Back Home

Zen Automated Driving Simulator (ZEN ADS™)

Zen Automated Driving Simulator (ZEN ADS™)

More Images
ZEN ADS™ is a standalone, versatile, indoor, classroom driver training simulator. The simulator for Light, Medium and Heavy vehicles comes with the option of either left or right hand drive.

The simulator facilitates training in a mock-up vehicle cabin with actual indicators and controls, thereby creating a realistic driving environment. The system is pre-loaded with programs so that the trainee can complete an exercise of choice without an instructor’s presence. The completed exercise can be later accessed for analysis by the trainee and instructor.

The driving training simulator is ideal for institutes imparting basic driver training. A number of simulators can be networked, if so required.

Zen Driver Aptitude Testing System (ZEN DATS™) (Optional)

ZEN DATS™ is a CSIR-approved testing system that enables to check psycho-motor reactions of driver’s reaction, recovery, vision and perception to put safe drivers on the road. The test comprises six tests−Simple Reaction Test, Complex Reaction Test, Depth Perception Test, Night Vision Test, Glare Recovery Test and Side Vision Test.

Key Features

  • No instructor station required to monitor the exercises
  • Various scenarios can be created, saved and assigned to the trainees in the form of courses
  • Trainee can start the assigned exercises, view his own replays and instructor can assess
    the reports later
  • Realistic dashboard assembly and controls, instrumentation and transmission
  • Offers realistic operating environment and ergonomics
  • Intelligent Traffic Models in driving scenes
  • Provides a variety of terrains and driving conditions
  • Environmental conditions like rain, fog, snowfall, intensity of light can be created
  • Progressive training structure increases levels of difficulty for trainees
  • Training can be conducted at multiple stations with different exercises simultaneously
  • Record/playback facility can be used to detect errors and suggest corrective measures