Braking Maneuvers Research Articles

Using the Buckingham π Theorem for Multi-System Transfer Learning: A Case-Study with 3 Vehicles Sharing a Database

Many advanced driver assistance schemes or autonomous vehicle controllers are based on a motion model of the vehicle behavior, i.e., a function predicting how the vehicle will react to a given control input. Data-driven models, based on experimental or simulated data, are very useful, especially for vehicles difficult to model analytically, for instance, ground vehicles for which the ground-tire interaction is hard to model from first principles. However, learning schemes are limited by the difficulty of collecting large amounts of experimental data or having to rely on high-fidelity simulations. This paper explores the potential of an approach that uses dimensionless numbers based on Buckingham’s π theorem to improve the efficiency of data for learning models, with the goal of facilitating knowledge sharing between similar systems. A case study using car-like vehicles compares traditional and dimensionless models on simulated and experimental data to validate the benefits of the new dimensionless learning approach. Preliminary results from the case study presented show that this new dimensionless approach could accelerate the learning rate and improve the accuracy of the model prediction when transferring the learned model between various similar vehicles. Prediction accuracy improvements with the dimensionless scheme when using a shared database, that is, predicting the motion of a vehicle based on data from various different vehicles was found to be 480% more accurate for predicting a simple no-slip maneuver based on simulated data and 11% more accurate to predict a highly dynamic braking maneuver based on experimental data. A modified physics-informed learning scheme with hand-crafted dimensionless features was also shown to increase the improvement to precision gains of 917% and 28% respectively. A comparative study also shows that using Buckingham’s π theorem is a much more effective preprocessing step for this task than principal component analysis (PCA) or simply normalizing the data. These results show that the use of dimensionless variables is a promising tool to help in the task of learning a more generalizable motion model for vehicles, and hence potentially taking advantage of the data generated by fleets of vehicles on the road even though they are not identical.

Control System for Regenerative Braking Efficiency in Electric Vehicles with Electro-Actuated Brakes

<div>This article presents the design and the analysis of a control logic capable of optimizing vehicle’s energy consumption during a braking maneuver. The idea arose with the purpose of enhancing regeneration and health management in electric vehicles with electro-actuated brakes. Regenerative braking improves energy efficiency and allows a considerable reduction in secondary emissions, but its efficiency is strongly dependent on the state of charge (SoC) of the battery. In the analyzed case, a vehicle equipped with four in-wheel motors (one for each wheel), four electro-actuated brakes, and a battery was considered.</div> <div>The proposed control system can manage and optimize electrical and energy exchanges between the driveline’s components according to the working conditions, monitoring parameters such as SoC of the battery, brake temperature, battery temperature, motor temperature, and acts to optimize the total energy consumption. The solution devised allows first to maximize the effects of regenerative braking when the battery SoC is too high to regenerate efficiently, then to safeguard the condition of the battery for both the battery’s long life and overheating and safeguard the condition of the brakes to prevent their overheating.</div>

A Method for the Rapid Propagation of Emergency Event Notifications in a Long Vehicle Convoy

Convoys composed of autonomous vehicles could improve the transportation and freight industries in several ways. One of the avenues of improvement is in fuel efficiency, where the vehicles maintain a close following distance to each other in order to reduce air resistance by way of the draft effect. While close following distances improve fuel efficiency, they also reduce both the margin of safety and the system’s tolerance to disturbances in relative position. The system’s tolerance to disturbances is known as string stability, where the error magnitude either grows or decays as it propagates rearward through the convoy. One of the major factors in a system’s string stability is its delay in sending state updates to other vehicles, the most pertinent being a hard braking maneuver. Both external sensors and vehicle-to-vehicle communication standards have relatively long delays between peer vehicle state changes and the information being actionable by the ego vehicle. The system presented here, called the Convoy Vehicular Ad Hoc Network (Convoy VANET), was designed to reliably propagate emergency event messages with low delay while maintaining reasonable channel efficiency. It accomplishes this using a combination of several techniques, notably relative position-based retransmission delays. Our results using Network Simulator 3 (ns3) show the system propagating messages down a 20-vehicle convoy in less than 100 ms even with more than a 35% message loss between vehicles that are not immediately adjacent. These simulation results show the potential for this kind of system in situations where emergency information must be disseminated quickly in low-reliability wireless environments.

Adaptive Advanced Emergency Braking on Combined Road Friction Coefficients

In this study, an Advanced Emergency Braking System (AEBS) is adopted to the combined road friction coefficients by proposing an emergency steering maneuver. AEBS is one of the significant driver assistant systems to avoid rear-end collisions. AEBS supports the drivers with acoustic and optical warnings before applying the full braking maneuver. However, in special cases, such as the sudden decrease of road friction coefficient during braking, a single hard braking maneuver without a proper steering assist may not be sufficient to prevent a rear-end collision. Therefore, AEBS may work with the autonomous emergency steering systems to prevent inevitable rear-end collisions. The originality of this study arises from the necessity of the adaptation of the AEBS to work in cooperation with the autonomous emergency steering systems. A predictive controller was used to support the emergency braking maneuver with an autonomous steering maneuver via observing the yaw rate of the vehicle. The predictive controller was developed in MATLAB software. The implementation of the controller was performed in a non-linear four-wheel vehicle model in the IPG/CarMaker simulation environment. The communication between the simulation environment and MATLAB software was established in the Simulink interface of MATLAB. The results proved that the predictive controller maintained the vehicle lateral stability without causing any type of collisions.

Characterizing the effect of mind wandering on braking dynamics in partially autonomous vehicles

Partially autonomous driving systems may require the human driver to take control at any moment, yet by their design, often cause difficulty with attention management. In this preliminary study, we propose a data- and dynamics-driven approach to characterize driving performance in a partially autonomous vehicle during a manual braking event, under attentive or mind wandering states. A 10-participant experiment was completed in an advanced driving simulator. We employ a non-parametric learning technique, conditional distribution embeddings, to the driving simulator data, to evaluate likelihood of successfully completing the braking maneuver, under both attentive and mind wandering states. Our approach shows a statistically significant difference in braking profiles during mind wandering and non-mind wandering episodes for each participant. Our results reveal that heterogeneity in driving performance may have important implications for the design of autonomy that is responsive to attentional states. Data-driven tools, such as the one proposed here, may be useful in designing participant-specific alerts and warnings for control handovers and other safety-critical maneuvers, because of their potential to accommodate heterogeneous response.

High-risk event prone driver identification considering driving behavior temporal covariate shift

Drivers who perform frequent high-risk events (e.g., hard braking maneuvers) pose a significant threat to traffic safety. Existing studies commonly estimated high-risk event occurrence probabilities based upon the assumption that data collected from different time periods are independent and identically distributed (referred to as i.i.d. assumption). Such approach ignored the issue of driving behavior temporal covariate shift, where the distributions of driving behavior factors vary over time. To fill the gap, this study targets at obtaining time-invariant driving behavior features and establishing their relationships with high-risk event occurrence probability. Specifically, a generalized modeling framework consisting of distribution characterization (DC) and distribution matching (DM) modules was proposed. The DC module split the whole dataset into several segments with the largest distribution gaps, while the DM module identified time-invariant driving behavior features through learning common knowledge among different segments. Then, gated recurrent unit (GRU) was employed to conduct time-invariant driving behavior feature mining for high-risk event occurrence probability estimation. Moreover, modified loss functions were introduced for imbalanced data learning caused by the rarity of high-risk events. The empirical analyses were conducted utilizing online ride-hailing services data. Experiment results showed that the proposed generalized modeling framework provided a 7.2% higher average precision compared to the traditional i.i.d. assumption based approach. The modified loss functions further improved the model performance by 3.8%. Finally, benefits for the driver management program improvement have been explored by a case study, demonstrating a 33.34% enhancement in the identification precision of high-risk event prone drivers.

Experimental Validation of a Driver Monitoring System

This paper presents an analysis of the risk of neck injury in vehicle occupants as a consequence of an impact. A review of the formulation of indexes that are used in the assessment and investigation of neck injury risk is discussed with the aim of providing a new, more appropriate index using suitable sensorized equipment. An experimental analysis is proposed with a new driver monitoring device using low-cost sensors. The system consists of wearable units for the head, neck, and torso where inertial measurement sensors (IMU) are installed to record data concerning the occupant’s head, neck, and torso accelerations while the vehicle moves. Two laser infrared distance sensors are also installed on the vehicle’s steering wheel to record the position data of the head and neck, as well as an additional IMU for vehicle acceleration values. To validate both the device and the new index, experiments are designed in which different sensorized volunteers reproduce an emergency braking maneuver with an instrumented vehicle at speeds of 10, 20, and 30 km/h before the beginning of any braking action. The neck is particularly sensitive to sudden changes in acceleration, so a sudden braking maneuver is enough to constitute a potential risk of cervical spine injury. During the experiments, large accelerations and displacements were recorded as the test speed increased. The largest accelerations were obtained in the experimental test at a speed of 30 km/h with values of 19.17, 9.57, 9.28, and 5.09 m/s2 in the head, torso, neck, and vehicle, respectively. In the same experiment, the largest displacement of the head was 0.33 m and that of the neck was 0.27 m. Experimental results have verified that the designed device can be effectively used to characterize the biomechanical response of the neck in car impacts. The new index is also able to quantify a neck injury risk by taking into account the dynamics of a vehicle and the kinematics of the occupant’s head, neck, and torso. The numerical value of the new index is inversely proportional to the acceleration experienced by the vehicle occupant, so that small values indicate risky conditions.

Investigating sources for variability in volunteer kinematics in a braking maneuver, a sensitivity analysis with an active human body model.

Occupant kinematics during evasive maneuvers, such as crash avoidance braking or steering, varies within the population. Studies have tried to correlate the response to occupant characteristics such as sex, stature, age, and BMI, but these characteristics explain no or very little of the variation. Therefore, hypothesis have been made that the difference in occupant response stems from voluntary behavior. The aim of this study was to investigate the effect from other sources of variability: in neural delay, in passive stiffness of fat, muscle tissues and skin, in muscle size and in spinal alignment, as a first step towards explaining the variability seen among occupants in evasive maneuvers. A sensitivity analysis with simulations of the SAFER Human Body Model in braking was performed, and the displacements from the simulations were compared to those of volunteers. The results suggest that the head and torso kinematics were most sensitive to spinal alignment, followed by muscle size. For head and torso vertical displacements, the range in model kinematics was comparable to the range in volunteer kinematics. However, for forward displacements, the included parameters only explain some of the variability seen in the volunteer experiment. To conclude, the results indicate that the variation in volunteer vertical kinematics could be partly attributed to the variability in human characteristics analyzed in this study, while these cannot alone explain the variability in forward kinematics. The results can be used in future tuning of HBMs, and in future volunteer studies, when further investigating the potential causes of the large variability seen in occupant kinematics in evasive maneuvers.

Respiratory patterns in spontaneously breathing near-term lambs delivered by caesarean section under spinal anaesthesia.

The transition to newborn life has typically been studied in intubated and mechanically ventilated newborn lambs delivered via caesarean section (CS) under general anaesthesia. As a result, little is known of the spontaneous breathing patterns in lambs at birth, particularly those at risk of developing respiratory distress (RD). We have developed a method for delivering spontaneously breathing near-term lambs to characterise their breathing patterns in the immediate newborn period. At 137-8 days gestation (2-3 days prior to delivery; term ∼147 days), fetal lambs (n = 7) were partially exteriorised for instrumentation (insertion of catheters and flow probes) before they were returned to the uterus. At 140 days, lambs were delivered via CS under light maternal sedation and spinal anaesthesia. Lambs were physically stimulated and when continuous breathing was established, the umbilical cord was clamped. Breathing patterns were assessed by measuring intrapleural and upper-tracheal pressures during the first four hours after birth. Newborn lambs display significant heterogeneity in respiratory patterns in the immediate newborn period that change with time after birth. Seven distinct breathing patterns were identified including: (i) quiet (tidal) breathing, (ii) breathing during active periods, (iii) breathing during oral feeding, (iv) tachypnoea, (v) expiratory braking manoeuvres, (vi) expiratory pauses or holding, and (vii) step changes in ventilation. We have described normal respiratory behaviour in newborn lambs, in order to identify respiratory behaviours that are indicative of RD in term newborn infants.

Acoustic effects of drone flights during sudden decelerations

With introduction of U-Spaces into European urban airspaces, unmanned aircraft traffic is expected to increase in the coming years. The growing number of unmanned aircraft, common known as drones, raises the question of the noise impact of these vehicles. So far, this new noise source has only been investigated acoustically in a rudimentary way. The German Environment Agency has, therefore, launched a measurement campaign with various small drone models to investigate acoustic effects. Since drone flights must be designed to be safe, a measurement campaign was conducted in which the models performed a full braking maneuver just before the measurement microphone. This is the case for collision avoidance or when strong gusts of wind occur. In addition, binaural measurements were recorded to provide psychoacoustic findings, as these parameters may be related to the degree of annoyance perceived by the public. In this paper, the measurements and results are presented. Noise levels of the overflights arecompared with noise levels of the deceleration maneuvers. In addition, psychoacoustic quantities such as loudness or sharpness are used and compared for both maneuvers. Finally, conclusions are drawn for the evaluation of drone noise, which can be used for future noise regulations or standardization.

Data-Driven Modeling and Regulation of Aircraft Brakes Degradation via Antiskid Controllers

In ground vehicles, braking actuator degradation and tire consumption do not represent a significant maintenance cost as the lifespan of both components, at least in common situations, is rather long. In the aeronautical context, and for aircraft in particular, instead, braking actuator degradation and tire consumption significantly contribute to an aircraft maintenance cost due to the frequency of their replacement. This is mainly due to the fact that aircraft braking maneuvers last significantly longer than those in the automotive context. So that the antilock braking system is always active during the braking maneuver, making its impact on the consumption of the two components significant. This work proposes an innovative data-driven model of brake and tire degradation, showing how they are related to the antiskid controller parameters. The analysis is carried out in a MATLAB/Simulink environment on a single wheel rigid body model, validated experimentally, which includes all the nonlinear effects peculiar of the aeronautic context. The results show that by using an appropriate antiskid control approach, it is possible to directly regulate the consumption of these components while at the same time guaranteeing the required braking performance.

On the Benefits of Active Aerodynamics on Energy Recuperation in Hybrid and Fully Electric Vehicles

In track-oriented road cars with electric powertrains, the ability to recuperate energy during track driving is significantly affected by the frequent interventions of the antilock braking system (ABS), which usually severely limits the regenerative torque level because of functional safety considerations. In high-performance vehicles, when controlling an active rear wing to maximize brake regeneration, it is unclear whether it is preferable to maximize drag by positioning the wing into its stall position, to maximize downforce, or to impose an intermediate aerodynamic setup. To maximize energy recuperation during braking from high speeds, this paper presents a novel integrated open-loop strategy to control: (i) the orientation of an active rear wing; (ii) the front-to-total brake force distribution; and (iii) the blending between regenerative and friction braking. For the case study wing and vehicle setup, the results show that the optimal wing positions for maximum regeneration and maximum deceleration coincide for most of the vehicle operating envelope. In fact, the wing position that maximizes drag by causing stall brings up to 37% increased energy recuperation over a passive wing during a braking maneuver from 300 km/h to 50 km/h by preventing the ABS intervention, despite achieving higher deceleration and a 2% shorter stopping distance. Furthermore, the maximum drag position also reduces the longitudinal tire slip power losses, which, for example, results in a 0.4% recuperated energy increase when braking from 300 km/h to 50 km/h in high tire–road friction conditions at a deceleration close to the limit of the vehicle with passive aerodynamics, i.e., without ABS interventions.

Data-driven and uncertainty-aware robust airstrip surface estimation

The performances of aircraft braking control systems are strongly influenced by the tire friction force experienced during the braking phase. The availability of an accurate estimate of the current airstrip characteristics is a recognized issue for developing optimized braking control schemes. The study presented in this paper is focused on the robust online estimation of the airstrip characteristics from sensory data usually available on an aircraft. In order to capture the nonlinear dependency of the current best slip on sequential slip-friction measurements acquired during the braking maneuver, multilayer perceptron (MLP) approximators have been proposed. The MLP training is based on a synthetic data set derived from a widely used tire–road friction model. In order to achieve robust predictions, MLP architectures based on the drop-out mechanism have been applied not only in the offline training phase but also during the braking. This allowed to online compute a confidence interval measure for best friction estimate that has been exploited to refine the estimation via Kalman Filtering. Open loop and closed loop simulation studies in 15 representative airstrip scenarios (with multiple surface transitions) have been performed to evaluate the performance of the proposed robust estimation method in terms of estimation error, aircraft braking distance, and time, together with a quantitative comparison with a state-of-the-art benchmark approach.

Does ABS ensure good performance in emergency braking for less skilled motorcyclists?

This study aims to investigate whether motorcyclists are able to use the full potential of anti-lock braking systems (ABS) in demanding braking situations that maintain the natural coupling of action and perception of emergency events, or whether instead the lack of braking skills in riders makes ABS almost ineffective and comparable to non-ABS brakes on dry pavement. Six experienced riders performed two experimental tests. First test included 12 emergency braking trials in a realistic scenario using a mock-up of an intersection conflict with a car initiating a left turn manoeuvre across the path (LTAP) of a motorcycle approaching from the opposite direction as an unpredicted moving hazard. Second test included three trials in a planned self-timed hard braking. The speed at the onset of braking was 35–45 km/h. The braking performance was measured from the initiation of brake pressure until the full stop of the vehicle. Front wheel ABS usage was determined by the pressure in the master cylinder and wheel callipers. The testing resulted in 85 data runs with full stop braking manoeuvres.Results revealed four categories of riders classified by their front wheel ABS usage during the emergency braking tests, which included two riders who underused front wheel ABS (9.6% and 27.4% of braking time on average). The worst case resulted in a significantly longer braking distance (braking deceleration of 5.2 m/s2). The highest skilled rider, who reached initial jerks close to 30 m/s3, used the ABS of the front wheel 93.7% of the braking time on average, resulting in a braking deceleration of 7.71 m/s2. Overall, the best braking performance was achieved in trials where the front ABS was activated for more than 80% of the braking. In planned self-timed hard braking test, where riders have more time to plan the braking manoeuvre, the experience rider with lowest performance during the emergency braking test improved braking efficiency and was able to increase ABS activation from 9.6% to 26.8% of the time, achieving a deceleration of 6.24 m/s2.ABS is demonstrated to reduce stopping distances and to improve stability under all braking conditions, but such features are not enough to guarantee a good braking performance in emergency events if the riders have not the skills to utilize the full braking power of the motorcycle. Less skilled riders, even with ABS, may not have the confidence to increase braking power further when reaching high decelerations that push them to the limit of their stabilisation control in emergency braking, thus increasing braking distance with potentially life-threatening consequences. Our results suggest that many experience riders still need knowledge and skill to make the ABS work to its optimum in emergency events to avoid crashes. Further research with larger sample sizes including the full diversity of the motorcyclist population is recommended to determine the actual proportion of motorcyclists underusing ABS.

Determining Key Parameters with Data-Assisted Analysis of Conditionally Automated Driving

In conditionally automated driving, a vehicle issues a take-over request when it reaches the functional limits of self-driving, and the driver must take control. The key driving parameters affecting the quality of the take-over (TO) process have yet to be determined and are the motivation for our work. To determine these parameters, we used a dataset of 41 driving and non-driving parameters from a previous user study with 216 TOs while performing a non-driving-related task on a handheld device in a driving simulator. Eight take-over quality aspects, grouped into pre-TO predictors (attention), during-TO predictors (reaction time, solution suitability), and safety performance (off-road drive, braking, lateral acceleration, time to collision, success), were modeled using multiple linear regression, support vector machines, M5’, 1R, logistic regression, and J48. We interpreted the best-suited models by highlighting the most influential parameters that affect the overall quality of a TO. The results show that these are primarily maximal acceleration (88.6% accurate prediction of collisions) and the TOR-to-first-brake interval. Gradual braking, neither too hard nor too soft, as fast as possible seems to be the strategy that maximizes the overall TO quality. The position of the handheld device and the way it was held prior to TO did not affect TO quality. However, handling the device during TO did affect driver attention when shorter attention times were observed and drivers held their mobile phones in only one hand. In the future, automatic gradual braking maneuvers could be considered instead of immediate full TOs.

The analysis of energy recovered by an electric vehicle during selected braking manoeuvres

Electrical vehicles have the ability to partially recover some kinetic energy during braking. Kinetic energy is transformed into electric energy, which is fed to the battery by the control system and stored there for further use. The aim of this paper was to analyse the levels of energy recovered by an electric vehicle during braking at various speeds and with different braking intensities. The first phase of testing consisted of vehicle braking tests in real-life conditions. The registered speed profiles were then used as input data for the simulation software. The authors have also analysed the effect of the state of charge of the battery and of the vehicle’s load on the amount of energy recovered during braking. The performed simulation tests demonstrated that the level of recovered energy is significantly affected by the initial braking speed and by the force of pressure applied to the brake pedal. The amount of recovered energy is less affected by the state of charge (SOC) of the battery and by the vehicle’s load. Energy regeneration during braking is currently an important research topic. The efficiency of an electric vehicle depends on the range, which can be extended thanks to the additional energy recovered during braking maneuvers. The presented preliminary simulation results are intended to assess the level of energy recovery in electric vehicles. The authors are aware that a full, comprehensive analysis requires additional research using electric vehicles that will verify the results presented in the paper.

Railcar Dynamic Response during Braking Maneuvers Based on Frequency Analysis

The dynamic response of a vehicle during braking is influenced by the tangential forces developed at the wheel-rail’s contact surface. The friction coefficient affects the load transfer from the wheel’s tread to the vehicle. In this work, the vibrations of a scale-down railway vehicle are monitored during braking and their relationship with the friction coefficient between wheel and rail is found out. The vehicle is instrumented with encoders, accelerometers, and is controlled via Bluetooth. The tests are carried out with clean and friction-modified rails. The tangential forces transmitted from the wheel to the railcar’s body are visualized in time and frequency using a proposed correlation algorithm based on the outputs of the Continuous Wavelet Transform (CWT). The results demonstrate that tangential forces have a significant impact on railway vehicles under conditions of high friction coefficients and large creep values.

Experimental Study on Longitudinal Acceleration of Urban Buses and Coaches in Different Road Maneuvers.

A vehicle's longitudinal acceleration is a parameter often used for determining vehicle motion dynamics. This parameter can also be used to evaluate driver behavior and passenger comfort analysis. The paper presents the results of longitudinal acceleration tests of city buses and coaches recorded during rapid acceleration and braking maneuvers. The presented test results demonstrate that longitudinal acceleration is significantly affected by road conditions and surface type. In addition, the paper presents the values of longitudinal accelerations of city buses and coaches during their regular operation. These results were obtained on the basis of registration of vehicle traffic parameters in a continuous and long-term manner. The test results showed that the maximum deceleration values recorded during the tests of city buses and coaches in real traffic conditions were much lower than the maximum deceleration values found during sudden braking maneuvers. This proves that the tested drivers in real conditions did not have to use sudden braking. The maximum positive acceleration values recorded in acceleration maneuvers were slightly higher than the acceleration values logged during the rapid acceleration tests on the track.

Vertical-Longitudinal Coupling Effect Investigation and System Optimization for a Suspension-In-Wheel-Motor System in Electric Vehicle Applications

In-wheel-motor-drive electric vehicles have attracted enormous attention due to its potentials of improving vehicle performance and safety. Road surface roughness results in forced vibration of in-wheel-motor (IWM) and thus aggravates the unbalanced electric magnetic force (UEMF) between its rotor and stator. This can further compromise vertical and longitudinal vehicle dynamics. This paper presents a comprehensive study to reveal the coupled vertical–longitudinal effect on suspension-in-wheel-motor systems (SIWMS) along with a viable optimization procedure to improve ride comfort and handling performance. First, a UEMF model is established to analyze the mechanical–electrical–magnetic coupling relationship inside an IWM. Then a road–tire–ring force (RTR) model that can capture the transient tire–road contact patch and tire belt deformation is established to accurately describe the road–tire and tire–rotor forces. The UEMF and the RTRF model are incorporated into the quarter-SIWMS model to investigate the coupled vertical–longitudinal vehicle dynamics. Through simulation studies, a comprehensive evaluation system is put forward to quantitatively assess the effects during braking maneuvers under various road conditions. The key parameters of the SIWMS are optimized via a multi-optimization method to reduce the adverse impact of UEMF. Finally, the multi-optimization method is validated in a virtual prototype which contains a high-fidelity multi-body model. The results show that the longitudinal acceleration fluctuation rate and the slip ratio signal-to-noise ratio are reduced by 5.07% and 6.13%, respectively, while the UEMF in the vertical and longitudinal directions varies from 22.2% to 34.7%, respectively, and is reduced after optimization. Thus, the negative coupling effects of UEMF are minimized while improving the ride comfort and handling performance.

The effect of a braking maneuver on the occupant’s kinematics of a highly reclined seating position in a frontal crash

Objective This study aims to make the comparison of the kinematics and possible injury values of the occupant in the highly reclined seating position in two cases: the first case is without the braking maneuver prior to the frontal crash, and the second case is considering the braking maneuver prior to the impact. Methods This study used the MADYMO human body model 50th percentile mid-size male seated on the front passenger seat model with the seatback reclined rearward 53° (fully reclined seatback) to simulate the occupant biomechanics and behavior during a frontal collision. To achieve the study aim, two simulation models were created. The first model is called the non-precrash model (VaAM-O). It was set to simulate the occupant kinematics in the fully reclined initial seating posture in the 200 ms of a crash without the braking maneuver before the crash. The second model, called the precrash model (VaAM-I), identified the occupant’s initial position after the car model performed a 1s deceleration of a braking maneuver. VaAM-I has then also simulated the occupant kinematics in 200 ms of a crash. Results This study showed a significant difference in the occupant’s posture at the beginning of the crash phase in the two cases. The upper torso of VaAM-I rotated up and moved forward earlier than VaAM-O prior to the crash phase due to the influence of the braking maneuver, and at the 50 ms, when the airbag deployed completely, the head had no contact with the airbag, and the head in VaAM-I forwarded to the airbag closer than VaAM-O about 24% of the distance to the airbag. Conclusions This study supplements the value data for the study of the out-of-position OOP of the occupant in the frontal crash. The contact force and position contact between the head and the airbag could attract the audience’s attention. On the other hand, a comparison of the seatbelt force and the seatbelt contacts the body between the conventional seatbelt as in this study, and the seat-integrated seatbelt system in the case wherein the occupant seats on the front seat with a highly reclined seatback should be performed.