Various Road User Charging (RUC) mechanisms are used to control the traffic and its resulting pollution, as well as revenue sources for reinvestment in the road infrastructure. Among them, Electronic Toll Collection (ETC) systems based on user positions estimated with Global Navigation Satellite Systems (GNSS) are particularly attractive due to their flexibility and reduced roadside infrastructure in comparison to other systems like tollbooths. Because GNSS positioning may be perturbed by different errors and failures, ETC systems, as liability critical applications, should monitor the integrity of GNSS signals in order to limit the use of faulty positions and the consequent charging errors. The integrity monitoring systems have been originally designed for civil aviation, so they need to be adapted to the ETC requirements. This paper studies the use of Receiver Autonomous Integrity Monitoring (RAIM), which are algorithms run within the GNSS receiver, and therefore easier to tune to ETC needs than other systems based on external information. The Weighted Least Squares Residuals (WLSR) RAIM used in civil aviation is analyzed, and an algorithm modification for ETC is proposed. Simulations demonstrate that the proposed RAIM algorithm has a superior level of availability over civil aviation based RAIM procedures, particularly in urban environments.

Certain GNSS applications conceived for road users in urban scenarios must meet some particular integrity requirements to assure the system safety, reliability or credibility. For instance, GNSS-based Road User Charging is one of these applications that recently has attracted special interest. A correct design of such applications needs the knowledge of the GNSS error distribution. Furthermore, the GNSS error model should have been built with overbounding techniques. The user is a vehicle equipped with a GNSS receiver that may track different signals of various systems (GPS, Galileo, SBAS), in a single-or dual-frequency configuration. The different error sources contributing to the total pseudorange error are identified, analyzed and modeled, using overbounding techniques when necessary. Finally the pseudorange measurement error model is obtained and analyzed for different receiver configurations.

International audienceThis study presents a review of the state-of-the-art and a novel classification of current vision-based localisation techniques in unknown environments. Indeed, because of progresses made in computer vision, it is now possible to consider vision-based systems as promising navigation means that can complement traditional navigation sensors like global navigation satellite systems (GNSSs) and inertial navigation systems. This study aims to review techniques employing a camera as a localisation sensor, provide a classification of techniques and introduce schemes that exploit the use of video information within a multi-sensor system. In fact, a general model is needed to better compare existing techniques in order to decide which approach is appropriate and which are the innovation axes. In addition, existing classifications only consider techniques based on vision as a standalone tool and do not consider video as a sensor among others. The focus is addressed to scenarios where no a priori knowledge of the environment is provided. In fact, these scenarios are the most challenging since the system has to cope with objects as they appear in the scene without any prior information about their expected position

GNSS-based Road User Charging (RUC) systems are particularly interesting because of their flexibility and reduced roadside infrastructure. At present, truck toll collection systems based on GPS receivers installed on the vehicles are already deployed in German and Slovak motorways. Reliability of road tolling systems is fundamental in order to limit the loss of revenue because of undercharging and the user claims because of overcharging. Consequently, GNSS integrity monitoring plays a key role in such systems, providing trustful positioning data that keep position errors and their associated legal or economical consequences within given limits. Nevertheless, the design of GNSS integrity algorithms like RAIM requires a deep knowledge of the characteristics of the application and GNSS errors. This paper analyzes the required parameters to develop RAIM algorithms for road tolling applications in urban and rural environments.

The use of GNSS for critical terrestrial applications requires adapted integrity monitoring algorithms for either safety or liability issues. Prior to the design of integrity monitoring algorithms, it is necessary to characterize the nominal error model of every error source affecting the pseudorange measurements. This paper focuses on describing a way to calculate the contribution of the multipath to the nominal error model by a set of simulations based on an urban channel model and a realistic GNSS tracking loop simulator. To improve the accuracy of the positioning, multipath mitigation techniques are usually implemented in the receivers. This paper assesses the performances of the Narrow Correlator, the Double-Delta and the A Posteriori Multipath Estimation techniques in an urban environment and provides their multipath residual nominal error model as a function of the satellite elevation angle. A relationship between quality monitoring indicators and the multipath estimation technique (APME) is also discussed. The results of this paper are obtained by simulating an actual urban railway environment and therefore can be taken as inputs for the design of GNSS integrity monitoring algorithms for rail users. The same approach can be used for the determination of the nominal error model for other terrestrial application subject to simulating an adapted channel.