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In order to drive autonomously and safely, self-driving cars always need to be focused on their surroundings and their interiors with the aid of their sensors (“Sense”).
Cameras, radar, ultrasonic and lidar sensors are the eyes and ears of an automated car and supply all the information required by the vehicle to perceive its entire surroundings. Additional sensors are even aligned inward into the passenger compartment, enabling the system to make autonomous decisions as to whether the driver is capable of taking control of the vehicle again if necessary.
But automated cars are aware of even more than their immediate surroundings: using up-to-date, high-resolution digital maps and connected real-time data from the cloud, the vehicle can also access external information such as traffic or weather data. Taken together, the vehicle therefore avails of a solid basis of information for the smart vehicle computer, which uses it for exact calculations. For a safe and relaxing drive in a self-driving car.
Using sensory data of the car’s surroundings, automated vehicles can detect critical situations faster and avoid them better than human drivers.
Automated vehicles can detect monotonous situations like traffic jams and take over the driving task. Thus, drivers reach their destination more relaxed.
The front camera detects and categorizes objects and other road users, traffic signs as well as road markings robustly and reliably and ensures a holistic understanding of the scene. Near-range cameras additionally generate a three-dimensional image of the immediate vehicle‘s surroundings.
Ultrasonic sensors emit short ultrasonic pulses that are reflected by obstacles (echo sounder principle). This enables a very fast and robust object detection. Due to their rather small range, the sensors are used in close range, especially for parking.
The lidar (light detection and range) sends out laser pulses and calculates the distance to objects and other road users early and reliably based on the time required by the backscattered laser light - thanks to high resolution at a long range and a wide field of view.
The front, rear or side mounted radar uses radio waves to detect the precise position, relative speed and direction of movement of objects in almost all weather conditions, in darkness and in tunnels with just one measurement based on the time it takes for the waves to return.
The front camera detects and categorizes objects and other road users, traffic signs as well as road markings robustly and reliably and ensures a holistic understanding of the scene. Near-range cameras additionally generate a three-dimensional image of the immediate vehicle‘s surroundings.
Ultrasonic sensors emit short ultrasonic pulses that are reflected by obstacles (echo sounder principle). This enables a very fast and robust object detection. Due to their rather small range, the sensors are used in close range, especially for parking.
The lidar (light detection and range) sends out laser pulses and calculates the distance to objects and other road users early and reliably based on the time required by the backscattered laser light - thanks to high resolution at a long range and a wide field of view.
The front, rear or side mounted radar uses radio waves to detect the precise position, relative speed and direction of movement of objects in almost all weather conditions, in darkness and in tunnels with just one measurement based on the time it takes for the waves to return.
But what’s happening around the vehicle? One requirement for automated driving involves reliable and precise perception of the surroundings. As the vehicle is required to move autonomously in real traffic situations, it must be able to detect and localize all relevant road users within the entire vehicle environment (360 degrees). This entails several sensors applying various surveying principles to monitor each area of the vehicle’s surroundings. This redundancy improves the reliability and stability of information. Most of the sensors required for these tasks are already in volume production today. For example, partially automated systems are already available which support drivers in difficult situations. These include remote park assist , garage park assistant , home zone park function or Bosch driving assist . In specific cases radar, video and ultrasonic sensors are not sufficient to deliver plausible data of two sensors constantly. Only the parallel use of several sensor principles ensures that automated driving is as safe as possible.
Which is why Bosch is working on new sensor technologies like the long-range lidar to meet the high demands on surroundings perception. The data provided by individual sensors are combined . This fusion increases the measuring range and improves the reliability and accuracy of the measurements. The different measuring principles are used to confirm all static and dynamic objects and are processed to a comprehensive environment model. This makes assisted and automated driving even safer and more comfortable. For example, the data fusion of radar, camera and lidar allows narrow silhouettes and plastic cladding to be detected even more reliably, speed limits detected by the camera are incorporated into the driving strategy by the radar sensor technology, and more complex parking maneuvers are not only made possible and simplified by the data fusion of ultrasonic sensors and close-range camera, but also made safer and more comfortable.
A basic requirement for highly and fully automated driving is represented by vehicle localization which must be both exact and constantly available. A single sensor is unable to fulfill these requirements which is why a combination of surround sensors (for detecting landmarks such as lane markings and buildings) with satellite navigation and correction service as well as inertial sensors and a digital map is used. High-definition digital maps are used for this purpose which contain far more layers of information than the maps for standard sat-nav devices. They also support the automated vehicle in planning individual driving maneuvers, e.g. whether the vehicle should change lanes or not. Through connectivity with the cloud, the data contained in the maps are constantly updated enabling inclusion of dynamic factors such as temporary closed lanes in travel plans. For the so-called road signature , Bosch has developed a pioneering solution for creating key parts of high-definition maps using vehicles’ radar and video sensors, literally as they drive by.
Information on current road conditions is also required by automated vehicles in order to detect potential dangers at an early stage and to ensure safety during driving. For these innovative road condition services, Bosch uses weather data supplied by its partner Foreca in a first expansion stage, in order to draw conclusions about possible hazards such as aquaplaning, ice or snow. Automated cars can then adapt their driving behavior to the respective conditions, choose a different route or ask the driver to take control if a safe onward journey cannot be guaranteed in automated mode.
In the future, Bosch will be supplementing its predictive road condition services to include data from the vehicle. What inside and outside temperatures are measured by the car? Are the wipers activated? Connectivity means that such information does not stay unused in the vehicle but reaches the cloud through the respective manufacturer’s backend. Bosch also evaluates the control interventions by the ESP® skid protection system in order to determine the friction value and condition of the road surface. All data combined and evaluated intelligently result in a smart Bosch service – and a feeling of safe automated driving.
Highly and fully automated functions need to monitor the driver as well as the vehicle’s surroundings. After all, drivers are not obliged to monitor the system when these functions are in operation. They can pass full control to the system, at least for a certain period of time or for a defined situation, after which the driver is requested to take control of the driving task – and the vehicle must be able to detect if the driver is capable of doing so. Bosch has already developedinterior monitoring systems which constantly monitors the driver and the other car passengers, reminds all occupants to fasten the seatbelt, deactivates the airbag if a child safety seat is present and issue warnings in dangerous situations such as fatigue or microsleep.
The system passing driving responsibility to the driver remains a challenge for engineers. How is the driver informed, how long does the driver need to take over? What happens if the driver does not take control? One possible scenario: If the driver fails to take over, even after multiple alerts, as the car approaches a freeway exit, the automated vehicle would stop autonomously on the hard shoulder.
Automated vehicles must have three fundamental skills: They need to perceive and interpret (Sense) their surroundings, use this information to make forecasts and derive a suitable driving strategy (Think), and then implement it reliably and safely (Act). Sensing the immediate environment is the task of the surround sensors which combines camera, radar and ultrasonic. Vehicle intelligence enabling it to interpret its surroundings and find the optimal driving strategy is made possible by software and algorithms which use the information gleaned from sensors as well as data from other connected systems.
Systems such as the powertrain, steering and brakes ensure that the respective driving strategy is then implemented on the road. This process of sensing, thinking and acting takes place during the entire journey. When applied to human beings, this process is similar to constant interactions in the body during which the sensory organs pick up stimuli which are processed by the brain before the nerve pathways, muscles and limbs implement the brain’s control signals as actions.
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