Despite the travel limitations imposed by the COVID-19 pandemic, the online NWE-4 was a great success and a valuable experience for each ESR. they got the chance to interact socially with other ESRs and benefit from the various scientific and soft-skill trainings.

Will the wireless communication of future autonomous vehicles be robust against electromagnetic disturbances? What about the continuous wave disturbance?

For autonomous vehicles (AV) to perform at par with human ability, we first need to understand human driving behaviour. For simplification, human driving tasks can be broken down into two categories of tasks, i.e., the ‘what tasks’ and the ‘how tasks’, together referred to as the orthogonal tasks. The driving task under the ‘what category’ can be further broken down ...

Safety concern in an autonomous vehicles (AV) primarily arises from the software pipeline which has successfully replaced the human driver, who earlier acted as an integrator and operator of various driving tasks. AV need to perform multiple highly dynamic and complex tasks for which they should be able to generalise any unpredictable situation and this process primarily depends on its ...

Building a safety case does not have to be a hassle.

Vehicle safety has a lot of checks before a model hits the market.

Half way through the Safer Autonomous Systems project the third Network Wide Event took place once again online. Please find the details of the agenda and the activities executed by the consortium in the following post.

To close the development loop of Assurance case (AC), the final task is the generation of evidence to support the claims. The techniques for evidence generation vary with different system development solutions.

Parts of Speech (POS) tagging is a text processing technique to correctly understand the meaning of a text. POS tagging is the process of assigning the correct POS marker (noun, pronoun, adverb, etc.) to each word in an input text. We discuss POS tagging using Hidden Markov Models (HMMs) which are probabilistic sequence models.

The use of machine learning (ML) algorithms is becoming common in safety-critical autonomous systems (AS) such as autonomous vehicles and advanced robotic tasks. These systems are nonlinear and interact with nonlinear (dynamic) environments, resulting in stochastic outcomes. In this post, we introduce how ML is applied to such dynamic systems, more specifically for the autonomous vehicles, and a first discussion ...