectric sensor to monitor driver's foot movement is proposed. The intelligent carpet contains two areas, namely the human‐vehicle interaction sensing area and the driving intention monitoring area. With the human‐vehicle interaction sensing area, the driver can interact with the vehicle through the left foot, resulting in reducing the occupation of visual resources and hand load. Furthermore, the driving intention monitoring area supported by the right foot can effectively identify driver's intentions and driver's behaviors, which are essential to trajectory prediction, optimal path planning, and driving safety. It is demonstrated that an intelligent carpet is potentially useful for human‐vehicle interaction, and transportation optimization and accident prevention.

LDIPRS: A novel longitudinal driving intention prior recognition technique empowered by TENG and deep learning

For autonomous vehicles, real-time and accurate longitudinal driving intention recognition is crucial as it effectively enhances driving safety and improves the driving experience. This study proposes a novel data and model hybrid-driven fine-grained longitudinal driving intention prior recognition system (LDIPRS). Firstly, the system integrates a human-pedal interaction sensor (HPIS) based on triboelectric nanogenerators for fine-grained longitudinal driving maneuver monitoring and the channel attention (CA)-enhanced convolutional neural network (CBRCNet). The HPIS, integrated into the vehicle's acceleration and brake pedals, is capable of monitoring driver foot movement information in the form of electrical signals before the vehicle responds, achieving data level advance. The collected electrical signals are fed into the CBRCNet network, which models and learns the mapping relationship between these signals and fine-grained longitudinal driving intentions, leading to model level advances. The HPIS completes the capture of longitudinal maneuver information 541 ms before the driving simulator starts to respond at the data level. At the model level, CBRCNet can achieve a recognition accuracy of 96.1 % based on partial response data (50 ms after starting response) rather than complete response data of the HPIS. Finally, our proposed LDIPRS realizes the recognition of emergency braking, rapid acceleration, normal braking, and normal acceleration in advance by 732 ms, 1035 ms, 1757 ms, and 2227 ms, respectively. This study introduces self-powered, low-cost, highly sensitive triboelectric sensors into the field of intention recognition, and combines the triboelectric sensors with deep learning algorithms to offer a promising solution to improve the safety of autonomous vehicles and the efficiency of intelligent transportation systems.

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.

Analyzing Driver Foot Behavior between Regenerative and Service Braking

Analyzing Driver Foot Behavior between Regenerative and Service Braking

Benefits estimation of regenerative braking versus service braking

A central question not yet examined in the literature is whether regenerative braking provides a kinematic deceleration safety advantage in time and distance over traditional service braking. This research explores three conditions of braking (traditional service braking, low level of regenerative braking, and high level of regenerative braking) to determine any safety advantages regenerative braking offers. Thirty participants took part in a simulator study with a between-subjects study design, allocating 10 participants per condition. The study drive took place in a simulator and involved three braking events. The results showed a significant difference between the means of the three conditions for average deceleration of the vehicle in the time interval between the driver releasing the accelerator and pressing the brake for all three events showing RB did provide the drivers with a braking advantage. When events 1 and 2 were combined, there was also significance with maximum brake force. Practitioner summary: This research looked to determine whether regenerative braking provides a deceleration safety advantage over traditional service braking. The results showed RB did provide the drivers with a braking advantage. The results also showed driver foot behaviour differed with the RB High condition.

Impact Attenuator Optimum Design for a FSAE Racing Car by Numerical and Experimental Crash Analysis

One of the most important requirements of the Formula SAE (Society of Automotive Engineers) race car design competition is that the car structure must guarantee a high protection level in case of frontal impacts, by preventing intrusions into the driver foot zone or dangerous deceleration levels. These functions are mainly performed by the impact attenuators, which have to guarantee a high specific energy absorption capacity (SEA) and in order to preserve vehicle performances, have to be as light weighted as possible. The aim of this study is the design of an impact attenuator, to be mounted on a Formula SAE car, which main purpose is to obtain the optimal crash energy management, maximizing the absorbed energy and optimizing the geometry. The outcome of the study highlights that the absorber structure made up of honeycomb sandwich panels (primary energy absorbers), realized by means of different aluminium alloys employing an innovative design considering particular geometrical cavities within the structure, could lead to reduce the overall weight and to achieve a more progressive deformation during the impact.

Robust driver foot tracking and foot gesture recognition using capacitive proximity sensing

Robust driver foot tracking and foot gesture recognition using capacitive proximity sensing

Prediction of accelerator operation using machine learning

This paper reports the regression analysis of the horizontal motion of a car driver's foot from a brake pedal to an accelerator pedal using machine learning methods, namely, neural network (NN), radial basis function network (RBFN), random forest (RF), and support vector regression (SVR) models, in order to predict the timing of when the driver steps on the accelerator from an web camera movie. The approximation performances of these models are compared based on root mean squared error (RMSE) and the estimated timing when the driver's foot reaches the accelerator pedal. From the results, the RF model could approximate the driver's foot motion most precisely. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Evaluation of driver lower extremity injuries in 16 oblique crashes with THOR

Injuries to the lower extremity (LE) continue to occur in frontal crashes despite increased attention on the vehicle structure and restraint design. This study focuses on thigh, leg, foot, and ankle injuries as well as occupant factors and intrusion levels. Sixteen vehicles, including three same types, with same moving deformable barriers of the same mass, velocity, and barrier face properties, and the same occupant Test Device for Human Occupant Restraint (THOR) 50th percentile adult male in the driver's seat were used to conduct oblique impact test. Data from the left (driver side) oblique crash tests conducted by National Highway Traffic Safety Administration (NHTSA) were used in this paper to analyse the detailed intrusion characteristics and the driver side THOR injuries from head to foot in these 16 tests. Different regions of the THOR dummy were analysed. Maximum values of all lower extremity injury criteria were obtained and analysed. Intrusion and lower extremity injuries correlation was found, knee airbag and lower extremity injury correlation was also analysed. The foot-well X and Y intrusions in the 16 tests rank from minimum 14 to maximum 309 mm and from −7 to 184 mm, independently. Sixty-nine per cent right knee displacement is greater than the left knee displacement. Thirty-one per cent knee displacement and 44% left upper tibia force of the 16 tests have values that exceed injury assessment reference values. Left upper tibia force was generally greater than other tibia forces. Half of the left upper tibia index (TI) and 37.5% of the right lower TI do not meet the standard value. The foot/ankle complex is generally at a higher risk than the other parts of the leg. Same vehicle reproducibility and injury were also analysed. Right knee displacement, left femur force, left upper tibia force, left upper TI, and left ankle rotation are the most critical injuries in the respective regions of the lower extremity. Intrusion may be more prominent in some frontal damage types than in others, but not the only reason for lower extremity injuries. Other factors that influence LE injuries are the position of driver foot, the geometry of the foot-well area, the direction of intrusion, the impact energy, and acceleration of the floor. Lower extremity is the most frequently injured body region with respect to more serious injuries in the analysed test data.

Vision Based Approach for Modelling and Prediction of Driver’s Behaviour

Driver inattention have been reported as a cause of fatal traffic accidents. To mitigate this problem we have to examine the link between the driver and the automobile to see what modifications can be made to the automobile to assist the driver. A new vision-based approach is developed for understanding driver behavior by using foot gesture analysis. Driver's foot video is captured, image processing is done using MATLAB software. The proposed system have potential to warn the driver to critical situations and predict need for braking action. If braking action is being planned by the driver then manual brake is applied otherwise automatic brake is used. To predict critical events obstacle detecting system is developed using ultrasonic sensors. Simulation result shown in graphical user interface.

The pattern of the electromagnetic field emitted by mobile phones in motor vehicle driving simulators

The paper reports the results of the determinations of UMTS EMF distributions in the driver’s cab of motor vehicle simulators. The results will serve as the basis for future research on the influence of EMF emitted by mobile phones on driver physiology. Two motor vehicle driving simulators were monitored, while an EMF source was placed at the driver's head or on the dashboard of the motor vehicle driving simulator. For every applied configuration, the maximal electric field strength was measured, as were the values at 16 points corresponding to chosen locations on a driver's or passenger's body. When the power was set for the maximum (49 mW), a value of 27 V/m was measured in the vicinity of the driver's head when the phone was close to the head. With the same power, when the phone was placed on the dashboard, the measured maximum was 15.2 V/m in the vicinity of the driver's foot. Similar results were obtained for the passenger. Significant perturbations in EMF distribution and an increase in electric field strength values in the mo-tor vehicle driving simulator were also observed in comparison to free space measurements, and the electric field strength was up to 3 times higher inside the simulator. This study can act as the basis of future studies concerning the influence of the EMF emitted by mobile phones on the physiology of the driver. Additionally, the authors postulate that it is advisable to keep mobile phones at a distance from the head, i.e. use, whenever possible, hands-free kits to reduce EMF exposure, both for drivers and passengers.

상용차 캐빈 내의 열전모듈에 의한 열유동 수치해석

The steady three-dimensional numerical analysis on the thermal flow using standard k-<TEX>${\varepsilon}$</TEX> turbulence model was carried out to investigate the air cooling effect of a cooler on the cabin for a commercial vehicle. Here, the heat exchanging method of this cabin cooler uses the cooling effect of a thermoelectric module. In consequence, the air system resistance of a cooler within the cabin is about 12.1 Pa as a static pressure, and then the operating point of a virtual cross-flow fan considering in this study is formed in the comparatively low flowrate region. The discharging air temperature of a cooler is about <TEX>$14{\sim}15^{\circ}C$</TEX>. Moreover, the air cooling temperature difference obtained under the outdoor cabin temperature of <TEX>$40^{\circ}C$</TEX> shows about <TEX>$7{\sim}9^{\circ}C$</TEX> in a driver resting space and about <TEX>$9{\sim}14^{\circ}C$</TEX> in the front of a driver's seat including the space of a driver's foot.

Modeling and prediction of driver behavior by foot gesture analysis

Understanding driver behavior is an essential component in human-centric Intelligent Driver Assistance Systems. Specifically, driver foot behavior is an important factor in controlling the vehicle, though there have been very few research studies on analyzing foot behavior. While embedded pedal sensors may reveal some information about driver foot behavior, using vision-based foot behavior analysis has additional advantages. The foot movement before and after a pedal press can provide valuable information for better semantic understanding of driver behaviors, states, and styles. They can also be used to gain a time advantage in predicting a pedal press before it actually happens, which is very important for providing proper assistance to driver in time critical (e.g. safety related) situations. In this paper, we propose and develop a new vision based framework for driver foot behavior analysis using optical flow based foot tracking and a Hidden Markov Model (HMM) based technique to characterize the temporal foot behavior. In our experiment with a real-world driving testbed, we also use our trained HMM foot behavior model for prediction of brake and acceleration pedal presses. The experimental results over different subjects provided high accuracy (∼94% on average) for both foot behavior state inference and pedal press prediction. By 133 ms before the actual press, ∼74% of the pedal presses were predicted correctly. This shows the promise of applying this approach for real-world driver assistance systems.

The inadequate effect of automobile seating on foot posture and callus development

Driver posture is an important factor to be considered in the ergonomics design process of automobiles. Most decisions during automobile design and manufacture are informed by studying the intricate biomechanical components of human musculoskeletal systems to ensure maximum comfort, safety and well-being during driving. A case study is presented that confirms inappropriate foot position as a causative factor for the development of abnormal lateral/plantar heel callosities when driving a 4 × 4-style vehicle. The driver's foot position was influenced by the seat geometry of the vehicle. Cessation of driving the 4 × 4-style vehicle and driving of an alternative automobile while on holiday for a period of 4 weeks resolved the condition. On return to the 4 × 4-style vehicle, however, the abnormal callus patterns redeveloped while using the same footwear and no change in any other parameters. It is therefore suggested that seat and consequent foot position is an important ergonomic factor that should be addressed in the future design of automobile seating.

Development and validation of virtual driving simulator for the spinal injury patient.

We developed a virtual reality (VR) driving simulator in order to safely evaluate and improve the driving ability of spinal injury patients. The simulator is composed of an actual car, a beam projector, and a large screen. For the interface of our driving simulator, an actual car was adapted and then connected to a computer. We equipped the car with hand control driving devices especially adapted for spinal injury patients. A beam projector was used so that the subjects could see the virtual scene on a large screen set up in front of them. The virtual environment (VE) consisted of 18 sections (e.g., a speed-limited road, a straight road, a curved road, a left turn) and each section was linked naturally to the next. The subjects selected for this trial were 10 normal drivers with valid driving licenses and 15 patients with thoracic or lumbar cord injuries who had prior driving experience. For evaluation, five driving skills were measured, including average speed, steering stability, centerline violations, traffic signal violations, and driving time in various road conditions such as straight and curved roads. The normal subjects manipulated the gas pedal and the brake with their feet, while the patients manipulated a hand control with their hands. After they finished driving the whole course, the participants answered the questions such as "How realistic did the virtual reality driving simulator seem to you?" and "How much was your fear reduced?" In this study, we found that the difference in manipulation method (i.e., the patient group's hand control versus the normal driver's foot controls) does not seem to influence relative performance in the VR driving simulator, though training to improve the use of hand controls in the VR driving simulator would be useful to reduce the fear that the patients feel while driving.

Initial Driver Foot Placement as an Antecedent to Pedal Error

Two observational studies were conducted to examine driver foot pedal operation characteristics which may influence pedal activation errors. Driver behaviors were observed during controlled closed-course and natural driving situations to document individual pedal operating characteristics. A substantial portion of the drivers in both studies shifted from park to forward and/or reverse gears without positioning a foot over or on the brake pedal. A small percentage of drivers used both feet for pedal activation. The results of these studies suggest that pedal design and layout should take these behaviors into consideration. Either method would likely be less accurate and potentially more hazardous than when the right foot is directly over the brake pedal, and suggests the efficacy of a mechanical interlock to prevent gear selection from park to either forward or reverse gears until contact with the brake pedal is made.

Zero-latency tracking of predictable targets by time-delay systems

When a ball rolls in front of a car there is a 200 ms time delay before the driver's foot starts to move from the accelerator pedal to the brake pedal. This 200 ms reaction time is typical of all human movements. However, we have found that humans can track predictable targets with zero-latency. In an effort to explain this anomaly, we have developed a control technique that has general applicability. Our scheme allows a time-delay system to track targets with zero-latency whenever the target movement is continuous, smooth, and predictable. In this paper, we explain our control scheme, present our model for the human eye movement system, and suggest other possible applications, For this control scheme the target-selective adaptive controller constructs an adaptive signal that depends on the frequency, amplitude and waveform of the target movement, as well as on the time delay and dynamics of the plant. When this adaptive signal is applied to the time-delay system it allows zerolatency tracking and improved dynamic performance. Figure 1 shows this scheme applied to a general state-variable feedback control system with a time delay in the forward path. The system input r^t), is composed of two parts : the reference source, rs(t) and the adaptive signal, ra(£). When r3(t) is not a known target waveform, ra(£) is turned off ; r^t) then equals rs(t) and the closed-loop transfer function becomes 7(8) _ hT(sI - A^bJSC exp ( - ST) ( ' exp ( - sr) The exp ( — sr) term in the numerator is a pure time delay that remains in spite of the feedback. The similar term in the denominator produces the phase lag that reduces the allowable gain. Of the other symbols, Y(s) represents

Transmitting Torque of Automobile Friction Clutches

Considering the starting performance of the car and the driver's foot motion the ratio-x-of the maximum transmitting torque of the friction clutch-Mo-to the maximum engine torque-ME-(x=MC/ME) is determined. The results obtained are as follows. x≒1.5 for passenger car x≒2 for generally used truck.