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

2017 ◽  
Author(s):  
Michael Aeberhard
Keyword(s):  
Data Fusion ◽  
Sensor Data ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Sensor Data Fusion ◽  
Level Sensor ◽  
Environment Perception ◽  
High Level ◽  
Level Fusion

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...

High Level Sensor Data Fusion Approaches For Object Recognition In Road Environment

2007 ◽  
Author(s):  
Nikos Floudas ◽  
Aris Polychronopoulos ◽  
Olivier Aycard ◽  
Julien Burlet ◽  
Malte Ahrholdt
Keyword(s):  
Object Recognition ◽  
Data Fusion ◽  
Sensor Data ◽  
Sensor Data Fusion ◽  
Level Sensor ◽  
High Level

scholarly journals Driving Environment Perception Based on the Fusion of Vehicular Wireless Communications and Automotive Remote Sensors

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1860
Author(s):  
Minjin Baek ◽  
Jungwi Mun ◽  
Woojoong Kim ◽  
Dongho Choi ◽  
Janghyuk Yim ◽  
...  
Keyword(s):  
Wireless Communications ◽  
Wireless Communication ◽  
Sensor Data ◽  
Automated Vehicles ◽  
Remote Sensors ◽  
Track Fusion ◽  
Remote Sensor ◽  
Level Sensor ◽  
Environment Perception ◽  
High Level

Driving environment perception for automated vehicles is typically achieved by the use of automotive remote sensors such as radars and cameras. A vehicular wireless communication system can be viewed as a new type of remote sensor that plays a central role in connected and automated vehicles (CAVs), which are capable of sharing information with each other and also with the surrounding infrastructure. In this paper, we present the design and implementation of driving environment perception based on the fusion of vehicular wireless communications and automotive remote sensors. A track-to-track fusion of high-level sensor data and vehicular wireless communication data was performed to accurately and reliably locate the remote target in the vehicle surroundings and predict the future trajectory. The proposed approach was implemented and evaluated in vehicle tests conducted at a proving ground. The experimental results demonstrate that using vehicular wireless communications in conjunction with the on-board sensors enables improved perception of the surrounding vehicle located at varying longitudinal and lateral distances. The results also indicate that vehicle future trajectory and potential crash involvement can be reliably predicted with the proposed system in different cut-in driving scenarios.

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