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The development of highly automated driving functions (AD) recently rises the demand for so called Fail-Operational systems for native driving functions like steering and braking of vehicles. Fail-Operational systems shall guarantee the availability of driving functions even in presence of failures. This can also mean a degradation of system performance or limiting a system’s remaining operating period. In either case, the goal is independency from a human driver as a permanently situation-aware safety fallback solution to provide a certain level of autonomy. In parallel, the connectivity of modern vehicles is increasing rapidly and especially in vehicles with highly automated functions, there is a high demand for connected functions, Infotainment (web conference, Internet, Shopping) and Entertainment (Streaming, Gaming) to entertain the passengers, who should no longer occupied with driving tasks.

The performance of environment perceiving sensors such as e.g. lidar, radar, camera and ultrasonic sensors is safety critical for automated driving vehicles. Therefore, one has to assess the sensors’ performance to assure the automated driving system’s safety. The performance of these sensors is however to some degree sensitive towards adverse weather conditions. A challenge is to quantify the effect of adverse weather conditions on the sensor’s performance early in the development of an automated driving system. This challenge is addressed in this work for lidar sensors. The lidar equation was previously employed in this context to derive estimates of a lidar’s maximum range in different weather conditions. In this work, we present a stochastic simulation framework based on a probabilistic extension of the lidar equation, to quantify the effect of adverse rainfall conditions on a lidar’s raw detection performance.

Advanced safety features and new services in connected cars depend on the security of the underlying vehicle functions. Due to the interconnection with the outside world and as a result of being an embedded system a modern vehicle is exposed to both, malicious activities as faced by traditional IT world systems as well as physical attacks. This introduces the need for utilizing hardware-assisted security measures to prevent both kinds of attacks. In this paper we present a survey of the different classes of hardware security devices and depict their different functional range and application. We demonstrate the feasibility of our approach by conducting a case study on an exemplary implementation of a function-on-demand use case. In particular, our example outlines how to apply the different hardware security approaches in practice to address real-world security topics. We conclude with an assessment of today’s hardware security devices.

A main challenge when developing next generation architectures for automated driving ECUs is to guarantee reliable functionality. Today’s fail safe systems will not be able to handle electronic failures due to the missing “mechanical” fallback or the intervening driver. This means, fail operational based on redundancy is an essential part for improving the functional safety, especially in safety-related braking and steering systems. The 2-out-of-2 Diagnostic Fail Safe (2oo2DFS) system is a promising approach to realize redundancy with manageable costs. In this contribution, we evaluate the reliability of this concept for a symmetric and an asymmetric Electronic Power Steering (EPS) ECU. For this, we use a Markov chain model as a typical method for analyzing the reliability and Mean Time To Failure (MTTF) in majority redundancy approaches. As a basis, the failure rates of the used components and the microcontroller are considered.

With increasing levels of driving automation, the perception provided by automotive environment sensors becomes highly safety relevant. A correct assessment of the sensors’ perception reliability is therefore crucial for ensuring the safety of the automated driving functionalities. There are currently no standardized procedures or guidelines for demonstrating the perception reliability of the sensors. Engineers therefore face the challenge of setting up test procedures and plan test drive efforts. Null Hypothesis Significance Testing has been employed previously to answer this question. In this contribution, we present an alternative method based on Bayesian parameter inference, which is easy to implement and whose interpretation is more intuitive for engineers without a profound statistical education. We show how to account for different environmental conditions with an influence on sensor performance and for statistical dependence among perception errors.

Driven by the growing internet and remote connectivity of automobiles, combined with the emerging trend to automated driving, the importance of security for automotive systems is massively increasing. Although cyber security is a common part of daily routines in the traditional IT domain, necessary security mechanisms are not yet widely applied in the vehicles. At first glance, this may not appear to be a problem as there are lots of solutions from other domains, which potentially could be re-used. But substantial differences compared to an automotive environment have to be taken into account, drastically reducing the possibilities for simple reuse. Our contribution is to address automotive electronics engineers who are confronted with security requirements. Therefore, it will firstly provide some basic knowledge about IT security and subsequently present a selection of automotive specific security use cases.

The increasing complexity of automotive functions which are necessary for improved driving assistance systems and automated driving require a change of common vehicle architectures. This includes new concepts for E/E architectures such as a domain-oriented vehicle network based on powerful Domain Control Units (DCUs). These highly integrated controllers consolidate several applications on different safety levels on the same ECU. Hence, the functions depend on a strictly separated and isolated implementation to guarantee a correct behavior. This requires middleware layers which guarantee task isolation and Quality of Service (QoS) communication have to provide several new features, depending on the domain the corresponding control unit is used for. In a first step we identify requirements for a middleware in automotive DCUs. Our goal is to reuse legacy AUTOSAR based code in a multicore domain controller.

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.

Starting from the USA and followed by the European Union, legal requirements concerning “Tire Pressure Monitoring Systems” (TPMS) for passenger cars and light trucks will be introduced in China as well and therefore in the third of the three largest automobile markets worldwide. Changes of pressure dependent physical tire properties such as dynamic roll radius and a certain tire eigenfrequency, which are included in the ESC-wheel speed signals, indicates pressure loss in an indirect manner. Systems with corresponding working principles are called “indirect Tire Pressure Monitoring System” (iTPMS). Since the tire is a structural element with varying characteristics according to the design parameters, the roll radius and frequency behavior due to pressure loss is variable as well. As a consequence, tires have to be evaluated regarding there compatibility to iTPMS during the vehicle development process.

The German funded project ARAMiS included work on several demonstrators one of which was a multicore approach on large scale software integration (LSSI) for the automotive domain. Here BMW and Audi intentionally implemented two different integration platforms to gain both experience and real life data on a Hypervisor based concept on one side as well as using only native AUTOSAR-based methods on the other side for later comparison. The idea was to obtain figures on the added overhead both for multicore as well as safety, based on practical work and close-to-production implementations. During implementation and evaluation on one hand there were a lot of valuable lessons learned about multicore in conjunction with safety. On the other hand valuable information was gathered to make it finally possible to set up a cost model for estimation of potential overhead generated by different integration approaches for safety related software functions.

In the context of the ARAMiS project, AUDI AG contributed the development of a multi-core demonstrator based on car functions already in production. For this demonstrator, these legacy car functions were ported from single-core platforms to a multi-core platform to gain real world close-to-production experience while utilizing the new technology. For complex functions with high demands for computational resources, it may be necessary to distribute computation over several cores. In this context, we investigated the parallelization of a legacy sequential AUTOSAR function. A main contribution of this work is an analysis of mechanisms provided by AUTOSAR, their limitations and, possible remedy. This paper will point out observations and experiences during the development of this demonstrator and show practical solutions for parallelization in an AUTOSAR environment.

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.

This study deals with the experimental investigation of the mechanical properties of a lithium-ion pouch cell and its modelling in an explicit finite element simulation code. One can distinguish between ‘macroscopic’ and ‘microscopic’ modelling approaches. In the ‘macroscopic’ approach, one material model approximates the behaviour of multiple inner cell layers. In the ‘microscopic’ approach, which is used in the present study, all layers and their interactions are modelled separately. The cell under study is a pouch-type lithium-ion cell with a liquid electrolyte. With its cell chemistry, design, size and capacity it is usable for automotive applications and can be assembled into traction batteries. One cell sample was fully discharged and disassembled, and its components (anode, cathode, separator and pouch) were examined and measured by electron microscopy. Components were also tensile tested.

The increased pressure for power, space, and cost reduction in automotive applications together with the availability of high performance, automotive qualified multicore microcontrollers has lead to the ability to engineer Domain Controller ECUs that can host several separate applications in parallel. The standard automotive constraints however still apply, such as use of AUTOSAR operating system, support for legacy code, hosting OEM supplied code and the ability to determine warranty issues and responsibilities between a group of Tier 1 and Tier 2 vendors who all provide Intellectual Property to the final production ECU. Requirements for safety relevant applications add even more complexity, which in most current approaches demand a reconfiguration of all basic software layers and a major effort to redesign parts of the application code to enable co-existence on the same hardware platform. This paper outlines the conflicting requirements of hosting multiple applications.

Multicore-based ECUs are increasingly used in embedded automotive software systems to allow more demanding automotive applications at moderate cost and energy consumption. Using a high number of parallel processors together with a high number of executed software components results in a practically unmanageable number of deployment alternatives to choose from. However correct deployment is one important step for reaching timing goals and acceptable latency, both also a must to reach safety goals of safety-relevant automotive applications. In this paper we focus at reducing the complexity of deployment decisions during the phases of allocation and scheduling. We tackle this complexity of deployment decisions by a mixed constructive and analytic approach.

Multicore processor are well established in classical and tablet personal computers for some year. Such processors use more then one central core for computation and allow to integrate more computational power with smaller costs. However more than 90% of all processors worldwide are not placed in classical IT but are empedded in bigger systems like in modern vehicles or airplanes. Such systems face a very high demand in terms of safety, security an reliability which hinders the use of multicores in such systems. The funded project ARAMiS faces these demands and has the goal to enable the usability of multicore systems in the domains automotive and avionics, as well as later also railway. ARAMiS is the basis for higher traffic safety, traffic efficiency and comfort.

The anti-lock braking system (ABS) is a widespread driver assistance system which allows a short braking distance while simultaneously maintaining the stability and steerability of the car. Vehicles with electric single-wheel drive offer many possibilities of improving the energy efficiency and the braking performance during ABS braking. In this paper, two different ways of including the electric machines in the ABS are analyzed in detail: the damping of torsional drive train vibrations in combination with recuperation and the dynamic split of the braking torque, where the hydraulic braking torque is kept constant and the dynamic modulation of the braking torque is performed by the electric machines. The damping algorithm is developed on the basis of a linearized model of the drive train and the tire-road contact by using state feedback and pole placement methods. Simulation results with a detailed multi-body system show the effectiveness of the control algorithms.

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.

With the introduction of the ISO26262 automotive safety standard there is a burden of proof to show that the processing elements in embedded microcontroller hardware are capable of supporting a certain diagnostic coverage level, depending on the required Automotive Safety Integrity Level (ASIL). The current mechanisms used to provide actual metrics of the Built-in Self Tests (BIST) and Lock Step comparators use Register Transfer Level (RTL) simulations of the internal processing elements which force faults into individual nodes of the design and collect diagnostic coverage results. Although this mechanism is robust, it can only be performed by semiconductor suppliers and is costly. This paper describes a new solution whereby the microcontroller is synthesized into a large Field Programmable Gate Array (FPGA) with a test controller on the outside.

GTL (Gas-To-Liquid) fuel is well known to improve tailpipe emissions when fuelling a conventional diesel vehicle, that is, one optimized to conventional fuel. This investigation assesses the additional potential for GTL fuel in a GTL-dedicated vehicle. This potential for GTL fuel was quantified in an EU 4 6-cylinder serial production engine. In the first stage, a comparison of engine performance was made of GTL fuel against conventional diesel, using identical engine calibrations. Next, adaptations enabled the full potential of GTL fuel within a dedicated calibration to be assessed. For this stage, two optimization goals were investigated: - Minimization of NOx emissions and - Minimization of fuel consumption. For each optimization the boundary condition was that emissions should be within the EU5 level. An additional constraint on the latter strategy required noise levels to remain within the baseline reference.