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A new index for evaluating load path dispersion is proposed, using a structural load path analysis method based on the concept of U* , which expresses the connection strength between a load point and an arbitrary point within the structure enables the evaluation of the load path dispersion within the structure by statistical means such as histograms and standard deviations. Presenter Tadashi Naito, Honda R&D Co., Ltd.

ISO 26262 is the actual standard for Functional Safety of automotive E/E (Electric/Electronic) systems. One of the challenges in the application of the standard is the distribution of safety related activities among the participants in the supply chain. In this paper, the concept of a Safety Element out of Context (SEooC) development will be analyzed showing its current problematic aspects and difficulties in implementing such an approach in a concrete typical automotive development flow with different participants (e.g. from OEM, tier 1 to semiconductor supplier) in the supply chain. The discussed aspects focus on the functional safety requirements of generic hardware and software development across the supply chain where the final integration of the developed element is not known at design time and therefore an assumption based mechanism shall be used.

The 31 papers in this technical paper collection cover topics such as steering system development, power steering systems, steer-by-wire systems, EPS, suspension systems, tires, and more.

The 30 papers in this technical paper collection focus on heavy tire modeling/testing and evaluation; vehicle dynamics; wide based tires, sustainability and maintenance; air suspension, off-road chassis and suspension; hybrid drive and chassis; all wheel/multi-wheel drive vehicle dynamics and performance; testing and experimental analysis of chassis and suspension; and advanced chassis control and rollover.

The 6 papers in this technical paper collection cover steering and suspension technologies. Topics include: twin level steering system; ride comfort improvement; small amplitude torsional steering column dynamics; HBMC (hydraulic body motion control system) for production vehicle application; and the development of hybrid EPS.

The 9 papers in this technical paper collection discuss steering and suspension technology. Topics covered include rear suspension design, composite material suspension arm, energy efficient hydraulic power assisted steering systems, and more. The 9 papers in this technical paper collection discuss steering and suspension technology. Topics covered include rear suspension design, composite material suspension arm, energy efficient hydraulic power assisted steering systems, and more.

This technical paper collection is focused on vehicle dynamics and controls using modeling and simulation, and experimental analysis of passenger cars, heavy trucks, and wheeled military vehicles. The papers address active and passive safety systems to mitigate rollover, yaw instability and braking issues; driving simulators and hardware-in-the-loop systems; suspension kinematics and compliance, steering dynamics, advanced active suspension technologies; and tire force and moment mechanics.

The 7 papers in this technical paper collection discuss new approaches as well as advances in application of steering and suspension related technologies.

The 19 Technical Papers in this collection address modeling, simulation, analysis, and control (MSA&C) of components, subsystems, and systems pertinent to aerospace power. This includes: tools and techniques, platforms, Mission and Campaign level MSA&C, and Verification and Validation of MSA&C.

This technical paper collection presents papers on steering and suspension related topics as it applies to ground vehicles. Papers for this session address new approaches as well as advances in application of steering, suspension related technologies.

This collection of technical papers focuses on state-of-the-art fatigue theory and advanced development in fatigue testing, material behavior under cyclic loading, and fatigue analysis methodology & research in the ground vehicle industry.

Papers with an emphasis on, but not limited to, innovative ideas to enhance automotive safety with improved material constitutive modeling, analysis method developments, simulation and pre/post processing tools, optimization techniques, crash code developments, finite element model updating, model validation and verification techniques, dummies and occupants, restraint systems, passive safety as well as lightweight material applications and designs are included in the collection.

The papers in this collection are to provide a forum for presentations on steering and suspension related topics as it applies to ground vehicles. Papers address new approaches as well as advances in application of steering, suspension related technologies.

Business Modeling/Operation Research/Big Data Analytics are key enablers for the next wave of innovation and growth across most industries and will address complex issues and systems that involve multiple objectives, alternatives, trade-offs, and large amounts of data and situations involving uncertainty or risk. These papers address new technical advances in these areas and provide valuable insights through the applications of real-world case studies.

Papers with an emphasis on, but not limited to, innovative ideas to enhance automotive safety with improved material constitutive modeling, analysis method developments, simulation and pre/post processing tools, optimization techniques, crash code developments, finite element model updating, model validation and verification techniques, dummies and occupants, restraint systems, passive safety as well as lightweight material applications and designs are included in the collection.

This technical paper collection provides information on steering and suspension related topics as it applies to ground vehicles. Papers address new approaches as well as advances in application of steering, suspension related technologies.

This technical paper collection discusses the modeling, analysis, and validation of commercial vehicle chassis, suspension, and tire modeling and simulation. Topics include commercial vehicle dynamics; chassis control devices such as ABS, traction control, yaw/roll stability control, and their interaction with suspension controls; modeling and simulation of ride comfort, as well as passive and active suspension control methodologies. Authors are encouraged to discuss the validation of their modeling and simulation.

Abstract Truck platooning comprises a number of trucks equipped with automated lateral and longitudinal vehicle control technology, which allows them to move in tight formation with short following distances. This study is an initial step toward developing an understanding of the occupant injury risks associated with the multiple sequential impacts between truck platoons and roadside safety barriers, regardless of whether the crash is associated with a malfunction of automated control or human operation. Full-scale crash impacts of a tractor-trailer platoon into a concrete bridge guardrail were simulated for a specific Test Level condition according to the Manual for Assessing Safety Hardware (MASH) standards. The model of the bridge barrier was developed based on its drawings, and material properties were assigned according to literature data.

Abstract A number of studies have shown that driving an unfamiliar vehicle has the potential to introduce additional risk, especially for novice drivers. However, such studies have generally used statistical methods based on analyzing crash and near-crash data from a range of driver groups, and therefore the evaluation has the potential to be subjective and limited. For a more objective perspective, this study suggests that it would be worthwhile to consider vehicle dynamic signals obtained from the Controller Area Network (CAN-Bus) and smartphones. This study, therefore, is focused on the effect of driver experience and vehicle familiarity for issues in driver modeling and distraction. Here, a group of 20 drivers participated in our experiment, with 13 of them having participated again after a one-year time lapse in order for analysis of their change in driving performance.

Abstract Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic flows. However, modeling driver’s lane-changing decision and implementation process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, this article presents a personalized Lane-Changing Model (LCM) for Advanced Driver Assistance System (ADAS) based on deep learning method. The LCM contains three major computational components. Firstly, with abundant inputs of Root Residual Network (Root-ResNet), LCM is able to exploit more local information from the front view video data. Secondly, the LCM has an ability of learning the global spatial-temporal information via Temporal Modeling Blocks (TMBs). Finally, a two-layer Long Short-Term Memory (LSTM) network is used to learn video contextual features combined with lane boundary based distance features in lane change events.