Uncertainty-dependent data collection in vehicular sensor networks

TL;DR

This paper proposes and evaluates data collection algorithms in vehicular sensor networks that leverage uncertainty estimates to optimize data transmission, enhancing traffic control system efficiency.

Contribution

It introduces uncertainty-dependent data collection algorithms specifically designed for vehicular sensor networks to improve communication efficiency.

Findings

Algorithms reduce data transmission by using uncertainty estimates.

Enhanced efficiency in vehicular sensor network data collection.

Potential improvements in traffic control system performance.

Abstract

Vehicular sensor networks (VSNs) are built on top of vehicular ad-hoc networks (VANETs) by equipping vehicles with sensing devices. These new technologies create a huge opportunity to extend the sensing capabilities of the existing road traffic control systems and improve their performance. Efficient utilisation of wireless communication channel is one of the basic issues in the vehicular networks development. This paper presents and evaluates data collection algorithms that use uncertainty estimates to reduce data transmission in a VSN-based road traffic control system.