Detailed and reliable data is crucial to ensure the efficient, reliable, and safe operation of future transportation networks. However, the more detailed the information about traffic participants is, the less data privacy regarding individual mobility patterns or identification of individuals is typically guaranteed. This work presents the use of roadside LiDAR sensors for the detection and tracking of vulnerable road users (VRU) and vehicles in a privacy-compliant way based on an exemplary hardware setup. The described data processing approach enables numerous use cases in the fields of, among others, traffic monitoring, control, and safety analysis.
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Detailed and reliable data is crucial to ensure the efficient, reliable, and safe operation of future transportation networks. However, the more detailed the information about traffic participants is, the less data privacy regarding individual mobility patterns or identification of individuals is typically guaranteed. This work presents the use of roadside LiDAR sensors for the detection and tracking of vulnerable road users (VRU) and vehicles in a privacy-compliant way based on an exemplary har...
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