Cooperative GNSS positioning aided by road-features measurements

Abstract

Cooperation between road users trough V2X communication is a way to improve GNSS localization accuracy. When vehicles localization systems involve standalone GNSS receivers, the resulting accuracy can be aected by satellite-specic errors of several meters. This paper studies how road-features like lane marking detected by on-board cameras can be exploited to reduce absolute position errors of cooperative vehicles sharing information in real-time in a network. The algorithms considered in this work are based on a error bounded set membership strategy. In every vehicle, a set membership algorithm computes the absolute position and an estimation of the satellite-specic errors by using raw GNSS pseudoranges, lane boundary measurements and a 2D georeferenced road map which provides absolute geometric constraints. As lane-boundary measurements provide essentially cross-track corrections in the position estimation process, cooperation enables the vehicles to improve their own estimates thanks to the dierent orientation of the roads. Set-membership methods are very ecient to solve this problem since they don't involve any independence hypothesis of the errors and so, the same information can be used several times in the computation. Such class of algorithm provides a novel approach to improve position accuracy for connected vehicles guaranteeing the integrity of the computed solution which is pivoting for automated automotive systems requiring guaranteed safety-critical solutions. Results from simulations and real experiments show that sharing position corrections reduces signicantly satellite-specic GNSS errors eects in both cross-track and along-track components. Moreover, it is shown that lane-boundary measurements help reducing estimation errors for all the networked vehicles even those which are not equipped with an embedded perception system.

Set-Membership Position Estimation With GNSS Pseudorange Error Mitigation Using Lane-Boundary Measurements

“…Based on set theory, bounded-error methods can compute a solution set not necessarily of minimum size, but guaranteed to fulfill the integrity risk requirement [3], [17].…”

“…In [3], a cooperative method to improve position estimation accuracy with integrity is presented. This method named Lane Boundary Cooperative Augmented Set-membership GNSS Positioning (LB-CASGP) involves a sensor fusion approach that exploits lane boundary measurements and cooperation between road users through V2X communication to improve both cross-track and along-track vehicle positioning.…”

“…This method named Lane Boundary Cooperative Augmented Set-membership GNSS Positioning (LB-CASGP) involves a sensor fusion approach that exploits lane boundary measurements and cooperation between road users through V2X communication to improve both cross-track and along-track vehicle positioning. In this paper we describe an algorithm called Lane Boundary Augmented Set-membership GNSS Positioning (LB-ASGP), which is a core part of the LB-CASGP approach [3]. By using local sources of information (such as: GNSS raw measurements, digital maps and lane boundary detection), meaning that it does not require V2X communication, the LB-ASGP is able to cope with communication shortage events.…”

Along-track localization for cooperative autonomous vehicles

“…which is the equation of a line. If σ 2 1 < σ 2 2 , then the maximum is reached for ω = 1 which leads to σ 2 = σ 2 1 and x = x 1 . On the contrary, if σ 2 1 > σ 2 2 , then we have σ 2 = σ 2 2 and x = x 2 .…”

Vehicle-to-Vehicle Real-Time Video Transmission through IEEE 802.11p for Assisted-Driving

“…The research lines in driver assistance systems are focused on the vehicular control technologies, and therefore, on the on-board installed sensors, controllers and actuators [2]. Nevertheless, in the recent years, the use of communication links between vehicles, and between them and the cloud network infrastructure to share sensor, actuator and control data is becoming more common [3]- [5].…”