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Take notes! Take the wheel! There is no better place to gain an appreciation for vehicle dynamics than from the driver’s seat. Spend three, intense days with a world-renowned vehicle dynamics engineer and SAE Master Instructor, his team of experienced industry engineers, and the BMW-trained professional driving instructors. They will guide you as you work your way through 12 classroom modules learning how and why vehicles go, stop and turn. Each classroom module is immediately followed by an engaging driving exercise on BMW’s private test track.

Active safety and (ADAS) are now being introduced to the marketplace as they serve as key enablers for anticipated autonomous driving systems. Automatic emergency braking (AEB) is one ADAS application which is either in the marketplace presently or under development as nearly all automakers have pledged to offer this technology by the year 2022. This one-day course is designed to provide an overview of the typical ADAS AEB system from multiple perspectives.

Vehicle functional requirements, emission regulations, and thermal limits all have a direct impact on the design of a powertrain cooling airflow system. Given the expected increase in emission-related heat rejection, suppliers and vehicle manufacturers must work together as partners in the design, selection, and packaging of cooling system components. The goal of this two-day course is to introduce engineers and managers to the basic principles of cooling airflow systems for commercial and off-road vehicles.

Photographs and video recordings of vehicle crashes and accident sites are more prevalent than ever, with dash mounted cameras, surveillance footage, and personal cell phones now ubiquitous. The information contained in these pictures and videos provide critical information to understanding how crashes occurred, and  analyze physical evidence. This course teaches the theory and techniques for getting the most out of digital media, including correctly processing raw video and photographs, correcting for lens distortion, and using photogrammetric techniques to convert the information in digital media to usable scaled three-dimensional data.

Convolutional neural networks are the de facto method of processing camera, radar, and lidar data for use in perception in ADAS and L4 vehicles, yet their operation is a black box to many engineers. Unlike traditional rules-based approaches to coding intelligent systems, networks are trained and the internal structure created during the training process is too complex to be understood by humans, yet in operation networks are able to classify objects of interest at error rates better than rates achieved by humans viewing the same input data.

This course is verified by Probitas Authentication as meeting the AS9104/3A requirements for continuing Professional Development. In the Aerospace Industry there is a focus on Defect Prevention to ensure that quality goals are met. Failure Mode and Effects Analysis (PFMEA) and Control Plan activities are recognized as being one of the most effective, on the journey to Zero Defects. This two-day course is designed to explain the core tools of Design Failure Mode and Effects Analysis (DFMEA), Process Flow Diagrams, Process Failure Mode and Effects Analysis (PFMEA) and Control Plans as described in AS13100 and RM13004.

In the evolving landscape of automated driving systems, the critical role of vehicle localization within the autonomous driving stack is increasingly evident. Traditional reliance on Global Navigation Satellite Systems (GNSS) proves to be inadequate, especially in urban areas where signal obstruction and multipath effects degrade accuracy. Addressing this challenge, this paper details the enhancement of a localization system for autonomous public transport vehicles, focusing on mitigating GNSS errors through the integration of a LiDAR sensor. The approach involves creating a 3D map using the factor graph-based LIO-SAM algorithm based on GNSS, vehicle odometry, IMU and LiDAR data. The algorithm is adapted to the use-case by adding a velocity factor and altitude data from a Digital Terrain model. Based on the map a state estimator is proposed, which combines high-frequency LiDAR odometry based on FAST-LIO with low-frequency absolute multiscale ICP-based LiDAR position estimation.

The global time that is propagated and synchronized in the vehicle E/E architecture is used in safety-critical, security-critical, and time-critical applications (e.g., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384. These failures reduce the vehicle availability, robustness, and safety of the road user. IEEE 1588 lists four mechanisms (integrated security mechanism, external security mechanism, architectural solution, and monitoring & management) to secure the global time. AUTOSAR defines the architecture and detailed specifications for the integrated security mechanism "Secured Global Time Synchronization (SGTS)" to secure the global time on automotive networks (CAN, FlexRay, Ethernet).

Opposed-piston two-stroke engines offer numerous advantages over conventional four-stroke engines, both in terms of fundamental principles and technical aspects. The reduced heat losses and large volume-to-surface area ratio inherently result in a high thermodynamic efficiency. Additionally, the mechanical design is simpler and requires fewer components compared to conventional four-stroke engines. When combining this engine concept with alternative fuels such as hydrogen and pre-chamber technology, a potential route for carbon-neutral powertrains is observed. To ensure safe engine operation using hydrogen as fuel, it is crucial to consider strict safety measures to prevent issues such as knock, pre-ignition, and backfiring. One potential solution to these challenges is the use of direct injection, which has the potential to improve engine efficiency and expand the range of load operation.

Nowadays, green hydrogen can play a crucial role in a successful clean energy transition, thus reaching net zero emissions in the transport sector. Moreover, hydrogen exploitation in internal combustion engines is favoured by its suitable combustion properties and quasi-zero harmful emissions. High flame speeds enable a lean combustion approach, which provides high efficiency and reduces NOx emissions. However, high air flow rates are required to achieve the load levels typical of heavy-duty applications. In this framework, the present study aims to investigate the required boosting system of a 6-cylinder, 13-liter heavy-duty spark ignition engine through 1D numerical simulation. A comparison among various architectures of the turbocharging system and the size of each component is presented, thus highlighting limitations and potentialities of each architecture and providing important insights for the selection of the best turbocharging system.