ATHENA is a garage project of AETHON aimed at reinventing the way we interact and communicate with our vehicle. In today’s non-automated vehicles, the interaction is simple, press the pedal – it accelerates, turn the wheel – it turns. But what happens in the vehicle of tomorrow, when automation gives your hands the opportunity to wander off and do something else besides grabbing the wheel?

It is simple, one might say, if something happens or I want the car to stop, I regain control simply by grabbing the wheel. That is true, it is possible, but there can be multiple unforeseen problems:

  • Drivers of automated vehicles regain control in a consistent and stabilized manor after around 40 sec (Merat et al., 2014)
  • Another study showed that drivers can take from 2 to more than 25 seconds to regain control, which is a significant time frame especially at high speed. Also, researchers noted that “Significantly longer control transition times were found between driving with and without secondary tasks” (Eriksson & Stanton, 2017)


This is only the tip of the iceberg. Automated cars are only starting to appear. In full automation we would not need to take control; vehicles got it covered for us. But then, what is the necessity for having a wheel? How will we communicate with the vehicle?

The Society for Automotive Engineers has developed a standard of 5 automation levels. Level 0 is no automation while level 5 is complete automation. This standard, also adopted by NHTSA (National Highway Traffic Safety Administration, USA –, states that at level 4 and level 5, driver intervention becomes optional. This means that drivers will cease to exist, no wheel or formal driving training will be required. However, interaction between the “passenger” and the vehicle, cannot cease to exist. We need to tell our car where to go and how to get there, make stops if necessary or if we wish to. We should not only be talking about smart and autonomous vehicles but also for informed and empowered operators that will replace the driver concept. Athena aims to empower those operators with voice control.

Athena Concept

Voice control will help us communicate “natural commands”, such as, make a stop after the blue car, and will help us maneuver under various conditions, translating our voice commands to vehicle movement and control. Athena is an AI that makes the translation: it receives the command from the driver and transmits it to the automated vehicle’s system. It does not blindly make a left when the driver requests it, but lets the vehicle know that the driver wants to make a left, leaving the car to decide when its safe. This is a new level of vehicle-machine interaction, a new Human-Machine Interface. It also learns about us as we speak, using Machine Learning and Natural Language Recognition for understanding and improving the commands. Most importantly though, Athena translates those commands to valid vehicle movement, understands complicated maneuvers and requests the vehicle to perform them ensuring that the driver does not become a passenger but an operator, empowering and reinventing the interface of future vehicles.

Short Demo

The automated vehicle is depicted with a red dot. At the end (right side) of the middle lane there is a segment of very low speed limit (~5km/h). “Human” vehicles (in green) choose to change lane to avoid the segment but the automated vehicle will not change lane without a human giving the command. The demo aims to show how Athena will operate in a simple yet relevant example.

* Simulation software provided by Technical University of Delft (
** Voice transcription (Speech-to-Text) is powered by Watson, IBM (
*** Automated vehicles’ movement: Longitudinal driving model by Papacharalampous et al. (2015)

MoveWise-Research (MW-R)

MoveWise-Research (MW-R)



This proposal for the project MoveWise-Research (MW-R) is submitted for the call INNOSUP-02-2016 “SME Innovation Associate”. AETHON requests to hire a post-doctoral researcher with sufficient academic experience on transportation engineering, data analytics, behavioural analysis and IT programming for the purpose of performing a proof-of-concept research (TRL 5 – development of model/algorithm) on modelling tours incorporating user feedback. The key objective of the MW-R project is to develop a model/algorithm for planning of tours and trips in real time incorporating user preferences and data on traffic obtained from public (and open) sources. The model will be created by using data from public transport authorities in Greece and by performing a small scale survey to obtain user feedback on trips. By achieving the MW-R goal, the model will be able to change the perspective of travellers by providing targeted information about planned routes that will improve mode, route, time of departure and destination choice. AETHON aims to incorporate the model in a smartphone application and to gain knowledge on transportation behavioural analysis that can be used in multiple professional activities.

Role of AETHON

AETHON is the coordinator of the project.

Project Information

Duration: 29/9/2017 to 28/9/2018 (12 months)

Budget: €64,243.8

Project link

Public Results

Questionnaire Survey Results: View pdf

You’ll find above the results of the first part of the questionnaire survey performed by AETHON during March 2018 (more information here:

Presentation of project results: View pdf

Y’ll find above the presentation summarizing mathematical modeling activities in the MW-R project

Open Publication for the project:

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 739607.

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