Technologies for highly automated driving on highways

Kämpchen, Nico; Aeberhard, Michael; Ardelt, Michael; Rauch, Sebastian

doi:10.1007/s38311-012-0176-y

Cited by 8 publications

(4 citation statements)

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“…The first fully automated drive between Munich and Ingolstadt in Germany was made on June 16th, 2011 with over 30 completely automated lane change maneuvers during the trip [8]. A combination of environment perception, localization and driving strategy technology was used to achieve this type of automated driving on highways [342,348]. The environment perception algorithms for object detection 1.2 Automation in Driver Assistance and Safety Systems presented in this thesis were successfully integrated into the prototype vehicles for this project.…”

Section: Automated Driving On Highwaysmentioning

confidence: 99%

“…The most prominent project which made use of the methods presented is BMW's research prototypes for automated driving on the highway, where a visualization of the automated driving system's functionality and environment model is shown in Figure 7.14. These prototype vehicles have been testing on public roads since 2011 [8,50], [336,342,348] and have since accumulated many thousands of kilometers of automated driving on the highways in the Munich area.…”

Section: Integration In Automated Driving and Adas Projectsmentioning

confidence: 99%

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Object-Level Fusion for Surround Environment Perception in Automated Driving Applications

Aeberhard¹

2017

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Driver assistance systems have increasingly relied on more sensors for new functions. As advanced driver assistance system continue to improve towards automated driving, new methods are required for processing the data in an efficient and economical manner from the sensors for such complex systems. In this thesis, an environment model approach for the detection of dynamic objects is presented in order to realize an effective method for sensor data fusion. A scalable high-level fusion architecture is developed for fusing object data from several sensors in a single system. The developed high-level sensor data fusion architecture and its algorithms are evaluated using a prototype vehicle equipped with 12 sensors for surround environment perception. The work presented in this thesis has been extensively used in several research projects as the dynamic object detection platform for automated driving applications on highways in real traffic. Contents Abbreviations VIII List of Symbols X Abs...

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Section: Automated Driving On Highwaysmentioning

confidence: 99%

Section: Integration In Automated Driving and Adas Projectsmentioning

confidence: 99%

Object-Level Fusion for Surround Environment Perception in Automated Driving Applications

Aeberhard¹

2017

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“…For several years, the BMW Group Research and Technology has been testing automated vehicles on the highways around Munich, Germany [14], [15]. The goal of this project was to learn about the technologies and algorithms necessary in developing a highly automated driving (HAD) system, as per the BASt definitions [16], or conditional automated driving, as per the NHTSA [17] and SAE [18] definitions, of automation levels.…”

Section: Introductionmentioning

confidence: 99%

Experience, Results and Lessons Learned from Automated Driving on Germany's Highways

Aeberhard

Rauch

Bahram

et al. 2015

IEEE Intell. Transport. Syst. Mag.

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The BMW Group Research and Technology has been testing automated vehicles on Germany's highways since Spring 2011. Since then, thousands of kilometers have been driven on the highways around Munich, Germany. Throughout this project, fundamental technologies, such as environment perception, localization, driving strategy and vehicle control, were developed in order to safely operate prototype automated vehicles in real traffic with speeds up to 130 km/h. The goal of this project was to learn what technologies are necessary for automated driving. This paper presents the architecture and algorithms developed during this project, results from real driving scenarios, the lessons learned throughout the project and a quick introduction into the latest developments for improving the system.

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“…The research vehicle as fitted is able to drive on highways autonomously with numerous sensors; it is able to operate at speeds between 0 km/h and 130 km/ h and complies with all traffic regulations. 2 The Defense Advanced Research Projects Agency (DARPA) Urban Challenge, which is a driverless car competition hosted by DARPA in the USA, encourages a number of academic teams and company research groups to develop autonomous vehicle technology in real-car applications, such as the autonomous vehicle Boss made by Carnegie Mellon University and the General Motors Corporation and the autonomous vehicle Junior entered by the Stanford Racing Team in the DARPA Urban Challenge (2007). 3 Since autonomous and unmanned vehicles either are being considered or have already been greatly valued, an active collision avoidance system (ACAS) is one of the key subsystems that guarantees that an autonomous vehicle avoids collisions with other obstacles on the road.…”

Section: Introductionmentioning

confidence: 99%

Simulation research on emergency path planning of an active collision avoidance system combined with longitudinal control for an autonomous vehicle

Cao

Song

Huang

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part D:

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Autonomous vehicle technology is greatly valued nowadays, and an active collision avoidance system is one of the key parts for autonomous driving. This study presents a comprehensive architecture of an active collision avoidance system for an autonomous vehicle, which is integrated with a decision-making module, a path-planning module, a lateral-path-following module and a fuzzy adaptive following module (longitudinal motion) to deal with potential hazards on a straight road or a curved road. In order to make the planned path for overtaking manoeuvres safer, an improved harmonic velocity potential approach for path planning is presented, which innovatively enhances the effect of an obstacle potential on a road by adding a scale term, so that it can generate a smooth path for a vehicle-overtaking manoeuvre. All the potentials which are used for vehicle lane keeping or lane changing are well designed. The lateral-path-following module is based on the constrained linear model predictive control approach, which ensures that the host vehicle can follow the planned path precisely. Furthermore, when the overtaking manoeuvre is not suitable, the fuzzy adaptive following module is utilized to ensure that the host vehicle can adaptively keep a safe distance from the preceding vehicle. Tactical decisions, such as overtaking, accelerating or decelerating, are determined by the decision-making module. Finally, several typical scenarios with low traffic on a straight road or a curved road are simulated to verify the effectiveness and the feasibility of the active collision avoidance system. The simulation results show that the host vehicle can make a successful collision avoidance manoeuvre without the intervention of a human driver in different situations.

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Technologies for highly automated driving on highways

Cited by 8 publications

References 0 publications

Object-Level Fusion for Surround Environment Perception in Automated Driving Applications

Object-Level Fusion for Surround Environment Perception in Automated Driving Applications

Experience, Results and Lessons Learned from Automated Driving on Germany's Highways

Simulation research on emergency path planning of an active collision avoidance system combined with longitudinal control for an autonomous vehicle

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