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Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.

The ever increasing use of electronics in modern vehicles has not stopped at comfort systems such as power seats and power windows. Every conventional system that requires operating force will eventually be replaced by a self-powered version. One such item is the electromechanical parking brake of the new Audi A8, offering a host of new features. Despite the many options for new functions, it is nevertheless important to keep the driver in mind. Being engineers, one tends to overlook that not all customers share our excitement for gadgets and overly complicated technical features.

The aim of the project is to reliably identify the set of constructive features responsible for the highest noise levels in the interior of motor vehicles. A simulation environment based on artificial intelligence techniques such as neural networks and genetic algorithms has been implemented. We used a system identification approach in order to approximate the functional relationship between the target noise series and the sets of constructive parameters corresponding to the cars. The noise levels were measured with a microphone positioned on the driver''s chair, and corresponded to a variation of the engine rotation of 600-900 rot/min. The database includes 45 different cars, each described by vectors of 67 constructive features.

The Advanced Lighting Simulation (ALS) is a development tool for systematically investigating and optimizing the Adaptive Light Control (ALC) system to provide the driver with improved headlamps and light distributions. ALS is based on advanced CA-techniques and modern validation facilities. To improve night time traffic safety the BMW lighting system ALC has been developed and optimized with the help of ALS. ALC improves the headlamp illumination by means of continuous adaptation of the headlamps according to the current driving situation and current environment. BMW has already implemented ALC prototypes in real vehicles to demonstrate the advantages on the real road.

The potential of determining the change of injury severity in the accident event taking passive as well as active measures into account at the vehicle (integral systems) are at present limited to pedestrian protective systems. Therefore, an extension of the existing methods for the application with common integral systems (front protection, side protection, etc.) is suggested. Nowadays the effectiveness of passive safety systems is determined in crash tests with very high accident severities. However, approximately 90% of real-world accidents have a lower accident severity as the required crash tests. Thus, this paper will present a method calculating the effectiveness of such an integral system based on real-world accident data. For these reasons, this paper is presenting a method for a more valid prediction of injury severity. The German In-Depth Database GIDAS allows clustering the accident event in relevant car-to-car scenarios.

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.

New power train concepts in the automobile industry will decisively change the familiar car acoustics. Secondary acoustic noise sources will be unmasked and dominate the driver's sound experience. The most important secondary noise source is the air conditioning (AC) system. Before a favorable AC sound can actively be designed, it is necessary to identify the acoustic noise sources and find means to influence them. This paper focuses on the AC outlet module which is, apart from the control unit, the only part visible to the customer. Typical acoustic spectra of flowed-through outlets show a characteristic tonality at about 3000 Hz. The knowledge of its aeroacoustic source mechanisms, the inherent implications for the customer and corrective measures especially in automobile surroundings has been limited so far. To analyze this phenomenon in detail, a simplified model outlet that shows the basic aeroacoustic behavior of a series production outlet was constructed and investigated.

When investigating the posture comfort in vehicles two important influencing factors can be distinguished: In order to evaluate these influences a combined laboratory-field-experiment was carried out. A real car was equipped with cameras to record the body posture and the joint angles. The static forces exerted by the driver on his contact points were recorded in a corresponding mock-up. The forces to maintain the body posture were calculated. The following results were found:

Strategies for weight reduction have driven the noise treatment advanced developments with a great success considering the already mastered weight decreases observed in the last years in the automotive industry. This is typically the case for all soft trims parts. In the early 2010's a typical european B-segment car soft trims weights indeed 30 to 40% less than in the early 2000's years. The main driver behind such a gap has been to combine insulation and absorption properties on a single part while increasing the number of layers. This product-process evolution was conducted using a significant improvement in the simulation capacities. In that sense, several studies presenting very good correlation results between Transmission Loss measurements and finite elements simulations on dashboard or floor insulators were presented. One may consider that those kinds of parts have already achieved a considerable improvement in performance.

The trend towards even more sophisticated driver assistance systems and growing automation of driving sets new requirements for the robustness and availability of the involved automotive systems. In case of an error, today it is still sufficient that safety related systems just fail safe or silent to prevent safety related influence of the driving stability resulting in a functional deactivation. But the reliance on passive mechanical fallbacks in which the human driver taking over control, being inevitable in such a scenario, is expected to get more and more insufficient along with a rising degree of driving automation as the driver will be given longer reaction time. The advantage of highly or even fully automated driving is that the driver can focus on other tasks than controlling the car and monitoring it’s behavior and environment.