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Über dieses Buch

Die inhaltlichen Schwerpunkte des Tagungsbands zur ATZlive-Veranstaltung Fahrerassistenzsysteme 2017 liegen unter anderem auf neuen Entwicklungen zum automatisierten Fahren. In Verbindung mit der Elektrifizierung und Vernetzung der Fahrzeuge entstehen neue Elektrik-/Elektronik-Architekturen und flexible Software-Plattformen. Weitere Themen sind z. B. neue Fahrerassistenzsysteme für Premium-Pkw, Brems- und Ausweich-Assistenten für Lkw und hochauflösende digitale Straßenkarten.



Automated driving functions for traffic flow models to assess the traffic situation

Nowadays, a detailed modelling of vehicle, sensors and environment is used for the development of Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD). Due to the time consuming simulation effort which comes along with then high complexity of these models, only specific scenarios can be simulated. For the investigation of the traffic situation at motorway sections with a length of some hundred meters up to some kilometres a big amount of vehicles have to be simulated at the same time. Therefore, microscopic simulation tools like VISSIM or SUMO can be used. But traffic simulation models are not designed for the simulation of automated driving behaviour. Due to these missing driving functionalities, traffic simulation tools cannot be used for studying the impact of the “artificial” driving on traffic flow and traffic performance.
In this article, a method is presented, that allows a view on the traffic situation in the near future including conventional, assisted and automated driven vehicles. Therefore, the microscopic traffic simulation environment VISSIM is enhanced by realistic automated driving functions, wherein the estimation of the needed vehicle model detailing is essential. On the one hand, it has to be ensured that a high number of vehicles can be simulated to enable the generation of traffic flow relevant parameters. On the other hand, the simplified vehicle models must not influence the basic driving behaviour, which has a significant effect on traffic flow characteristics.
The longitudinal and lateral controller for automated driving functionalities are developed in MATLAB and coupled with VISSIM via its external driver interface. In VISSIM the user can classify the vehicles as conventional, assisted or automated, but also sub-classifications in the automation levels are possible. This enables a flexible modelling and so a high variety of automation and penetration is possible. In addition, the basic longitudinal and lateral behaviour models (speed controller and lane change controller) are extended by cooperative behaviour models representing systems like Truck-Platooning, Cooperative Adaptive Cruise Control or Cooperative Lane Chang Assistant.
The microscopic traffic flow model which is coupled with advanced vehicle controllers is used to simulate the interaction between individual vehicles in mixed traffic situations. The output of this micro-simulation is used in the macroscopic transport model to determine traffic characteristics like travel speed, link capacity and others. Using this method allows to analyse the impact on capacity of automated driving in mixed traffic situations on motorways and other major roads. It is used to demonstrate how various automation levels and different vehicle categories (passenger and commercial vehicles) influences the link capacity of basic freeway segments as well as merge, diverge and weaving segments. Moreover, special events like roadwork zone or traffic jam effect the track availability with focus on travel speed, link capacity and traffic density.
Andreas Kerschbaumer, Martin Rudigier, Michael Haberl, Bernhard Hintermayer

Assistance-on-demand – development of a speech-based, personalized left-turning assistant

We recently developed the concept of “Assistance on Demand”. This describes an advanced driver assistance system (ADAS) which supports a driver in an inner city scenario only if she asks for assistance. A key element is the control of the ADAS via speech which allows the driver to flexibly formulate her requests for assistance while the situation develops. Our application scenario is turning left at unsignalized urban intersections. After the driver has activated the system via a speech command it monitors the right side traffic and informs about suitable gaps to enter the intersection, just like a co-driver would do.
In a first user study together with the Würzburg Institute for Traffic Sciences we investigated this concept in a driving simulator. The results showed that drivers clearly preferred our speech-based system to a visual system implemented via a HUD and to driving manually without system support.
We assume that drivers differ in what they perceive as a suitable gap to make the left turn. To test this hypothesis we have performed a second simulator study using CarMaker where 9 participants were turning left in crossing traffic from both sides. We deploy a probabilistic method to estimate the smallest accepted gap of each driver, so called critical gap. The results reveal that there is, as postulated, a significant inter-individual difference in the critical gap between the drivers. Next we investigate how well we can predict if a driver will accept a gap presented to him. We show that a prediction based on a driver’s personalized critical gap can achieve an accuracy of more than 90%.
Martin Heckmann, Heiko Wersing, Dennis Orth, Dorothea Kolossa

Evolution or revolution of the user experience through networked vehicles

The advancing networking and digitisation of automobiles provides unprecedented potential for new functionalities in the automotive industry, the consumer industry and for the driver. This advancement in vehicle functions offers, in addition to all positive aspects, a new increased danger potential due to the driver’s distraction. According to a survey conducted by the IT service provider CSC 2014, 61 percent of drivers are already distracted due to the new functions in the field of infotainment, connectivity or driver assistance and the tendency is increasing with new possibilities of the “Connected Car”.
Heiko Herchet, Johannes Barckmann

From research to mass production – using a versatile platform for developing new HAD software functions

These days developing highly automated driving (HAD) systems means to provide genuine features to the customers. This is in relation to features that no one else can provide or at least an OEM should be the first to show a function in a stock vehicle. However, these features are often developed in a research & development (R&D) or pre-series department using rapid prototyping methods, shown to the management, and then forwarded to the engineering department to be included into the product.
Sebastian Ohl

Integrated Cockpit Computer

The path to a central computer using virtualization technologies
Für den in den vergangenen Jahren anhaltenden Trend zur Zentralisierung und Vereinheitlichung von Steuergeräten sind die steigende Komplexität an Fahr- und Komfortfunktionen, sowie die immer leistungsfähigeren Hardware-Komponenten als Hintergründe zu benennen. Diese Entwicklung bildet u.a. die Grundlage zur Einsparung von Kosten im Bereich der Fahrzeuginfrastruktur.
Ausgangspunkt ist die aktuelle Fahrzeug-Vernetzungsarchitektur mit einem ersten Schritt hin zur Vereinheitlichung von Infotainmentsystem und Clusterinstrument. Teilaspekte dabei sind die folgenden Punkte:
  • Gesamtsystem bestehend aus zwei bis x Display-Einheiten und dem Integrated ClusterComputer
  • Anforderungen an funktionale Sicherheit und Verfügbarkeit
  • Möglichkeiten der Trennung von unterschiedlichen Softwarebereichen mit demAnsatz derVirtualisierung
Der Integrated Cluster Computer dient wiederum als Ausgangspunkt für einen möglichen Lösungsansatz für zukünftige Fahrzeugplattformen. In diesem Ansatz wird ein Verbund von Zentralrechnern als Grundlage gewählt, welche die Möglichkeiten bieten, sehr dynamisch Applikationen während der Laufzeit zwischen verschiedenen ECUs zu verschieben bzw. Applikationen auf verschiedenen ECUs zu parallelisieren. Weitere Aspekte sind als interessant anzusehen und werden in zukünftigen Rechnerarchitekturen eine mögliche Anwendung finden:
  • Priorisierung von Applikationen mit dem Einsatz von Coldplug, Hotplug, Swap VM undParallel Function Processing
  • Anforderung und Einsatz an intelligente Diagnose-/Steuerungsverfahren
Alternative Nutzung der Rechenressourcen außerhalb des Fahrzeuges am Beispiel Cloud
David Rabe, Matthias Rudolf

Automotive 3D reconstruction based on multi-pixel LED headlight systems

Autonomous driving is one of the major trends in mobility for the past decade as well as for the upcoming years. In order to realize a fully automated vehicle steering a detailed representation about the cars environment is of crucial importance. This is only possible with reconstruction systems allowing dense reconstruction grids combining trustworthiness of the data, based on redundant information.
Christian Schneider, Maximilian Meyer, Tim Kunz

Legal Framework For Automated Driving Functions „Burden Or Vantage“?

Legal framework for automated driving functions „burden or vantage“?
Carsten Winkelbach, Folkert Jürgens, Heiko Ehrich

Evaluation of ADAS at low speed scenarios

According to latest research performed by several RCAR (Research Council for Automobile Repairs) members and partners during the last years, parking and maneuvering accidents appear to be increasingly relevant in third party damage liability and first party or motor own damage claims, a trend evident in many RCAR member states.
Gerald-Alexander Beese, Helge Kiebach

Current research results on the effectiveness of driver assistance systems with increasing degree of automation

As the research institute for Allianz Deutschland AG, the Allianz Zentrum für Technik (Allianz Center for Technology, AZT) is researching issues from the automotive technology and road safety sectors with the following fundamental aims:
  • increasing safety on the road through damage prevention
  • decreasing damage costs on vehicle insurance through damage prevention, improved crash behaviour, increased reparability and economic repair and calculation procedures.
Marcel Borrack, Johann Gwehenberger, Julian Schatz, Philip Feig

Connected car – driver assistance sensors get connected

In future we will see more and more connected cars, which means that cars have a direct mobile communication or WLAN link to the cloud, to traffic infrastructure or even between each other, based on secure connections. First legislation initiatives, e.g. in China, already require continuous supervision of drivetrain systems based on a cloud network. New business models and extended chains of economic value will change and create new markets.
Stephan Stass, Hans-Jörg Mathony, Cristian Gavanescu, Christian Passmann, Dieter Hötzer

Use cases for automated driving commercial vehicles

Automated driving will be one of the most important trends of the next decade and will have a sustained impact on the automotive industry itself and the way vehicles are used in the future. Automated driving is particularly important for the commercial vehicle sector in view of the high mileages trucks accumulate as compared to passenger cars.
Alexander-Cosmin Teleki, Maria Fritz, Matthias Kreimeyer


Driver assistance in the new BMW 5 Series –experience automation.
Claus Dorrer, Reiner Friedrich, Philipp Reinisch

Scenario-based approach for developing ADAS and automated driving functions

Ever since the advent of the first electronic driver assistance systems, such as the electronic speed control invented by Daniel Aaron Wisner as early as 1968, these systems have undergone rapid evolution. While these were formerly integrated as standalone individual components, modern advanced driver assistance systems are not only connected to the vehicle components which they control but also networked with each other.
Andreas Höfer, Martin Herrmann

A real-time capable multi-sensor model to validate ADAS in a virtual environment

The realization of secure, reliable, and socially accepted autonomous vehicles is closely connected to the ability of validating the functionality of Advanced Driver Assistance Systems (ADAS). As environmental sensors (radar, lidar, video, or ultrasonic) gather multifaceted information of the current traffic scenario, the input vector to the ADAS ECU is high-dimensional, including for example weather conditions, traffic flow or material properties.
Marius Feilhauer, Jürgen Häring

Virtual Validation of Automated Driving Functions Using a Construction Site Assistant as an Example

Virtual Validation of Automated Driving Functions Using a Construction Site Assistant as an Example.
André Rolfsmeier, Hagen Haupt, Karsten Krügel

Evasive Maneuver Assist (EMA) – enhanced vehicle safety using a combination of braking and steering

Evasive Maneuver Assist leverages the capabilities of WABCO’s industry-leading OnGuardACTIVE™, its most advanced, radar-only collision mitigation system. A radar sensor identifies moving or stationary vehicles ahead and alerts the driver via visual, audio and haptic signals of impending rear-end collisions. Should the driver determine that the system cannot avoid a rear-end collision by driver-initiated or autonomous braking alone, Evasive Maneuver Assist engages to help the driver to safely steer around an obstructing vehicle and to bring truck and trailer to a complete and safe stop.
Stephan Kallenbach, Ralph-Carsten Lülfing, Klaus Plähn

Sensor-based learning – one step closer to autonomous driving

On the route towards autonomous driving, boring routine tasks for the driver will gradually become obsolete. There are a lot of driving scenarios where driver assistance features may already work more or less independent from the driver and others where the driver has to take over, e.g. the autonomous driving road ends. The reasons for taking over vary from limitations of the range of ego sensors or recognition algorithms as well as to information, e.g. legal traffic regulations per country, which cannot be derived from in-vehicle sensor observations. What all have in common is that any reaction both from the driver but also from a driver assistance feature needs to be in time. This becomes clear when investigating the limitations of the range of ego sensors or recognition algorithms as well as information, e.g. legal traffic regulations per country, which cannot be derived from sensor observations.
Nicole Beringer

Vehicle speed trajectory optimization under limits in time and spatial domains

Among various aspects for predictive vehicle energy management optimization, driving speed profile optimization is a key factor for reducing energy consumption. Focus of this article is to optimize the speed trajectory of the vehicle along a given route, to reduce the energy consumption without sacrificing the overall travel time, which is a typical trade-off with energy consumption.
Ziqi Ye, Thorsten Plum, Stefan Pischinger, Jakob Andert, Michael Stapelbroek, Jan Pfluger

Trusted execution environments in vehicles for secure driver assistance systems

Advanced driver assistance systems (ADAS) offer compelling benefits for vehicle drivers. However, they also require a deep integration with safety critical vehicle functions such as steering, acceleration, and breaking. This fact makes it relevant to review ADAS not only with regard to safety, but also with regard to security. It constitutes a serious impact on the safety of passengers if an attacker gets in the position to manipulate ADAS components.
Jens Köhler, Henry Förster

The impact of 5G on future driver assistance and autonomous driving systems

The car of tomorrow is not only communicating with other cars (peer to peer and ad-hoc networking) and the infrastructure (Car2Infrastructure), but also with its entire surroundings (Car2X). They will inform themselves about obstacles, analyze the behavior of other traffic members and communicate with traffic signs and signals exchange data with mobile devices and many more! The demand for networking and communication between the vehicles permeates the automotive industry in breathtaking speed.
Sebastian Rettlinger, S. Butenweg, F. Fitzek

Big data re-simulations for autonomous driving using DaSense

The core of autonomous driving are intelligent algorithms that control real-time actions based on the recordings of on-board sensors which monitor the environment as well as the internal states of the car. Many open issues are to be solved before the vision of autonomously driving fleets of cars employing such algorithms will become reality. Amongst them is how to structure the process of developing the algorithms to meet functional and non-functional requirements.
Tobias Abthoff, Nicoletta John, Katharina Kreplin, Jonas Lorenz, Andreas Pawlik, Tilmann Piffl, Jose Villaveces, Adrian Villwock

Incorporating high fidelity physics into ADAS and autonomous vehicles simulation

Developing Advanced Driver Assistance Systems (ADAS) and autonomous vehicles is a challenge without precedence. Whole new engineering fields – such as artificial intelligence – need to be developed, yet time-to-market is short with intense competition. Estimates indicate that billions of miles of road testing will be necessary to ensure safety and reliability of ADAS and autonomous vehicles. This seemingly impossible task can only be accomplished with the help of engineering simulation. With simulation thousands of driving scenarios and design parameters can be virtually tested with precision, speed and cost economy. This paper describes six specific areas where simulation is essential in the development of autonomous vehicles and advanced driver assistance systems. It specifically focuses on high-fidelity simulation methods involving rigorous solutions of underlying physical phenomena.
Sandeep Sovani, Lee Johnson, Jacques Duysens

Development and test of a lane change prediction algorithm for automated driving

Due to a large number of integrated advanced driver assistance systems (ADAS) the driver nowadays can hand over the driving task to the vehicle in specific, monotone driving scenarios. Short reaction times and the constant awareness of the computer reduces the number of accidents and thus increases safety. Currently available ADAS still need to be constantly monitored by the driver in case a situation appears that cannot be handled properly by the system.
Christian Wissing, Karl-Heinz Glander, Carsten Haß, Till Nattermann, Torsten Bertram

In-vehicle validation of safety-critical sensor fusion ECUs with microprocessor technology

High demands regarding computing power, safety and security for sensor fusion ECUs require new architectures with microprocessors. The article describes the necessary new measurement concepts and the impact of the software concepts.
Heinz Tilsner, Burkhard Triess


Die langfristigen Ziele und der Nutzen automatischer Fahrfunktionen stehen zwar nicht infrage, aber bei den ersten Markteinführungen gilt es nun, genauer hinzuschauen, wie auf der von Continental und Etas unterstützten 3. ATZ-Tagung Fahrerassistenzsysteme – Von der Assistenz zum automatisierten Fahren am 26. und 27. April in Frankfurt am Main.
Markus Schöttle
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