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Scientists Propose a Novel Regional Path Tracking Scheme For Autonomous Ground Vehicles


Carnegie Mellon University's Land Tamer autonomous Unmanned Ground Vehicle.

Researchers at Jilin University in China have proposed a model predictive control algorithm that could track a complex road by monitoring the desired lateral position of the road centerline of autonomous ground vehicles.

Credit: Carnegie Mellon University

Researchers at Jilin University in China have proposed a model predictive control algorithm that could track a complex road by monitoring the desired lateral position of the road centerline of autonomous ground vehicles (AGVs).

The research was designed to overcome the drawbacks of the pure-pursuit tracking method, which may cause collisions when tracking a more complex road while ignoring the size and shape of fully automated vehicles. In addition, the algorithm aims to solve failures due to neglecting the width of the path when using the centerline to describe the desired path.

In the study, the road boundaries and shape of the vehicle are taken into account. To follow the centerline in the given feasible region, the algorithm needs to minimize the difference between the predicted output and the road centerline, and it also must consider the saturation of the mechanical system and ensure that AGVs consume less energy. The road boundaries and saturation of the actuator also are described as constraints.

The new technology consists of an environment perception system and a driving control system. The driving control system runs on a single-board computer handling decision-making, planning, and control, while the environment perception system features lane marking detection and preceding vehicle recognition, which run on two different computers.

From Phys.org
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Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA


 

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