A Method to Assess and Compare Proving Grounds in the Context of Automated Driving Systems

Katzorke, Nils; Moosmann, M.; Imdahl, R.; Lasi, Heiner

doi:10.1109/itsc45102.2020.9294310

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…Driver assistance systems include FCW, AEB, LKA, or ESP. ADAS are maximum level 2 solutions according to SAE [2, 35,36]. They form the basis of higher-level systems.…”

Section: Normative and Unified Av Test Proceduresmentioning

confidence: 99%

Research Scenarios of Autonomous Vehicles, the Sensors and Measurement Systems Used in Experiments

Prochowski

Szwajkowski

Ziubiński

2022

Sensors

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Automated and autonomous vehicles are in an intensive development phase. It is a phase that requires a lot of modelling and experimental research. Experimental research into these vehicles is in its initial state. There is a lack of findings and standardized recommendations for the organization and creation of research scenarios. There are also many difficulties in creating research scenarios. The main difficulties are the large number of systems for simultaneous checking. Additionally, the vehicles have a very complicated structure. A review of current publications allowed for systematization of the research scenarios of vehicles and their components as well as the measurement systems used. These include perception systems, automated response to threats, and critical situations in the area of road safety. The scenarios analyzed ensure that the planned research tasks can be carried out, including the investigation of systems that enable autonomous driving. This study uses passenger cars equipped with highly sophisticated sensor systems and localization devices. Perception systems are the necessary equipment during the conducted study. They provide recognition of the environment, mainly through vision sensors (cameras) and lidars. The research tasks include autonomous driving along a detected road lane on a curvilinear track. The effective maintenance of the vehicle in this lane is assessed. The location used in the study is a set of specialized research tracks on which stationary or moving obstacles are often placed.

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“…Driver assistance systems include FCW, AEB, LKA, or ESP. ADAS are maximum level 2 solutions according to SAE [2, 35,36]. They form the basis of higher-level systems.…”

Section: Normative and Unified Av Test Proceduresmentioning

confidence: 99%

Research Scenarios of Autonomous Vehicles, the Sensors and Measurement Systems Used in Experiments

Prochowski

Szwajkowski

Ziubiński

2022

Sensors

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“…Advanced methods may significantly reduce the necessary testing time on proving grounds. However, the role of proving ground testing cannot be completely replaced [35].…”

Section: Introductionmentioning

confidence: 99%

Development and Functional Validation Method of the Scenario-in-the-Loop Simulation Control Model Using Co-Simulation Techniques

Toth,

Szalay

2023

Machines

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With the facilitated development of highly automated driving functions and automated vehicles, the need for advanced testing techniques also arose. With a near-infinite number of potential traffic scenarios, vehicles have to drive an increased number of test kilometers during development, which would be very difficult to achieve with currently utilized conventional testing methods. State-of-the-Art testing technologies such as Vehicle-in-the-Loop (ViL) or Scenario-in-the-Loop (SciL) can provide a long-term solution; however, validation of these complex systems should also be addressed. ViL and SciL technologies provide real-time control and measurement with multiple participants; however, they require enormous computational capacity and low-latency communication to provide comparable results with real-world testing. 5G (fifth-generation wireless) communication and Edge computing can aid in fulfilling these needs, although appropriate implementation should also be tested. In the current paper, a realized control model based on the SciL architecture was presented that was developed with real-world testing data and validated utilizing co-simulation and digital twin techniques. The model was established in Simcenter Prescan© connected to MATLAB Simulink® and validated using IPG CarMaker®, which was used to feed the simulation with the necessary input data to replace the real-world testing data. The aim of the current paper was to introduce steps of the development process, to present the results of the validation procedure, and to provide an outlook of potential future implementations into the state of the art in proving ground ecosystems.

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Critical Scenario Identification Concept: The Role of the Scenario-in-the-Loop Approach in Future Automotive Testing

Szalay

2023

IEEE Access

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A Method to Assess and Compare Proving Grounds in the Context of Automated Driving Systems

Cited by 5 publications

References 2 publications

Research Scenarios of Autonomous Vehicles, the Sensors and Measurement Systems Used in Experiments

Research Scenarios of Autonomous Vehicles, the Sensors and Measurement Systems Used in Experiments

Development and Functional Validation Method of the Scenario-in-the-Loop Simulation Control Model Using Co-Simulation Techniques

Critical Scenario Identification Concept: The Role of the Scenario-in-the-Loop Approach in Future Automotive Testing

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