Integrity-Based Path Planning Strategy for Urban Autonomous Vehicular Navigation Using GPS and Cellular Signals

TL;DR

This paper presents an integrity-based path planning method for urban autonomous vehicles that integrates GPS and LTE signals, optimizing for safety and efficiency by considering signal integrity and environmental factors.

Contribution

It introduces a novel path planning strategy that accounts for signal faults and integrity levels using simulated pseudoranges in complex urban terrains.

Findings

Optimal paths have the lowest average horizontal protection level (HPL).

The strategy effectively predicts and avoids faulty signal zones.

Simulation results validate the approach's effectiveness in urban environments.

Abstract

An integrity-based path planning strategy for autonomous ground vehicle (AGV) navigation in urban environments is developed. The vehicle is assumed to navigate by utilizing cellular long-term evolution (LTE) signals in addition to Global Positioning System (GPS) signals. Given a desired destination, an optimal path is calculated, which minimizes a cost function that considers both the horizontal protection level (HPL) and travel distance. The constraints are that (i) the ratio of nodes with faulty signals to the total nodes be lower than a maximum allowable ratio and (ii) the HPLs along each candidate path be lower than the horizontal alert limit (HAL). To predict the faults and HPL before the vehicle is driven, GPS and LTE pseudoranges along the candidate paths are generated utilizing a commercial ray-tracing software and three-dimensional (3D) terrain and building maps. Simulated pseudoranges inform the path planning algorithm about potential biases due to reflections from buildings in urban environments. Simulation results are presented showing that the optimal path produced by the proposed path planning strategy has the minimum average HPL among the candidate paths.