Grass Surrogate

The Need

Road departure is a serious threat to vehicle safety and can result in fatal accidents. To prevent road departure, some vehicles are equipped with a road departure mitigation system that can detect when a vehicle is about to leave the road and take corrective actions. However, there is a need for testing and evaluating system that include a realistic and reliable environment that can simulate various roadside objects, such as grass, which may affect the performance of the vehicle sensors.

The Technology

Ohio State University professor Dr. Chi-Chih Chen, along with a team of researchers, has developed a novel grass surrogate that can mimic the characteristics of natural grass relative to one or more vehicle sensors, such as cameras, radar sensors, or LIDAR sensors. The grass surrogate includes grass blades that are made of a synthetic material and coated with a mixture of high gloss acrylic paint and high reflectance pigments. The grass blades are oriented at an acute angle relative to a base and can exhibit substantially the same visual appearance, radar reflectivity, and radar cross-section as natural grass.

Commercial Applications

The grass surrogate can be used for various commercial applications, such as:

  • Testing and evaluating road departure mitigation systems that rely on vehicle sensors, such as lane keeping assist systems, adaptive cruise control systems, or collision avoidance systems
  • Testing and evaluating autonomous driving systems that use vehicle sensors to navigate the road environment
  • Creating realistic and immersive driving simulators for training purposes


The grass surrogate offers several benefits and advantages over existing solutions, such as:

  • Providing a consistent and reliable testing environment for vehicle sensors under various weather and lighting conditions
  • Reducing the cost and complexity of testing by eliminating the need for natural grass maintenance and replacement
  • Enhancing the accuracy and validity of testing results by replicating the characteristics of natural grass with high fidelity
  • Improving the safety and efficiency of testing by minimizing the risk of damage to vehicles and sensors caused by natural grass

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