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3D digital human modeling (DHM) tools for vehicle packaging facilitate ergonomic design and evaluation based on anthropometry, comfort, and force analysis. It is now possible to quickly predict postures and positions for drivers with selected anthropometry based on ergonomics principles. Despite their powerful visual representation technology for human movements and postures, these tools are still questioned with regard to the validity of the output they provide, especially when predictions are made for different populations. Driving postures and positions of two populations (i.e. North Americans and Koreans) were measured in actual and mock-up SUVs to investigate postural differences and evaluate the results provided by a DHM tool. No difference in driving postures was found between different stature groups within the same population. Between the two populations, however, preferred angles differed for three joints (i.e., ankle, thigh, and hip).

Shudder vibration of a hydraulic power steering system during parking maneuver was studied with numerical and experimental methods. To quantify vibration performance of the system and recognize important stimuli for drivers, a shudder metric was derived by correlation between objective measurements and subjective ratings. A CAE model for steering wheel vibration analysis was developed and compared with measured data. In order to describe steering input dependency of shudder, a new dynamic friction modeling method, in which the magnitude of effective damping is determined by average velocity, was proposed. The developed model was validated using the measured steering wheel acceleration and the pressure change at inlet of the steering gear box. It was shown that the developed model successfully describes major modes by comparing the calculated FRF of the hydraulic system with measured one from the hydraulic excitation test.

In general, driving performance is developed to meet preference of average customers. But there is no single standardized guideline which can satisfy various driving tastes of all drivers whose gender, cultural background, and age are different. To resolve this issue, automotive companies have introduced drive mode buttons which drivers can manually select from Normal, Eco, and Sport driving modes. Although this multi-mode manual systems is more efficient than single-mode system, it is in a transient state where drivers need to go through troubles of frequently selecting their preferred drive mode in volatile driving situations It is also doubtful whether the three-categorized driving mode can meet complex needs of drivers.. In order to settle these matters, it is necessary to analyze individual driving style automatically and to provide customized driving performance service in real time.

Conventional EPS (Electric Power Steering) systems are operated by one type of steering tuning map set by steering test drivers before being released to customers. That is, the steering efforts can't change in many different driving conditions such as road conditions (low mu, high mu and unpaved roads) or some specific driving conditions (sudden stopping, entering into EPS failure modes and full accelerating). Those conditions can't give drivers consistent steering efforts. This paper approached the new concept technology detecting those conditions by using vehicle and EPS sensors such as tire wheel speeds, vehicle speed, steering angle, steering torque, steering speed and so on. After detecting those conditions and judging what the best steering efforts for safe vehicle driving are, EPS systems automatically can be changed with the steering friction level and selection of steering optimized mapping on several conditions.

Professional bus drivers are highly exposed to physical fatigue and work-related injuries because driving task includes complicated actions that require a variety of ability and cause extreme concentration or strain. For this reason, there has always been some sense of concern regarding driver fatigue, especially for drivers of commercial vehicles. In this study, we have tried to analyze quantitative fatigue degree of urban bus drivers by measuring their physiological signals. The investigation is made up of the following approaches: a traditional questionnaire survey and video-ethnographic method with 4-way cameras. The close-circuit cameras are installed to observe the upper and lower body of real drivers when they are in driving or even resting. This approach can help to understand urban bus drivers' behaviors and fatigue-related issues. Based on the video-ethnographic investigation results above, we have got certain patterns of drivers.

This paper presents the research related to the self-driving system that has been actively carried out recently. Previous studies have been limited to ensure the path following performance in linear and steady state-alike handling region with small lateral acceleration. However, in the high speed driving, the vehicle cornering response is extended to nonlinear region where tire grips are saturated. This requires a technology to create the driving path for minimum time maneuvering while grasping the tire grip limits of the vehicle in real time. The entire controller consists of three stages-hierarchy: The target motion is determined in the supervisor phase, and the target force to follow the target behavior is calculated in the upper stage controller. Finally, the lower stage controller calculates the actuator phase control input corresponding to the target force.

With the spread of new trends such as autonomous driving and vehicle subscription service, drivers may pay less attention to the maintenance of the vehicle. Brake pads being safety critical components, the wear condition of all service brakes is required by regulation to be indicated by either acoustic of optical devices or a means of visually checking the degree of brake lining wear [1]. Current application of the wear indicator in the market uses either sound generating metal strip or wire harness based pad wear sensor. The former is not effective in generating clear alarm to the driver, and the latter is not cost effective, and there is a need for more effective and low cost solution. In this paper, a pad wear monitoring system using MOC(Motor On Caliper) EPB(Electric Parking Brake) ECU is proposed. An MOC EPB is equipped with a motor, geartrain and an ECU. The motor current when applying the parking brake is influenced by the mechanical load at the brake pad side of the system.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

Suspension is a system which operates dynamically according to road condition unlike other system statically mounted to the body. Especially this is more remarkable in high performance vehicle because there are more high inputs from road to suspension than normal vehicle. For this reason, the tightening torque of suspension system of high performance vehicle is more important than other systems and normal vehicle. To support the clamping between parts against force from road when cornering, optimized tightening torque is required to maximize R&H performance. For this optimization, it should be conducted first to comprehend how much performance effects on vehicle by tightening torque. This paper presents relationship between tightening torque of suspension parts hardware and R&H performance.

Today, many automakers are using LED lamp sources in exterior lamps to establish brand awareness and introduce specialized lamp designs. These eye-catching LED lamp source solutions require many control functions as the lamp functions are diversified and advanced, and accordingly the requirements for standardization and optimization of controllers are increasing. In particular, our LED rear combination lamps have a variety of LED loads according to the design of the lamp model, the installation position, and the diagnostic regulations, so that the design complexity and the number of specifications of the controller are increased [4]. In recent years, more and more aesthetic designs and new technologies are used by various automakers to optimize their controllers in cooperation with global partners to optimize costs [1].

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

In order to perform the Optimal Route Planning avoiding traffic congestion, the structural elements (Rode type, Link type, Facilities type, Lane number, Turning type) in digital map and real-time traffic information are required. However, subjectively tuned cost weights of these elements, non theoretical relationship, and partially supported real-time traffic information that are mostly used for this implementation are not enough to satisfy. Therefore, in this research, by analyzing the relationship between the previously acquired traffic information history for some period of time and elements in digital map, we introduce the reasonable traffic information model that makes to estimate the speed information. Including the estimated speed, all the important factors of map database and the driver's preference, finally we made the cost model.

This paper introduces newly developed suspension system for the all-new SantaFe model of Hyundai Motor Company which will be on the market this year. The new suspension of the all-new SantaFe has been developed to give better handling and driving confidence to a driver compared to the previous model while maintaining a good ride experience. To achieve these targets, the suspension has been fully changed and finely adjusted. The compliance characteristics have been contrasted to those of the previous model. Also, the crash performance and package efficiency which are related to suspension layout has been considered without limitation of suspension performance. Based on the customer’s voice of market, the suspension of the newly developed SantaFe has tried to fit the various customer’s demands.

As autonomous driving vehicles are developed, automotive makers start focusing on implementing new door types, such as a falcon wing door or a B-pillarless dual sliding door, which could be one of the best-selling points. To make these doors electrically operate, applying advanced sensors like a RADAR or an Ultrasonic sensor is almost mandatory. Without these sensors, the door could be easily damaged or the customers could be seriously injured. Due to physical limitation, however, every sensor has a noise in nearby area and has a specification of the minimum detection range, which causes us not to be able to precisely detect the object in close area. If the controller cannot detect the precise distance of the object, the door could malfunction, since it could misidentify the obstacles. In this paper, we propose a method to reduce the minimum detection range by applying a prior estimation scheme.

In the path following problem, a commercial vehicle has a delay of a hydraulic steering actuator and slow steering response accordingly. In addition, there are disturbances due to the harsh driving conditions of commercial vehicles. These disturbances may include uncertainties about actuator dynamic delay, modeling error and steering angle sensor offset. Designing a lateral controller with good performance that can overcome this problem is the key to successfully carrying out autonomous driving of commercial vehicles. Usually, it is difficult to consider disturbances with uncertainties in the geometric based control methods. Therefore, this paper proposed a lateral controller using feedback augmented disturbance observer for the commercial vehicle. First, a dynamics was modeled which can describe delay of the hydraulic actuator of the commercial vehicle. After that, a lateral controller was designed based on this dynamics model.

In this study it will show, big data analysis and user survey of driving records were conducted to investigate frequency of use and ease of operation of the regen paddle to control one-pedal driving system in electric vehicle. According to 3.8 million driving record big data analysis result, it was found that the driver manipulates 3.31 times on average during a single trip, mainly during the early stages of driving. According to user observation research result in 41.8% of participants did not used or used less than 5 time of regen paddle during one single trip. Also 336 participants, which occupy 83%, responded that the regen paddle manipulation for one-pedal driving was inconvenient. In conclusion, because of the use frequency of the regen paddle is low and the operation of regen paddle is inconvenient. It seems necessary to change the design of the regen paddle.

‘Active safety systems’ are actively being developed to prevent collisions. The integration of ‘active safety systems’ and traditional ‘passive safety systems’ such as seatbelt and airbags is an important issue. The ‘Integrated safety’ performance is that comprehensively controls the performance of ‘active’ and ‘passive’ safety systems to reduce occupant injuries. To develop ‘integrated safety’ performance, it is important to develop crash scenarios for autonomous vehicles. This study is about the development of ‘Estimation Tool of Occupant Injury Risk’ for deriving risk integrated safety scenarios focused on occupant injury. The results of random traffic simulation using ‘Virtual Prototype’ were used to select parameters, and ‘MADYMO Equivalent Simplified Vehicle Crash Analysis Model’ was used to derive F-D characteristics for each vehicle collision condition.

Bad weather conditions such as torrential rain, heavy snow, and thick fog frequently occur worldwide. Vehicle accidents in such bad weather conditions account for a significant portion of all vehicle accidents, and the level of damage is relatively severe compared to other accidents that occur in clear weather. This paper analyzes the driver's driving stability in bad weather conditions, which has such a significant meaning, in various ways through experiments on the inconvenience experienced by the driver. In this study, three levels of bad weather conditions were implemented in a driving simulator environment to evaluate driver inconvenience for six activities. Through driving experiment, quantitative bio-signals and vehicle signals were analyzed in each weather condition. The SD survey was used to assess the driver's inconvenience level for activities performed while driving and analyze the ranking of inconvenience.

Expanding various future mobilities such as purpose built vehicle (PBV), urban air mobility (UAM), and robo-taxi, the application of autonomous driving system (ADS) technology is also spreading. The main point of ADS is to ensure safety by monitoring vehicle anomalies to prevent functional failure or accident. In this study, a model-based diagnosis and prognosis process was established using degradation data generated during autonomous driving simulation. A vehicle model was designed using Modelica/Dymola, and autonomous driving simulation was performed by integrating the lane keeping assistant (LKA) system with the vehicle model using Matlab/Simulink. Degradation data for the 3 components (a shock absorber damper, a suspension bush, and a tire) of the chassis system were input into the integrated simulation model. The degradation behavior was monitored with K-nearest neighbor (K-NN) and Gaussian mixture model (GMM).

APAS refers to a low speed sound warning system of electric vehicles, which emits alerting sound only to target pedestrians by sound focusing techniques with array of speakers and object detective camera. In the present study, experimental and numerical investigations are conducted in designing speaker part and array of APAS with consideration of three main performance matrices; HEV/EV warning sound regulations in Europe and U.S., pedestrian awareness, and driver’s noise comfort. The present APAS speaker consists of back enclosure, wave guide and front grill. Each of these components plays an important role for characterizing frequency emphasis and sound directivity. The main impedance frequencies of the speaker are determined by considering warning sound regulations and also by analyzing acoustic frequency response at in/outside of a vehicle.