utonomous vehicles are being increasingly adopted in agriculture to improve productivity and efficiency. For an autonomous agricultural vehicle to operate safely, environment perception and interpretation capabilities are fundamental requirements. The Ambient Awareness for Autonomous Agricultural Vehicles (QUAD-AV) project provided a multisensory approach in an autonomous agricultural vehicle with such ambient awareness. The vehicle is mounted with a multisensory array of devices combining different sensor modalities and multi-algorithm approaches that detect the various kinds of obstacles and build an obstacle database that can be used for vehicle control. This project investigated the potential of four technologies: vision/stereovision; light detection and ranging (lidar); thermography; and, microwave radar. A vehicle was developed that is capable of recognising obstacles such as humans, animals, inanimate objects, etc. The use of ambient awareness vehicles will provide additional safety features in agricultural landscapes where humans, machines and other obstacles might be present. The cognitive ability to perceive the environment is, in many cases, a matter of guaranteeing the safety of peopleand animals, and avoiding riskingexpensive machines or causing yield damage.