Skip to main content

TRL's DigiCar driving simulator becomes fully automated

As the path to acceptance of automated vehicles on the UK’s roads moves forward, so does TRL’s role in developing robust research tools to provide the necessary evidence as to the human response to automation and its general acceptance by the driving population. Behind the scenes, TRL experts have been working on developing the software required to enable the transition of DigiCar to run as an automated vehicle as and when required. As a result, TRL’s full mission driving simulator, DigiCar, has devel
November 18, 2014 Read time: 2 mins
As the path to acceptance of automated vehicles on the UK’s roads moves forward, so does 491 TRL’s role in developing robust research tools to provide the necessary evidence as to the human response to automation and its general acceptance by the driving population.

Behind the scenes, TRL experts have been working on developing the software required to enable the transition of DigiCar to run as an automated vehicle as and when required.

As a result, TRL’s full mission driving simulator, DigiCar, has developed into a partially or fully automated vehicle.

DigiCar provides the transport sector with a sophisticated research tool to understand driver behaviours and reactions to environments both within the vehicle itself and outside. Offering a totally safe driving experience, DigiCar provides a platform for repeatable testing, gathering accurate data for analysis and dissemination, enabling Governments, manufacturers and others to make informed decisions regarding the introduction of vehicle automation.

Dr Nick Reed, Principal Human Factors researcher at TRL and vehicle automation expert said:  “We are delighted to have completed this development using a flexible web-based platform to enable partial or full automation of DigiCar. This opens the potential for a range of studies to investigate how automation of the driving task will affect driver behaviour and how transitions between vehicle automation modes are understood by drivers.

For more information on companies in this article

Related Content

  • Urban mobility and demand management - the Mobility Credits Model
    January 26, 2012
    Vito Marcolongo and Marco Troglia, Quaeryon srl describe the Mobility Credits Model, which is intended to combine inducements and fairness to improve mobility while reducing its more negative economic and environmental effects
  • Ettifos to show Sirius, its software-defined modem C-V2X platform
    April 24, 2025

    As the push for intelligent transportation systems accelerates, cellular Vehicle-to-Everything (C-V2X) technology is set to revolutionize vehicle communication for connected mobility and smart city deployments.

    However, developing, testing, and optimising V2X applications requires a robust, flexible solution that accommodates real-world field testing and real-time communication.

    Ettifos, V2X solutions provider, will be in Seville exhibiting Sirius, its Software-defined Modem (SDM) C-V2X platform, which provides just that.

  • Level 4/5 autonomous driving will be possible in the next five years, says research
    May 9, 2017
    Growing consumer preference for convenience-enhancing technologies and automobiles-as-a-service options helped double the adoption of vehicles with automated driving features in 2016, says Frost & Sullivan’s mobility team. Going forward, large-scale investments from original equipment manufacturers (OEMs) will refine the use of artificial intelligence (AI) and cognitive cloud-based technology solutions even further, enabling level 4/5 autonomous driving within the next five years. Retrofitted automated driv
  • Inrix informs FHWA’s data improvements
    December 19, 2017
    Refinements in the data available from the US Federal Highway Administration will improve road management across America. David Crawford reports. In August 2017, the US Federal Highway Administration (FHWA) issued the first results from an upgraded version of its National Performance Management Research Data Set (NPMRDS). Developed to identify the locations and times of high congestion affecting traffic flows along America’s 259,000km (161,000 mile) national highway system, this is a key resource for sta