Virtual Vehicle

Owing to increased environmental demands to replace petroleum-derived materials with more environmentally friendly materials, research has been directed towards the potential of using wood in the automotive industry. This study extensively investigates the compressive strength ( f c ) of two hardwood species (beech and birch) with different anatomical directions, at various moisture and temperature levels, in an attempt to understand the wood’s behaviour during the forming process. The experimental tests were performed at 20, 100 and 140 °C on specimens with five moisture levels, ranging from completely dry to wet conditions. Overall, irrespective of the investigated direction, the measured compressive strength exhibited a clear exponential trend with increasing moisture content over the whole temperature range. This was capitalised on to present a simple predictive equation to roughly estimate the f c of beech and birch in different moisture and temperature conditions by relating to their dry f c at a reference temperature of 20 °C. The proposed approach was compared with other procedures and trends reported in the literature for the effect of moisture and temperature on the f c of wood. Furthermore, the reduction factors for the effect of temperature on the f c of softwoods, as set out in Eurocode 5 (EN 1995-1-2), were discussed in comparison with the present study findings. It was shown that, although the Eurocode approach is conservative, it may still be applicable for estimating the f c of hardwood species.

The objective of this study was to assess the biofidelity of the Global Human Body Models Consortium (GHBMC) 50th male (M50-O) v6.0 seated in an upright (25-degree recline) all-belts-to-seat (ABTS) in a 56 km/h rear-facing frontal impact. The experimental boundary conditions from the post-mortem human subjects (PMHS) tests were replicated in the computational finite element (FE) environment. The performance of the rigidized FE ABTS model obtained from the original equipment manufacturer was validated via simulations using a Hybrid III FE model and comparison with experiments. Biofidelity of the GHBMC M50-O was evaluated using the most updated NHTSA Biofidelity Ranking System (BRS) method, where a biofidelity score under 2 indicates that the GHBMC response varies from the mean PMHS response by less than two standard deviations, suggesting good biofidelity. The GHBMC M50-O received an occupant response score and a seat loading score of 1.71 and 1.44, respectively. Head (BRS = 0.93) and pelvis (BRS = 1.29) resultant accelerations, and T-spine (avg. BRS = 1.55) and pelvis (BRS = 1.66) y-angular velocities were similar to the PMHS. The T-spine resultant accelerations (avg. BRS = 1.93) and head (BRS = 2.82), T1 (BRS = 2.10) and pelvis (BRS = 2.10) Z-displacements were underestimated in the GHBMC. Peak chest deflection in the anterior-posterior deflection in the GHBMC matched with the PMHS mean, however, the relative upward motion of abdominal contents and subsequent chest expansion were not observed in the GHBMC. Updates to the GHBMC M50-O towards improved thorax kinematics and mobility of abdominal organs should be considered to replicate PMHS characteristics more closely.

While systems or products are becoming increasingly complex and new technologies emerge to manage this growing complexity, the potential of virtualized or simulation‐based product development is not yet fully exploited. This is mainly due to the fact that simulation results are still not trusted enough. Therefore, this paper outlines a possible approach to derive and ensure required levels of modeling and simulation credibility from the criticality of a simulation task. Furthermore, a framework is presented for assessing the implementation of a credible simulation process. This framework is based on an existing process reference model, ensuring modeling and simulation credibility, and on a process assessment model, which has proven itself in the German automotive industry in the assessment of process capability. Finally, the introduction to this framework is demonstrated using an example from the automotive domain, i.e., the simulation‐based safety approval for the virtual testing of an Automated Lane Keeping System.

Driver behaviour monitoring is a broad area of research, with a variety of methods and approaches. Distraction from the use of electronic devices, such as smartphones for texting or talking on the phone, is one of the leading causes of vehicle accidents. With the increasing number of sensors available in vehicles, there is an abundance of data available to monitor driver behaviour, but it has only been available to vehicle manufacturers and, to a limited extent, through proprietary solutions. Recently, research and practice have shifted the paradigm to the use of smartphones for driver monitoring and have fuelled efforts to support driving safety. This systematic review paper extends a preliminary, previously carried out author-centric literature review on smartphone-based driver monitoring approaches using snowballing search methods to illustrate the opportunities in using smartphones for driver distraction detection. Specifically, the paper reviews smartphone-based approaches to distracted driving behaviour detection, the smartphone sensors and detection methods applied, and the results obtained.

Automated vehicles and vehicle-to-everything (V2X) communication open the window for sharing of sensor data. This paper aims to provide a systematic view of the delay chain involved. We implemented collective perception (CP) into two street legal automated driving demonstrators (ADDs) to provide insight into the components’ delay. The implementation allowed us to gather highly accurate Quality of Service (QoS) measurements for V2X communication in practical field environments and to gather a set of delay measurements for a working CP system, accompanied by scalability discussions. The results provide a basis for evaluating the delay impact of single components and the applicability of CP use cases from the perspective of time advantage.

The railway industry uses top-of-rail products to control and manage the friction in the wheel/rail interface to help ensure efficient train operations and reduce wheel and rail damage. A product is typically applied from a wayside applicator that pumps a puddle onto the rail head where a passing wheel will pick it up and then transfer it down the track. The aim of this study was to study the transfer mechanisms of water-based top-of-rail friction modifiers (TOR-FMs) and how they are linked to the friction conditions in the wheel/rail interface. The transfer mechanisms were split into three parts: pick-up, carry-on and consumption. Pick-up looks at how the product transfers from the puddle on the rail to a wheel tread, whereas the carry-on mechanism relates to the product transfer back to the wheel. Consumption focuses on the removal rate of the product layer from the wheel or rail. A full-scale rig and twin disc machine were chosen to perform the tests because each rig could give different insights into understanding the product transfer mechanisms. Two products were tested of similar formulation. Results show that there are differences in the transfer and friction between the two products despite them being relatively similar. The test methods developed can clearly resolve differences between varying product types, which could be useful for product development studies or approvals work. The outcomes could also be used to develop a model of transfer/consumption.

A new dataset for automated driving, which is the subject matter of this paper, identifies and addresses a gap in existing similar perception datasets. While most state-of-the-art perception datasets primarily focus on the provision of various onboard sensor measurements along with the semantic information under various driving conditions, the provided information is often insufficient since the object list and position data provided include unknown and time-varying errors. The current paper and the associated dataset describe the first publicly available perception measurement data that include not only the onboard sensor information from the camera, Lidar, and radar with semantically classified objects but also the high-precision ground-truth position measurements enabled by the accurate RTK-assisted GPS localization systems available on both the ego vehicle and the dynamic target objects. This paper provides insight on the capturing of the data, explicitly explaining the metadata structure and the content, as well as the potential application examples where it has been, and can potentially be, applied and implemented in relation to automated driving and environmental perception systems development, testing, and validation.

Objective: In 2020, 17% of all crash fatalities were individuals aged 65 years or older. Crash data also revealed that for older occupants, thoracic related injuries are among the leading causes of fatality. Historically, the majority of near-side impact postmortem human subjects (PMHS) studies used a generic load wall to capture external loads that were applied to PMHS. While these data were helpful in documenting biofidelity, they did not represent a realistic response an occupant would undergo in a near-side crash. The objective of this research was to test small, elderly female PMHS in a repeatable, realistic near-side impact crash scenario to investigate current injury criteria as they relate to this vulnerable population. Method: Ten small, elderly PMHS were subjected to a realistic near-side impact loading condition. The PMHS were targeted to be elderly females age 60+, approximately 5th percentile in height and weight, with osteopenic areal bone mineral density. Each subject was seated on a mass-production seat, equipped with a side airbag and standard three-point restraint with a pretensioner. Other boundary conditions included an intruding driver's side door. PMHS instrumentation included strain gages on ribs 3-10 bilaterally to identify fracture timing. Two chestbands were used to measure chest deflection, one at the level of the axilla and one at the level of the xiphoid process. Results: Injuries observed included rib fractures, particularly on the struck side, and in multiple cases a flail chest was observed. Eight of ten subjects resulted in AIS3+ thoracic injuries, despite previously tested ATDs predicting less than a 10% chance of AIS3+ injury. Subjects crossed the threshold for AIS3 injury in the range of only 1% - 9% chest compression. Additionally, mechanisms of injury varied, as some injuries were incurred by door interactions while others came during airbag interactions. Conclusions: This research points to two areas of concern that likely require further analysis: (1) the appropriateness of potentially oversimplified PMHS testing to establish injury thresholds and define injury criteria for complicated crash scenarios; (2) the importance of identifying the precise timing of injuries to better understand the effect of current passive restraint systems.

Objective: One potential nonstandard seating configuration for vehicles with automated driving systems (ADS) is a reclined seat that is rear-facing when in a frontal collision. There are limited biomechanical response and injury data for this seating configuration during high-speed collisions. The main objective of this study was to investigate thoracic biomechanical responses and injuries to male postmortem human subjects (PMHS) in a rear-facing scenario with varying boundary conditions.Method: Fourteen rear-facing male PMHS tests (10 previously published and 4 newly tested) were conducted at two different recline angles (25-degree and 45-degree) in 56 km/h frontal impacts. PMHS were seated in two different seats; one used a Fixed D-Ring (FDR) seat belt assembly and one used an All Belts To Seat (ABTS) restraint. For thoracic instrumentation, strain gages were attached to ribs to quantify strain and fracture timing. A chestband was installed at the mid-sternum level to quantify anterior-posterior (AP) chest deflections. Data from the thorax instrumentation were analyzed to investigate injury mechanisms.Results: The PMHS sustained a greater number of rib fractures (NRF) in the 45-degree recline condition (12 ± 7 NRF for ABTS45 and 25 ± 18 NRF for FDR45) than the 25-degree condition (6 ± 4 NRF for ABTS25 and 12 ± 8 NRF for FDR25), despite AP chest compressions in the 45-degree condition (-23.7 ± 9.4 mm for ABTS45 and -39.6 ± 11.9 mm for FDR45) being smaller than the 25-degree condition (-38.9 ± 16.9 mm for ABTS25 and -55.0 ± 4.4 mm for FDR25). The rib fractures from the ABTS condition were not as symmetric as the FDR condition in the 25-degree recline angle due to a belt retractor structure located at one side of the seatback frame. Average peak AP chest compression occurred at 45.7 ± 3.4 ms for ABTS45, 45.6 ± 3.1 ms for FDR45, 46.7 ± 1.9 ms for ABTS25, and 46.9 ± 2.3 ms for FDR25. Average peak seatback resultant force occurred at 43.9 ± 0.9 ms for ABTS45, 44.6 ± 0.8 ms for FDR45, 42.5 ± 0.2 ms for ABTS25, and 41.5 ± 0.5 ms for FDR25. The majority of rib fractures occurred after peak AP chest compression and peak seatback resultant force likely due to the ramping motion of the PMHS, which might create a combined loading (e.g., AP deflection and upward deflection) to the thorax. Although NRF in the 45-degree reclined condition was greater than the 25-degree recline condition, similar magnitudes of rib strains were observed regardless of seat and restraint types, while strain modes varied.Conclusions: The majority of rib fractures occurred after peak AP chest compression and peak seatback force, especially in FDR25, ABTS45, and FDR45, while the PMHS ramped up along the seatback. AP chest compression, seatback load, and strain measured along the rib could not explain the greater NRF in the 45-degree recline conditions. A complex combination of AP chest deflection with upward deflection was discovered as a possible mechanism for rib fractures in PMHS subjected to rear-facing frontal impacts in this study.

Objective: The objective of this study was the quantitative evaluation and comparison of the responses of the Hybrid III 5th percentile female (HIII-05F) and the 5th percentile female Test Device for Human Occupant Restraint (THOR-05F) anthropomorphic test devices (ATDs) subjected to abdominal loading conditions. Method: The HIII-05F and THOR-05F were subjected to 3 different abdominal loading conditions: fixed-back belt pull (low compression), fixed-back belt pull (high compression), and free-back rigid bar impact at 6 m/s. The stroke of the impact was controlled to represent injurious and noninjurious loading conditions as observed in the experiments with postmortem human subjects (PMHS). Quantitative comparisons were made between the ATD abdominal force and compression responses and biofidelity corridors obtained from matched-pair PMHS tests under identical loading conditions, using the most recent version of the NHTSA Biofidelity Ranking System (BRS). Results: The overall THOR-05F BRS scores across all tests (BRS score = 1.84) indicated good biofidelity. For the belt loading test conditions, the average BRS scores for both THOR-05F (BRS scores = 1.45 and 1.34) and HIII-05F (BRS scores = 1.42 and 1.01) showed good biofidelity. For the rigid bar loading condition, the THOR-05F (BRS score = 2.74) showed better biofidelity compared to HIII-05F (BRS score = 10.63), with the HIII-05F exhibiting poor performance in this condition. The average pressures recorded by the abdomen pressure twin sensors (APTS) in the current study ranged from 45 to 130 kPa, increasing proportionally with higher stroke and loading rate. Conclusions: Overall, the THOR-05F BRS scores were better than the HIII-05F BRS scores, which suggests improved biofidelity of the THOR-05F abdomen. The abdominal insert in the HIII-05F did not provide enough room for compression, leading to higher stiffness and occupant motion as observed in the rigid bar tests. Because of practical challenges in measuring abdomen deflection in a soft ATD abdomen component, use of APTS in THOR-05F provides the ability to measure the restraint loading to the abdomen and assess the risk of abdominal injury. With good BRS scores observed in this study for THOR-05F, pressure and other measurements included in the THOR-05F may be used to develop abdominal injury risk functions in the future.

When a tribological system is operated for the first time, the first hours of operation are of the utmost importance as the surfaces of the contacting elements mate to each other, involving significant wear processes until the surfaces reach stable topological characteristics. This initial phase in a combustion engine is known as running-in and is of critical importance in the study of friction and wear phenomena. Despite this, there is little information in the literature dedicated to running-in and, therefore, data improving its understanding is greatly anticipated. In this work, a novel wear debris detection system measuring in real time was employed to investigate the running-in of an inline 4-cylinder gasoline engine; it consists primarily of an optical sensor with the capability of detecting very small particles from 4 μm. For the tests, the engine was mounted on a test bench and operated under stationary working conditions. The results of the wear debris measurements showed interesting insights into the engine running-in process; although in general, the results followed the expected trend, they also showed an unexpected behavior: it was expected to obtain the highest amounts of wear debris at the beginning of the running-in, but instead the number of debris stagnated and only started to increase after about 20 h to then decrease again. The best operating conditions to run-in the engine were identified at the middle of the running-in period, without the presence of large wear debris that could lead to severe wear. Finally, it was found that the engine running-in was not finished until at least 75 h of operation, although commonly, a running-in time of 10 h is used in the industry.

Fuel cell powertrains have higher efficiencies compared to internal combustion engine powertrains, but—despite lower thermal losses—thermal requirements are noticeably higher. The commonly used Polymer Electrolyte Membrane Fuel Cell is highly sensitive to temperature deviations; hence specifications of coolant temperatures must be strictly observed. Furthermore, their working-temperature level is closer to ambient air, requiring a more efficient cooling system. This work focuses on medium-duty and heavy-duty truck segments. The aim is to provide a possible optimization guideline for cooling system developers to select an adequate heat exchanger for available air mass flows. This energetical and thermal layout process is based on fuel cell module information provided by Plastic Omnium New Energies Wels GmbH, firstly by simple steady-state calculations and secondly by transient vehicle system simulations. To define the system to the full extent, the analyses cover full-load operation, VECTO cycles, real-driving cycles, and the highest ambient temperatures. Finally, an optimized system is presented, matching the best trade-off between heat exchanger size and mass flows. Results show a linear and then exponential increase in heat exchanger size with soaring thermal requirements. Thus, with a well-defined thermal layout validated on the full vehicle level, the lowest possible component sizes are identified at which still harshest mission profiles can be completed.

The main objective of this article is to provide angle-dependent spectral reflectance measurements of various materials in the near infrared spectrum. In contrast to already existing reflectance libraries, e.g., NASA ECOSTRESS and Aster reflectance libraries, which consider only perpendicular reflectance measurements, the presented dataset includes angular resolution of the material reflectance. To conduct the angle-dependent spectral reflectance material measurements, a new measurement device based on a 945 nm time-of-flight camera is used, which was calibrated using Lambertian targets with defined reflectance values at 10, 50, and 95%. The spectral reflectance material measurements are taken for an angle range of 0° to 80° with 10° incremental steps and stored in table format. The developed dataset is categorized with a novel material classification, divided into four different levels of detail considering material properties and distinguishing predominantly between mutually exclusive material classes (level 1) and material types (level 2). The dataset is published open access on the open repository Zenodo with record number 7467552 and version 1.0.1 [1]. Currently, the dataset contains 283 measurements and is continuously extended in new versions on Zenodo.

In railway operation, the sanding process is used to overcome low adhesion conditions in the wheel–rail contact. In the literature, previously conducted research has been experimental, e.g., measuring adhesion coefficients (ACs) under different contact conditions (dry, wet, …) or applying different sands. Under dry conditions, sanding can reduce measured ACs, while under wet conditions different types of rail sand can leave ACs unchanged or increase adhesion. Despite active research, the physical mechanisms causing the change in ACs under sanded conditions are still poorly understood. A possible remedy is the development of advanced models of sanding including local effects. As a basis for such a model, this study presents experimental results concerning single grain crushing behaviour of two types of rail sand under dry and wet contact conditions. Firstly, initial breakage behaviour is investigated with focus on the particle fragments’ size and spread as only fragments within the running band are available to influence the AC during roll-over. Secondly, single grain crushing tests are conducted under realistic wheel–rail load showing the formation of solidified clusters of sand fragments, as well as their size and thickness. This information is important for understanding mechanisms and for future physics-based modelling of the sanding process in wheel–rail contacts.

Detailed investigations of white etching layers (WELs) formed on rails and wheels are of utmost importance to improve railway safety. This calls for lab-generated WELs with well-comparable characteristics to conduct further testing such as in twin-disc experiments. In this work, laser surface treatments were applied on wheel steels to induce thermally induced WELs. To evaluate the influence of the initial deformation state of the sample, undeformed and severely plastically deformed ER7 wheel steels were selected. In this study, it is shown that surface temperatures of > 640 °C lead to thermally induced WELs, with differences based on the initial deformation state. The thermally induced WELs are compared to a field-WEL present on an ex-service railway wheel. Results indicate that the WEL induced by laser treatment on an initially deformed wheel material provides the best match with the field-WEL. The most distinct difference is a grain size gradient within the outermost 30 µm of the field-WEL caused by deformation after the formation in service. This study clearly shows that the variation in initial microstructures and laser process parameters leads to differences in microstructural characteristics of thermally induced WELs and must be considered when imitating and testing WELs in laboratories.

Automated Vehicles aim to increase road safety as automated driving systems (ADS) take over the human driving task in the operational design domain (ODD), introducing severe challenges for safety validation. Pure driving over many kilometres to gather enough evidence for a safety argument is not feasible. Scenario-based testing is an approach to overcome this, but challenges like parameter discretisation still prevail, hindering safety assurance. This work proposes contributions towards a traceable and efficient safety argumentation for ADS built upon ODD coverage. First, ODD coverage is thoroughly quantified across all scenario levels, assuming distribution functions’ availability for the scenario parameters. Secondly, a sampling method for n-dimensional scenario parameter distributions is proposed. The provided algorithms adapt an initial k-means clustering using pre-defined boundary conditions requiring significantly fewer scenarios. Furthermore, a risk metric for urban intersections is presented for scenario evaluation. The risk metric consists of two parts, scene prediction of traffic participants (TPs) and risk assessment. The scene prediction uses a manoeuvre-based motion model with a data-driven approach towards trajectory prediction, increasing the validity. For the risk assessment, a probabilistic risk prediction for the TPs is performed for each scenario scene. The risk metric shows a reasonable tradeoff between sensitivity and specificity, outperforming time-to-collision. These contributions are exemplarily applied at an intersection using a simplified setup for generating TPs and ego vehicle trajectories. The results indicate that an increased safety argumentation is enabled using the proposed methods alongside a coverage process, facilitating further research.

New advanced driver assistance system/automated driving (ADAS/AD) functions have the potential to significantly enhance the safety of vehicle passengers and road users, while also enabling new transportation applications and potentially reducing CO2 emissions. To achieve the next level of driving automation, i.e. SAE Level-3, physical test drives need to be supplemented by simulations in virtual test environments. A major challenge for today’s virtual test environments is to provide a realistic representation of the vehicle’s perception system (camera, lidar, radar). Therefore, new and improved sensor models are required to perform representative virtual tests that can supplement physical test drives. In this article, we present a computationally efficient, mathematically complete, and geometrically exact generic sensor modeling approach that solves the FOV (field of view) and occlusion task. We also discuss potential extensions, such as bounding-box cropping and sensor-specific, weather-dependent FOV-reduction approaches for camera, lidar, and radar. The performance of the new modeling approach is demonstrated using camera measurements from a test campaign conducted in Hungary in 2020 plus three artificial scenarios (a multi-target scenario with an adjacent truck occluding other road users and two traffic jam situations in which the ego vehicle is either a car or a truck). These scenarios are benchmarked against existing sensor modeling approaches that only exclude objects that are outside the sensor’s maximum detection range or angle. The modeling approach presented can be used as is or provide the basis for a more complex sensor model, as it reduces the number of potentially detectable targets and therefore improves the performance of subsequent simulation steps.

A difficult challenge for today’s driver monitoring systems is the detection of cognitive distraction. The present research presents the development of a theory-driven approach for cognitive distraction detection during manual driving based on temporal control theories. It is based solely on changes in the temporal variance of driving-relevant gaze behavior, such as gazes onto the dashboard (TDGV). Validation of the detection method happened in a field and in a simulator study by letting participants drive, alternating with and without a secondary task inducing external cognitive distraction (auditory continuous performance task). The general accuracy of the distraction detection method varies between 68% and 81% based on the quality of an individual prerecorded baseline measurement. As a theory-driven system, it represents not only a step towards a sophisticated cognitive distraction detection method, but also explains that changes in temporal dashboard gaze variance (TDGV) are a useful behavioral indicator for detecting cognitive distraction.