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CoPreMo: A Collaborative Predictive Model in Time Series and its Application to Radar Target Tracking for ADAS/AD Vehicles
  • Zie Eya Ekolle ,
  • Ryuji Kohno
Zie Eya Ekolle

Corresponding Author:[email protected]

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Ryuji Kohno


The use of radar sensors in the detection and ranging of targets is an important technology that plays a leading role in the operation of many modern technologies such as the automotive driving assistant systems (ADAS) and the automated driving (AD) technologies. ADAS/AD are technologies that enable unmanned vehicle control along a trajectory. Some of the challenges of using these technologies in vehicles include the risk of misdirection and collision of the vehicle with an obstacle along its trajectory. To avoid these, many technologies such as radar are being used to detect and track targets and trajectories of ADAS/AD vehicles. In this study, we focus on radar tracking technologies and propose a collaborative predictive model in time series, called CoPreMo, for this purpose. We carried out experiments with the model on a simulated radar system to track the range of a target in an ADAS/AD scenario and achieved a range tracking performance that surpasses those of the presented baseline models.
21 Dec 2023Submitted to TechRxiv
22 Dec 2023Published in TechRxiv