Assessing vehicle fuel economy in real-world driving conditions is a critical requirement to
establish a reliable baseline when evaluating driver assistance systems or autonomous …

Driving simulation is becoming an increasingly important component of research and
development in the automotive industry. When performing simulator studies in urban …

In this chapter, we present the concept of an integrated multi-agent simulation platform to
support the development and validation of autonomic cooperative car-to-car systems. The …

Connectivity and automation have accelerated the development of algorithms that use route
and real-time traffic information for improving energy efficiency. The evaluation of such …

This demonstration presents the integrated multi-agent traffic simulation for human-in-the-
loop cooperative drive systems testing. Its openness and flexibility supports a wide range of …

Increasing cost of fuel and global regulatory targets are driving the automotive industry
towards fuel efficient vehicles. Hybrid electric vehicles (HEVs) can significantly improve the …

While emerging technology for self-driving automation in vehicles progresses rapidly, the
transition to an era of roads full of fully connected and automated vehicles (CAVs) may take …

Millions of people are killed every year in road accidents, caused mostly by human errors.
Therefore, it is of paramount importance to support the driver by improving the interaction …

Cognitive distraction during the driving task might cause impairment of detection
performance and of the recognition and/or response selection, increasing the risk of road …

We demonstrate how AgentDrive platform can be used to develop agent-based driver
assistance systems. We expect that new V2X technologies penetrating automotive industry …