The Outer waist belt is a component that has both a functional element that is a sealing with the outside of the door and an element contributing to improvement of the appearance of the outside the door. Therefore, it is an important design factor to select a material that is favorable to permanent deformation and does not deteriorate in appearance due to external environmental conditions. In this paper, the section and production method for Hybrid structured belt which has TPV rib for good sealing and PVC skin for good appearance dealt with.
The objective of this study was to investigate the interactions between elderly drivers and a proactive steering intervention system in a human-machine shared framework. To this end, we conducted an experiment using a driving simulator. The main focus of our analysis was on how elderly drivers react to shared driving under various conditions regarding the target paths of the system. From the result obtained for 20 elderly drivers, we confirmed three types of reaction tendencies: persistence to usual driving, persistence to newly learned driving, and autonomy abandonment.
Various Advanced Driver Assistance Systems (ADAS) become prevailing recently. In this paper, we argue the safety analysis of combined ADAS systems. The definition of ADAS is vague, so we obey the definition of Code of Practice for the Design and Evaluation of ADAS (CoP) (1). In this definition, the ADAS have to be active, that is, it “provide(s) active support for lateral and/or longitudinal control”. There is a technical report that provides the consolidation way of various warnings emitted by the several ADAS systems (ISO/TR 12204 (2)). However, the problem is not limited to the warning signals. We have to consider the controller of ADAS because it is actively controlled from its definition. We need the more integrated way, and we provide a way to handle this situation by using the idea: DESH-G model.
We have developed a portable breath-based alcohol detection device that can easily determine whether a person has consumed alcohol. The device consists of a sensor to detect saturated water vapor in human breath and three semiconductor gas sensors to detect ethanol, acetaldehyde, and hydrogen. The device can determine whether the gas introduced into it is human exhaled breath and can detect the alcohol level at the same time. This ensures that the sample is of a person’s breath, not an artificial source. The selected gas sensors exhibited low relative standard deviation (RSD) for the repeated measurements. Each gas concentration is calculated using an algorithm based on a differential evolution method with a measurement accuracy of approximately ±5 ppm. These functions can be integrated into a smart key.
This paper proposes and evaluates an algorithm called Multi-Objective planning based on Simulated Annealing (MOSA) that plans a trajectory (speed profile) for a passenger car on a free, single lane road. This algorithm is relying on a decomposition of the decision space into “chunks” that are optimized separately. Two objectives have been taken into account: travel time and fuel consumption. Optimization constraints are built from safety modelings combining legal speed, curves speed limits and junctions limits. The multi-objective optimization is performed through a linear scalairisation method and the optimization is a parametric optimization based on simulated annealing. The algorithm has been tested on simulated annealing convergence and results show a good convergence under 500 iterations and a small sensitivity to variables initialization. However, sensitivity to core parameters of the simulated annealing (initial temperature and temperature decreasing rate) is very high and some guidelines for the calibration of these parameters are given in this paper. Then, the algorithm has been tested and compared to experimental results and it shows that, even if some drivers can drive the road quicker than the algorithm, they cannot drive with a lower fuel consumption. Furthermore, the algorithm results are better than the most of the experimental results according to the Pareto definition of dominance and global results outperform results from another planning algorithm based on Dijkstra’s algorithm. Future works will concentrate on improving the algorithm to be more reactive to unexpected obstacles and more consistant in the “chunks” transitions.
Our goal is to address the need for driver-state detection using wearable and in-vehicle sensor measurements of driver physiology and health. To address this goal, we deployed in-vehicle systems, wearable sensors, and procedures capable of quantifying real-world driving behavior and performance in at-risk drivers with insulin-dependent type 1 diabetes mellitus (DM). We applied these methodologies over 4 weeks of continuous observation to quantify differences in realworld driver behavior profiles associated with physiologic changes in drivers with DM (N=19) and without DM (N=14). Results showed that DM driver behavior changed as a function of glycemic state, particularly hypoglycemia. DM drivers often drive during at-risk physiologic states, possibly due to unawareness of impairment, which in turn may relate to blunted physiologic responses (measurable heart rate) to hypoglycemia after repeated episodes of hypoglycemia. We found that this DM driver cohort has an elevated risk of crashes and citations, which our results suggest is linked to the DM driver’s own momentary physiology. Overall, our findings demonstrate a clear link between at-risk driver physiology and real-world driving. By discovering key relationships between naturalistic driving and parameters of contemporaneous physiologic changes, like glucose control, this study directly advances the goal of driver-state detection through wearable physiologic sensors as well as efforts to develop “gold standard” metrics of driver safety and an individualized approach to driver health and wellness.
Model-based assessment methodology for social acceptance of Autonomous Driving Vehicle considering advantages and disadvantages is proposed. Basic framework of assessment methodology is introduced and the representative example of the assessment is discussed.
Variable Compression Systems for Internal Combustion Engines will become increasingly more important to meet stringent global fuel economy standards. A 2-Step VCS system is in development in cooperation of AVL and IWIS and the basic functionality was described in a technical paper, presented at the JSAE 20175333. The system is based on a hydraulically switched and locked conrod with telescopic shank. This paper discusses the main development results which have been obtained for the Proof of Concept and for the completion of the functional and design validation as well as the industrialisation concept with a modular production approach.
This study focuses on improving the acceptability of elderly drivers for proactive intervention systems using information sharing. Based on the observations of our previous studies, we modify the visual contents for avoiding information overload. To evaluate them, we conduct a driving simulator experiment that 12 elderly drivers participate in. The results confirm that the modified contents basically maintain or improve the evaluation of conveying the intended meanings, reducing disturbance, and improving feeling of trust without causing information overload. In addition, we also confirm a significant effectiveness of information sharing to improve the acceptability under the 5% significance level using the Wilcoxon signed-rank test.
Discharge of electric field generated by a spark plug is one of the most important and influential factors to determine combustion behavior of SI engines, as it initiates flame kernels by supplying energy to the air-fuel mixture. A discharge model is required to analyze this process with the help of numerical simulation. A new probabilistic discharge model has been developed, in which the probability of the breakdown is proportional to the intensity of the local electric field. A wide variety of discharges, such as air gap discharge, surface discharge and branching discharge like corona, can be calculated with the developed model. Consequently a detailed analysis of the process from discharge to combustion can be achieved.
Increasingly vehicle automation may convey greater capability than it actually possesses. The emergence of highly capable vehicle automation (e.g., SAE Level 4) and the promise of driverless vehicles in the near future can lead drivers to inappropriately cede responsibility for driving to the vehicle with less capable automation (e.g., SAE Level 2). This inappropriate reliance on automation can compromise safety, and so we investigated how algorithms and instructions might mitigate overreliance. Seventy-two drivers, balanced by gender, between the ages of 25 and 55, participated in this study using a fixed-base driving simulator. Drivers were exposed to one of three vehicle steering algorithms: lane centering, lane keeping, or an adaptive combination. A gaze tracker was used to track eye glance behavior. While automation was engaged, participants were told they could interact with an email sorting task on a tablet positioned near the center stack. Changes in roadway demand—traffic approaching in the adjacent lane—varied across the drive. Instructions indicating the driver was responsible, in combination with the adaptive algorithm, led drivers to be particularly attentive to the road as the traffic approached them. These results also have implications for evaluating more capable automation (SAE Levels 4 and 5), where drivers need not attend to the road: unnecessary attention to roadway demands might indicate lack of trust and acceptance of control algorithms that guide driverless vehicles.
Injection of fuel into the exhaust system is used to support the operation of exhaust gas aftertreatment systems. When injecting a fluid into the exhaust system, one major challenge is to design the exhaust system for optimal fuel distribution and to define an appropriate injection pressure. Simulation techniques are a suitable measure to support the corresponding development process. Hence, the project “Exhaust Fuel Injection” was initiated. Project target is the alignment of simulation methods and measurement techniques to predict the HC distribution in radial and axial direction at the inlet of a catalyst. This includes the definition of suitable measurement techniques to determine the hydrocarbon concentrations upstream of a catalyst. Transient 3D Computational Fluid Dynamics (CFD) simulation was used to model the fuel injection into a purpose-built exhaust system. The simulation results of the distribution of hydrocarbons at catalyst inlet in radial and axial direction are compared with measurements performed at an engine test bench. In total 18 variations were simulated and measured and twelve of them showed deviations in the uniformity index (UI) below 2 %. Only two variations resulted in deviations in UI above 3%. The trends in axial distribution showed good correlation between test bench and simulation. Especially the influence of injection pressure and operating point was predicted well by the simulation.
This paper proposes a novel data-centric framework for microscopic traffic flow simulation with intra and inter driver heterogeneity. We utilized a naturalistic driving corpus of 46 different drivers to learn and model the behavior divergence of Japanese drivers. First, ego-driver behavior signals are used to extract unique features of each driver with an auto-encoder. Then, using these features, drivers are divided into groups using unsupervised clustering algorithms. For each driver group, a feedforward neural network is trained for predicting the desired speed given the road topology. The trained network is then used in a microscopic traffic flow model for simulations. We used a macroscopic traffic survey conducted in Japan to evaluate the proposed framework. Our findings indicate that the proposed framework can simulate a realistic traffic flow with high driver heterogeneity.
Automotive manufacturers have developed a variety of countermeasures to optimize a vehicle’s performance under the Small Overlap Frontal Crash (SOFC) test. Generally, the SOFC test produces higher severity pulses and greater vehicle body intrusion than any other existing crash mode. Therefore, the primary focus of this research was to develop a system-level sled test methodology for the optimization of vehicle restraints, dummy kinematics and head protection through the analysis of primary control factors. For this study, a universal sled buck was specially designed to accept a variety of vehicle interior components and to adapt to varying vehicle packaging conditions.
This study examines a driver assistance system to prevent unnecessary deceleration at a signalized intersection. The assistance system presents the distance required to pass through signalized intersections without decelerating. The driving simulator experiments are carried out to evaluate the performance of the system. The system encourages the earlier deceleration and prevents the unnecessary deceleration. These effects contribute to reduce the fuel consumption. In addition, the assistance system shortens drivers’ reaction time to the emergency deceleration of the preceding vehicle in comparison with the conventional onboard monitor indication. This effect achieved the reduction of the collision risk to the preceding vehicle.
The objective of this study was to develop indices for detecting a driver’s state that consider the driver’s judgment process in various circumstances using a naturalistic driving behavior database. The deceleration timing when a driver approaches a non-signalized intersection was considered, and a deceleration strategy for the approach to an intersection was formulated based on a naturalistic driving behavior database compiled from the real world. A deviated state detection method that incorporates the formulated strategy is proposed, and the validity of the method was examined.
The e-4WD(electric four wheel drive) is the system that transfer powers to wheels and has an electric motor and reduction gear unit on a rear wheel axle. Durability test mode for e-4WD system is required. In this study, several types of sensors were equipped on the electric vehicle which has e-4WD system to measure not only vehicle behaviors and driving torques, but also driving condition. As a result of the analysis on vehicle behaviors in each driving condition, the e-4WD module operating durability mode which is optimized for new hybrid plaform’s dimension has been developed. System vibrational test method and revolutional test method for motor and reduction gear unit have also been developed. Moreover, the modeling that is available for developing accelerated durability test mode with only e-4WD Design parameters and driving condition has been studied.
With the increase of available computer performance, unsteady Computational Fluid Dynamics (CFD) is now widely used for industrial applications. For the analysis of unsteady vehicle aerodynamics, massive data storage is required for saving time series of spatially highly resolved flow fields. The size of these transient datasets can be significantly reduced using the Incremental Proper Orthogonal Decomposition (POD) by computing POD modes in parallel to the CFD. In this paper, we present a successful approximation of the transient flow field using a reduced number of modes computed by Incremental POD.
The automotive industry is showing high demand for efficient design of cooling systems in electric vehicles. The development of complex aero-thermodynamic systems requires reliable, high-fidelity simulations of high Reynolds number flows. We implemented a numerical solver based on the double-distribution lattice-Boltzmann method (LBM). The main advantage of the LBM, compared to the Navier-Stokes-based solvers, is its computational efficiency and intrinsic parallelism, which allows for execution on massively parallel architectures (GPUs). We have validated our GPU implementation by simulating a natural convection flow and a heated cylinder in an enclosed cavity. Both cases show very good agreement with published literature. In the future, we aim to extend the usage of the LBM framework to industry-relevant cases like the simulation of various packaging concepts for electric vehicles.