An assessment on the use of stationary vehicles to support cooperative positioning systems

Abstract

In this paper, we evaluate the ability of stationary vehicles (e.g. parked or temporary stopped cars) as tools to enhance the capabilities of existing cooperative positioning algorithms in vehicular networks. First, some real-world facts are provided to support the feasibility of our ideas. Then, we examine the idea in greater details in terms of the technical requirements and methodological analysis, and provide a comprehensive experimental evaluation using dedicated simulations. The routing of a drone through an urban scenario is presented as a non-traditional application case, where the benefits of the proposed approach are reflected in a better utilisation of the flight time

Autonomous Car Parking System through a Cooperative Vehicular Positioning Network

“…Recently, some authors have proposed to use the V2X capabilities of the autonomous cars to design cooperative positioning systems [ 21 , 27 ]. We follow this trend and, similarly in this work, surrounding autonomous cars will be used as anchor nodes in the lateration method.…”

“…For this reason, authors developed cooperative systems where, instead of using RSUs, the surrounding cars are considered as anchor nodes. Examples of cooperative systems can be found in [ 21 , 22 ].…”

Hybrid urban navigation for smart cities

“…These positioning errors, specially those from conventional GPS, cannot be neglected in comparison with the average dimension of a drone (tens of centimeters). As with any traditional GNSS system, 6 the accuracy of GPS can also be greatly affected by atmospheric/environmental conditions, shadowing by buildings, and multipath propagation which is especially problematic in dense urban environments [5], [1]. While there exist different demonstrations of GPS-only (i.e.…”

“…As the GPS readings at this location (solid line in Figure 4)) contain positioning errors of high magnitude, the GPS-only system was unworkable in such an scenario, which provides a stronger justification to the use of our approach. So far, in the steps toward a full proof of concept, we used the whole set of collected GPS data (4 hours of latitude, longitude, and HDOP readings, collected every 10 s) to obtain an improved position estimation by means of a weighted average described in [1]. Thus, every sample i is weighted by the factor λ i given by…”

“…3 The proposed hybrid system of wireless devices could be created by installing elements in the current city environment by either taking advantage of current infrastructure or by adding new sensors to the fleet of vehicles involved in ad-hoc networks. The latter approach, following [1] also enables the possibility of alternative monetization platforms for connected vehicles, with a car owner potentially receiving micro-payments to participate in the network. Providing such a network of collaborative technologies offers a broader coverage of an urban environment.…”