Sensor Models — Key Ingredient for Sensor Fusion in Automated Driving

In automated driving, the term sensor model is typically used when it comes to the simulation of sensors, e.g. as part of a validation chain. While sensor models are a major aspect of simulation, they are equally important for the performance of the environmental model and its contained sensor fusion. Scalable sensor fusion architectures allow easy exchange of sensor models so that tested components can be reused and more development resources can be spent in sensor modeling.

What is a Sensor Model?

Regardless of whether a sensor model is used for simulation or sensor fusion, it describes (and typically approximates) how objects like cars, pedestrians and so on interact with a particular sensor. Here, “interacting” involves the two aspects object detectability and object appearance:

Exemplary radar camera fusion where the radar‘s detection rate gets smaller with increasing object distance. Object confirmation time gets reduced if the radar’s detection characteristic is properly modeled (solid lines) compared to a radar model with constant detection rate (dashed lines).

How Sensor Models Influence Sensor Fusion Architectures

In theory, we could design sensor models that are very close to the real sensor behavior, e.g. physical models or highly complex phenomenological models. In reality, we are often limited in the degree of freedom for sensor modeling. This is mainly due to limitations of the intended execution hardware and a lack of relevant data for the identification and parametrization of such complex models.

Requirements of a Scalable Sensor Fusion Architecture

Modifications in the architecture of the sensor fusion can compensate for this limitation up to some extend, however, these architecture modifications are model-specific and often require deep modifications of the overall algorithm and code. Especially when it comes to production usage and automotive development processes and regulations like ISO 26262, these modifications become cost and time intensive if applied manually in each and every project.

Sensor fusion enthusiast and co-founder of BASELABS.