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Abstract Introduction: This study evaluates driving ability in those with Charcot Marie Tooth Disease Type 1A, a hereditary peripheral neuropathy. Methods: Individuals with Charcot Marie Tooth Disease Type 1A (n = 18, age = 42 ± 7) and controls (n = 19; age = 35 ± 10) were evaluated in a driving simulator. The Charcot Marie Tooth Neuropathy Score version 2 was obtained for individuals. Rank Sum test and Spearman rank correlations were used for statistical analysis. Results: A 74% higher rate of lane departures and an 89% higher rate of lane deviations were seen in those with Charcot Marie Tooth Disease Type 1A than for controls (p = 0.005 and p < 0.001, respectively). Lane control variability was 10% higher for the individual group and correlated with the neuropathy score (rS = 0.518, p = 0.040), specifically sensory loss (rS = 0.710, p = 0.002) and pinprick sensation loss in the leg (rS = 0.490, p = 0.054).

Abstract The vehicle attributes developed for emerging markets like India are unique because of different topographical conditions, diversity and culture within the different states. Major attributes in vehicle development process is development of safe and sustainable vehicle systems (steering, brakes etc.) for the driver. India is presently an emerging market for automotive sector. With booming economy, purchasing power of the consumer has gone up in the past few years. Most of young population of India have started buying the cars. At the same time, India’s road infrastructure, vehicle regulations have exalted over the years. The consumer cognizance towards the vehicles have started changing now. They want safer, robust system in their vehicles with new convenience features at affordable cost. In recent years, almost all OEM’s in India have migrated steering systems from HPAS to EPAS for payback on fuel economy and weight.

Abstract The transient surface pressure over a full-scale, operational compact automotive vehicle—a Volkswagen Golf 7—exposed to transient crosswinds with relative yaw angles of β = 22-45° has been characterized. Experiments were performed at the BMW side-wind facility in Aschheim, Germany. Measurements of the incoming flow in front of the car were taken with eleven five-hole dynamic pressure probes, and separately, time-resolved surface pressure measurements at 188 locations were performed. Unsteady characteristics (not able to be identified in quasi-steady modelling) have been identified: the flow in separated regions on the vehicle’s leeward side takes longer to develop than at the windward side, and spatially, the vehicle experiences local crosswind as it gradually enters the crosswind.

Abstract Estimating the power demand of a steering system is one of the main tasks during steering system development in the concept phase of a vehicle development process. Most critical for typical axle kinematics are parking maneuvers with simultaneously high rack forces and velocities. Therefore, the focus of the article is a tire model for standstill, which can be parametrized without measurements, only having tire dimensions and conditions (inflation pressure and wheel load) as input. Combined with a double-track model, a vehicle model is developed, which is able to predict the rack force and is fully applicable during the concept phase. The article demonstrates quantitatively that the tie rod forces, and thereby especially the tire bore torque, cause the largest fraction of the power demand at the rack. For this reason, the prediction of the bore torque is investigated in detail, whereby basic approaches from the literature are analyzed and enhanced.

Abstract Rolling-resistance is leading the direction of numerous tire developments due to its significant effect on fuel consumption and CO2 emissions considering the vehicles in use globally. Many attempts were made to reduce rolling-resistance in vehicles, but with no or limited success due to tire complexity and trade-offs. This article investigates the concept of multiple chambers inside the tire as a potential alternative solution for reducing rolling-resistance. To accomplish that, novel multi-chamber designs were introduced and numerically simulated through finite-element (FE) modeling. The FE models were compared against a standard design as the baseline. The influences on rolling-resistance, grip, cornering, and mechanical comfort were studied. The multi-chambers tire model reduced rolling-resistance considerably with acceptable trade-offs. Independent air volumes isolating tread from sidewalls would maintain tire’s profile effectively.

Abstract With increased consumer demand for fuel efficient vehicles as well as more stringent greenhouse gas regulations and/or Corporate Average Fuel Economy (CAFE) standards from governments around the globe, the automotive industry, including the OEM (Original Equipment Manufacturers) and suppliers, is working diligently to innovate in all areas of vehicle design. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, mass reduction has been identified as an important strategy in future vehicle development. In this article, the development, analysis, and experiment of multi-cornered structures are presented. To achieve mass reduction, two non-traditional multi-cornered structures, with twelve- and sixteen-cornered cross-sections, were developed separately by using computer simulations.

Abstract A two-dimensional model of three elements, high-lift airfoil, was designed at a Reynolds number of ?????? using computational fluid dynamics (CFD) to generate downforce with good lift-to-drag efficiency for a formula student open-wheel race car basing on the nominal track speeds. The numerical solver uses the Reynolds-averaged Navier-Stokes (RANS) equation model coupled with the Langtry-Menter four-equation transition shear stress transport (SST) turbulence model. Such model adds two further equations to the ?? − ?? SST model resulting in an accurate prediction for the amount of flow separation due to adverse pressure gradient in low Reynolds number flow. The ?? − ?? SST model includes the transport effects into the eddy-viscosity formulation, whereas the two equations of transition momentum thickness Reynolds number and intermittency should further consider transition effects at low Reynolds number.

Abstract Within the scope of today’s product development in automotive engineering, the aim is to produce lighter and solid parts with higher capabilities. On the one hand lightweight materials such as aluminum or magnesium are used, but on the other hand, increased stresses on these components cause higher bolt forces in joining technology. Therefore screws with very high strength rise in importance. At the same time, users need reliable and effective design methods to develop new products at reasonable cost in short time. The bolted joints require a special structural design of the thread engagement in low-strength components. Hence an extension of existing dimensioning of the thread engagement for modern requirements is necessary. In the context of this contribution, this will be addressed in two ways: on one hand extreme situations (low strength nut components and high-strength fasteners) are considered.

Abstract Today’s explosive condition of the market is compelling the manufacturing organizations to switch from traditional manufacturing (TM) to lean manufacturing (LM) to create a footprint in this competitive era. In this article, 16 critical success factors (CSFs) for LM implementation are identified through a vast literature review, the opinion of academicians and industry experts and interpretive structural modeling (ISM) is used to create interrelationships among the identified CSFs, and interpretive ranking process (IRP) rank these CSFs based on dominance with respect to performance dimensions. Leadership and management made the foundation of an ISM model while the training and people development have secured the first rank in the IRP model. Implementation of such ISM- and IRP-based models of CSF would give a clear understanding of these CSFs so that LM researchers, decision-makers, managers, and practitioners of LM will use their resources more efficiently.

Abstract In this article, a hierarchical coordinated control algorithm for integrating active rear steering and driving/braking force distribution (ARS+D/BFD) was presented. The upper-level control was synthesized to generate the required rear steering angle and external yaw moment by using a sliding-mode controller. In the lower-level controller, a control allocation algorithm considering driving/braking actuators and tire forces constraints was designed to assign the desired yaw moment to the four wheels. To this end, an optimization problem including several equality and inequality constraints were defined and solved analytically. Finally, computer simulation results suggest that the proposed hierarchical control scheme was able to help to achieve substantial enhancements in handling performance and stability.

Abstract This article presents the application of the Enhanced Sequence Diagram (ESD) for the analysis of the functionality of a system with shape-changing aspects in the context of its multiple operational modes, considering an active real spoiler as a case study. The article provides new insights on the ESD support for model-based capture and articulation of functional requirements across multiple operation modes of the same system, with appropriate detail on attributes and metrics, and the alignment of these attributes and metrics in line with the concept of time through scope lines. The article also provides a comprehensive argument and discussion, exemplified based on the case study, for the support that the ESD provides for early systems functional and architecture analysis, within the context of a broader model-based Failure Mode Analysis methodology.

Abstract The ability of senior citizens as well as other members of the general population to engage in an effective manner with technology is of increasing importance as new and innovative technologies become available. While recognizing the challenges that technologies can have on different populations, the ability to interact successfully with new technologies will, for seniors, have important consequences that can affect their quality of life and those of their families in numerous and important ways. This study, building upon previous research, examines the major dimensions of decision-making regarding attitudes toward autonomous vehicle technologies (ATVs) and their use. The study utilized data from a study of senior citizens in the Dallas-Fort Worth (DFW) area and compared the results with a sample of graduate students from a local university.

Abstract Geometric variation stemming from manufacturing can be a limiting factor for the quality and reliability of products. Therefore, manufacturing assessments are increasingly being performed during the early stages of product development. In the aerospace industry, products are complex engineering systems, the development of which require multidisciplinary expertise. In such contexts, there are significant barriers against assessing the effects of geometric variation on the functionality of products. To overcome these barriers, this article introduces a new methodology consisting of a modelling approach linked to a multidisciplinary simulation environment. The modelling approach is based on the parametric point method, which allows point-scanned data to be transferred to parameterised CAD models. In a case study, the methodology is implemented in an industrial setting.

Abstract A new method that allows data-enabled (empirical) models, commonly used for automotive engine calibration, to extrapolate beyond the range of training data has been developed. This method used a physics-based system-level one-dimensional model to improve interpolation and allow extrapolation for three data-based algorithms, by modifying the model input (feature) space. Neural network, regression, and k-nearest neighbor predictions of engine emissions and volumetric efficiency were greatly improved by generating 736,281 artificial feature spaces and then performing feature selection to choose feature spaces (feature selection) so that extrapolations in the original feature space were interpolations in the new feature space. A novel feature selection method was developed that used a two-stage search process to uniquely select the best feature spaces for every prediction.

Abstract The Formula SAE (FSAE) is an international engineering competition where a Formula style race car is designed and built by students from worldwide universities. According to FSAE regulation, an air restrictor with circular cross section of 20 mm for gasoline-fuelled and 19 mm for E-85-fuelled vehicles is to be incorporated between the throttle valve and engine inlet. The sole purpose of this regulation is to limit the airflow to the engine used. The only sequence allowed is throttle valve, restrictor and engine inlet. A new approach of combining ram theory and acoustic theory methods are investigated to increase the performance of the engine by designing an optimized intake runner for a particular engine speed range and an optimized plenum volume in this range. Engine performance characteristics such as brake power, brake torque and volumetric efficiency are taken into considerations.

Abstract Identifying and eliminating failure scenarios is critical in the development of autonomous vehicle (AV) systems. However, finding such failures through real-world vehicle-level testing is a difficult task as system disengagements and accidents are rare occurrences. Simulation approaches have been proposed to supplement vehicle-level testing and reduce the costs associated with operating large fleets of autonomous test vehicles. While one can run more vehicles in simulation than in the real world, applying traditional Monte Carlo sampling techniques to find failures still yields an unguided search and a large waste of computing resources. A more directed method than random sampling is needed to identify failure scenarios in a computationally efficient manner. Adaptive Stress Testing (AST) is a method that uses reinforcement learning (RL) paradigms to efficiently find failure scenarios in stochastic sequential decision-making systems.

Abstract Autonomous vehicles (AVs) are being rapidly introduced into our lives. However, public misunderstanding and mistrust have become prominent issues hindering the acceptance of these driverless technologies. The primary objective of this study is to evaluate the effectiveness of a driving simulator to help the public gain an understanding of AVs and build trust in them. To achieve this aim, we built an integrated simulation platform, designed various driving scenarios, and recruited 28 participants for the experiment. The study results indicate that a driving simulator effectively decreases the participants’ perceived risk of AVs and increases perceived usefulness. The proposed methodologies and findings of this study can be further explored by auto manufacturers and policymakers to provide user-friendly AV design.

Abstract Connected and automated vehicles (CAVs) can bring safety, mobility, and energy benefits to transportation systems. Ideally, CAV applications would be fully evaluated and validated prior to real-world implementation. However, many technical challenges in both software and hardware hinder the process. To comprehensively evaluate all aspects of CAV applications, an integrated evaluation environment is needed with various simulation tools from different domains. In the current literature, there lacks a well-developed interface to enable multi-resolution simulation of vehicle, traffic, virtual environment, and hardware-in-the-loop (HIL) simulation. In this work, a modular and flexible interface is developed to enable multi-resolution vehicle and traffic co-simulation for CAV applications.

Abstract Contemporary research has found differences between demographic groups in their stated instrument cluster component design preferences. For instance, elderly drivers prefer large icons and textual displays of information, while younger drivers preferred gauges to display information. The purpose of this study was to evaluate whether instrument clusters, designed for specific demographic groups, would facilitate safe driving behavior and solicit higher evaluation scores in their targeted demographics. Fifty participants, consisting of 30 elderly and 20 younger drivers (gender-balanced), completed a series of tasks to retrieve information from the instrument cluster while driving a high-fidelity simulator. Participants’ driving behavior, response time, subjective ratings, and a semi-structured post-experimental interview on different cluster designs were collected to evaluate each instrument cluster design.

Abstract This article presents data mining methodologies designed to support data-driven, long-term, and large-scale research in the areas of in-vehicle monitoring, learning, and assessment of older adults’ driving behavior and physiological signatures under a set of well-defined driving scenarios. The major components presented in the article include the instrumentation of an easily transportable vehicle data acquisition system (VDAS) designed to collect multimodal sensor data during naturalistic driving, an ontology that enables the study of driver behaviors at different levels of integration of semantic heterogeneity into the driving context, and a driving trip segmentation algorithm for automatically partitioning a recorded real-world driving trip into segments representing different types of roadways and traffic conditions.