Satellite-based navigation systems, such as Global Positioning System (GPS) or Galileo, are the most common and accessible techniques for vehicle positioning. However, in dense urban areas, even if combined with vehicle on-board sensors, they lead to large localization errors due to multipath and signal blockage. In recent years, Cooperative Intelligent Transportation Systems (C-ITSs) have gained increasing attention as they allow vehicles to cooperate and broadcast safety-related information to the neighbors through Vehicle-to-Vehicle (V2V) communications. In this paper, a novel cooperative positioning method is developed by exploiting V2V communications without using explicit V2V ranging. Vehicles localize, in a distributed way, a set of jointly sensed non-cooperative features (e.g., people, traffic lights) and use them as common noisy reference points to implicitly enhance their own position accuracy. Distributed belief propagation is combined with consensus-based estimation of the features' positions to enable cooperative localization of vehicles. Numerical results show that the proposed method is able to significantly enhance the GPS-based vehicle location accuracy, especially in scenarios with dense feature deployments.

Enhanced vehicle positioning in cooperative ITS by joint sensing of passive features

Soatti, Gloria;Nicoli, Monica;
2017

Abstract

Satellite-based navigation systems, such as Global Positioning System (GPS) or Galileo, are the most common and accessible techniques for vehicle positioning. However, in dense urban areas, even if combined with vehicle on-board sensors, they lead to large localization errors due to multipath and signal blockage. In recent years, Cooperative Intelligent Transportation Systems (C-ITSs) have gained increasing attention as they allow vehicles to cooperate and broadcast safety-related information to the neighbors through Vehicle-to-Vehicle (V2V) communications. In this paper, a novel cooperative positioning method is developed by exploiting V2V communications without using explicit V2V ranging. Vehicles localize, in a distributed way, a set of jointly sensed non-cooperative features (e.g., people, traffic lights) and use them as common noisy reference points to implicitly enhance their own position accuracy. Distributed belief propagation is combined with consensus-based estimation of the features' positions to enable cooperative localization of vehicles. Numerical results show that the proposed method is able to significantly enhance the GPS-based vehicle location accuracy, especially in scenarios with dense feature deployments.
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)
978-1-5386-1526-3
Global Positioning System, Iterative closest point algorithm, Sensors, Noise measurement, Vehicular ad hoc networks, Distance measurement
File in questo prodotto:
File Dimensione Formato  
CV_2017_ITSC.pdf

Accesso riservato

Descrizione: Full paper
: Publisher’s version
Dimensione 1.41 MB
Formato Adobe PDF
1.41 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1048567
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? 3
social impact