Comment équilibrer vitesse et précision dans les systèmes de véhicules autonomes ?

First have to decide the end use for AVS such as, shuttle, truck, taxi, warehouse stacker etc. After that need to define requirements. 1. Define level of autonomous vehicle between 0 & 5 according to SAE. 2. Then check if already there is use case for the requirement and try to built on top of it. 3. Is it for specific area indoor or also outdoor or public road or warehouse. 4. Will it be in all machine and unmanned environment or if there is human interaction then more safety and control features are required. 5. If it need to do repetitive works or the work based on input command everything. 6. Repetitive works can be done faster and requires less sensory for AVS. Whereas, for task based it requires more sensory involvement.

After requirements finalized, next step is to select the methods and then tools for it. 1. Select if the product will be developed in one go or will be put in field and to be updated as per client feedback. 2. For mechanical part of the AVS, need to check if have to use AutoCAD, solid works, Siemens NX, Ansys etc. From my experience Siemens NX along with AutoCAD is best combination. 3. Then come the electrical / electronic parts and for that also need to select tools such as AutoCAD, EPLAN, PSpice, Siemens Edge etc. 4. Similarly the last will be simulation software such as Matlab, Simulink etc. 5. After selection need to check compatibility of softwares with each other to select best possible combination, covering all aspects.

Autonomous Vehicle Systems (AVS) are 100% about safety; all else comes after, including cost. Apply standard engineering principals to the overall AVS design. An engineering rule of thumb is a safety factor of 3. This means redundancy in AVS, b/c it cannot have a single failure. A single failure results in serious injury or fatality. The over-sampling of music data stream over the internet is instructive for AVS systems. The command-stream from AVS systems needs over-sampled also. This pre-supposes a multiply-redundant on-board AVS. A cloud backup for the on-vehicle AVS system is a good practice b\c it can be the last-resort system. Apply Specific standards like ISO 26262 to ensure the highest level of safety. #AVSStandardsPrincipals ☺️

Integrating data from multiple sensors such as cameras. This fusion helps improve accuracy by cross-validating information from different sources. Develop control algorithms that optimize vehicle behavior for both speed and accuracy. These algorithms should balance factors such as acceleration, braking, and steering.

Sensor Fusion: Diversity and redundancy in measurement of spatial position and its derivatives allows for sensor fusion to reduce the uncertainty of these variables. A Kalman filter can also be used to improve accuracy by combining linear predictions and adjusting them using periodic measurements. Optimization: Define the objective functions for optimization of a particular metric. If multiple metrics can be optimized constraints and regularization techniques can be used to establish a best overall compromise. For example, acceleration performance can be optimized within constraints of safety, and operation costs.

To balance speed and accuracy in autonomous vehicle systems, one needs to calibrate the sensors of the vehicle with speed and precision . The sensors of autonomous vehicles include LiDARs, Inertial Measurement Units (IMUs), Cameras, Radars, and more. These sensors collect spatial information around the vehicle, which is then processed by the vehicle’s on-board computer system. The system performs a variety of post-processing tasks, including perception, prediction, and accurate actions like braking at an intersection.