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Algorithm May Help Autonomous Vehicles Navigate Narrow, Crowded Streets


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Navigating a narrow two-way street.

The researchers developed a method to model different levels of driver cooperativeness how likely a driver was to pull over to let the other driver pass and used those models to train an algorithm that could assist an autonomous vehicle to safely and efficiently navigate this situation.

Credit: Carnegie Mellon University School of Computer Science

An algorithm developed by researchers at Carnegie Mellon University (CMU) could enable autonomous vehicles to navigate crowded, narrow streets where vehicles traveling in opposite directions do not have enough space to pass each other and there is no knowledge about what the other driver may do.

Such a scenario requires collaboration among drivers, who must balance aggression with cooperation.

The researchers modeled different levels of cooperation between drivers and used them to train the algorithm.

In simulations, the algorithm was found to outperform current models; it has not yet been tested on real-world vehicles.

From Carnegie Mellon University School of Computer Science
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Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

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