- Fully integrated with D-LAB and analysis along with other data
- Visualization & data on driving performance in D-LAB
- Live data
GET A HOLISTIC OVERVIEW OF HUMANS BEHAVIOR
With the miniSim simulator system you are optimally equipped for your research purposes. The NADS miniSim™ is a portable, high-performance driving simulator designed for research, development, clinical and training applications. With the integration and the connection of the simulator to our software platform D-LAB you now have the possibility including drivers behavior in your research. You get an adaptable solution for a wide range of applications and achieve best results at a moderate cost level.
Clients interested in evaluating various aspects of driver behavior together with driving performance in a simulated environment. Clients already using NADS miniSim with a need to analyze driving performance during specific tasks.
Driving performance data including speed, steering wheel angle, acceleration, braking, lane position, headway measurement, etc. is streamed into D-LAB for further analysis and correlation with other data such as eye tracking or physiological data. It just needs an update to our software platform D-LAB.
TECH STUFF
MiniSim streams the driving performance data to D-Lab via TCP/IP. The data that are to be streamed into D-Lab are configured via an XML file, along with the IP and port. This “connector” is called D-Link. Our software D-LAB can then visualize the data live, record it synchronously with all other data, and enables analysis and export of the data.
The following data is transferred:
– Speed (mph)
– X-Y location
– Lateral and Longitudinal Acceleration
– Yaw Rate
– Steering Wheel Angle
– Accel Pedal Position (0-1)
– Brake Pedal Force (0-180 lbf)
– Lane position (in feet)
– Headway (if lead vehicle is present)
REQUIRED EQUIPMENT
– D-LAB Connect Module
– miniSim
More information about miniSim can be found here.
APPLICATION EXAMPLES
– Driver distraction testing compliant to NHTSA/AAM guidelines
– Understanding human behavior in the context of autonomous vehicle development
– Using driving performance data to improve HMI design and development
– Analyzing driving performance of patients during rehabilitation
– Gathering data from experienced / professional drivers to train new drivers
