Advanced Physics Based Sensor Simulation Approaches for Testing Automated and Connected Vehicles

This presentation was made at NAFEMS Americas Seminar "Engineering Analysis & Simulation in the Automotive Industry: Creating the Next Generation Vehicle Accurate Modelling for Tomorrow's Technologies".

The automotive engineering community is now confronting the largest technology transformation since its inception. This includes the electrification of powertrains for more efficient consumption and cleaner emissions, the reinvention of the battery with fast wireless charging capabilities and finally the advent of a fully autonomous vehicle. Compounding to these technology changes, the automotive companies design verification process is moving away from a major reliance on physical testing to almost a full virtual simulation product verification process. The challenges to the automotive engineers are enormous and require a significant increase in the upfront use of numerical simulation capabilities, methods and processes such they’re able to efficiently design, manufacture and deliver these very innovative technologies to the market in greater speeds than ever before.

Resource Abstract

In order to provide a “due care” testing approach to automated and connected vehicle technology, an advanced sensor simulation must be involved. Although real-world or field tests are required as well as test track testing, simulation can provide a bulk of the testing and also provide tests not producible via real or test track testing. However, to provide the most accurate and best validation, sensor simulation closest to “raw data” would be preferred. Furthermore besides the deterministic set of data that a simulation program can produce, it is also important to produce probabilistic models that correlate to real world data. Advanced physics based sensor models with deterministic and probabilistic components are introduced. The models described include: Camera, Radar, Lidar and V2X. These models can be used to produce ROC (Receiver Operating Characteristic) curves and other measures of detection and estimation system performance. Using these measures allows for a robust system for real world operation.

Document Details

AuthorGioutsos. T
Date 8th November 2018


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