Smarter and safer automated driving

Hi-tech driver assistance systems being developed by EU-funded researchers aim to perfect the link between human and machine in self-driving cars. This could help prevent accidents and fatalities on Europe's roads.

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Countries
Countries
  Algeria
  Argentina
  Australia
  Austria
  Bangladesh
  Belarus
  Belgium
  Benin
  Bolivia
  Bosnia and Herzegovina
  Brazil
  Bulgaria
  Burkina Faso
  Cambodia
  Cameroon
  Canada
  Cape Verde
  Chile
  China
  Colombia
  Costa Rica
  Croatia
  Cyprus
  Czechia
  Denmark
  Ecuador
  Egypt
  Estonia
  Ethiopia
  Faroe Islands
  Finland
  France
  French Polynesia
  Georgia


  Infocentre

Published: 3 June 2019  
Related theme(s) and subtheme(s)
Industrial researchIndustrial processes & robotics
Information society
Innovation
Research policyHorizon 2020
TransportRoad
Countries involved in the project described in the article
Belgium  |  France  |  Germany  |  Greece  |  Ireland  |  Italy  |  Netherlands  |  Spain  |  Sweden  |  Switzerland
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Smarter and safer automated driving

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© pavelvinnik #243439695, 2019 source: stock.adobe.com

Automated driving is soon set to change the way we drive, but its success depends – in large part – on how effectively this cutting-edge technology links to the living, breathing person behind the steering wheel.

If that link can be perfected, then it could herald a future in which human errors are compensated for by intelligent software, leading to safer trips and more efficient road usage for all vehicle types.

Enter the EU-funded ADASANDME project. Its partners are working together to take everything we know about automated driving and combine that with emerging knowledge of how to predict and detect key factors affecting a driver’s state – such as fatigue, stress, inattention, fear and fainting – in various situations.

By developing advanced driver assistance systems, ADASANDME’s work aims to ensure that vehicles can switch safely and reliably back and forth between human drivers and automation modes.

‘Regardless of what vehicle you drive, you’ll suffer from being impaired now and then,’ says ADASANDME project coordinator Anna Anund of VTI, the Swedish National Road and Transport Institute. ‘But our challenge is to only return control to a driver who has been under automation if that driver is fit to take over. At the same time, we need to make sure the driver benefits from this – to make sure that drivers are more rested and less stressed.’

Trucks, bikes and automobiles

With the analysis of drivers’ needs and the current state of the technologies now complete, the remainder of the project will see the ADASANDME team focusing on seven key areas to identify, clarify and organise the requirements of the systems. These areas are:

  • driver inattention in long-haul trucking;
  • electric car range anxiety;
  • smooth, safe automation transitions in cars;
  • emergency manoeuvres in cars for when a driver does not react;
  • driver inattention when long range touring on motorbike;
  • rider fainting on motorbikes;
  • passenger pick-up/drop-off automation for buses.

The researchers are developing robust detection and prediction algorithms to monitor different driver conditions, using both existing and novel sensing technologies that will take traffic and weather conditions into account. They are also working to personalise these systems so that they can be tailored to the physiology of the driver and his or her typical driving behaviour.

Ultimately, the newly developed human-machine interfaces and automation systems will be evaluated with a range of drivers with real vehicles, on real roads, to ensure they can accurately detect when the driver is unable to drive safely, take control, and avoid danger.

Towards the end of the project, the team will be checking that the advanced driver assistance systems will be able to accurately recognise the driver’s condition and offer clear information to the driver. The researchers will also be investigating the extent to which drivers trust and accept the system, how they react to system warnings and suggestions, and collecting their opinions on its use.

Market potential

‘There are several innovations in our project, ranging from new driver state detection algorithms based on physiological signals and eye trackers adapted for automation, to new, more effective human-machine interfaces,’ says Anund.

There is plenty of market potential for technologies developed over the course of the project. For example, sensor and algorithm developers are working on a number of innovations that are likely to be strong candidates for commercialisation in the near future.

Project details

  • Project acronym: ADASANDME
  • Participants: Sweden (Coordinator), Germany, Greece, Italy, Switzerland, Netherlands, France, Spain, Ireland, Belgium
  • Project N°: 688900
  • Total costs: € 9 609 700
  • EU contribution: € 8 998 950
  • Duration: September 2016 to February 2020

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