High Accuracy GPS-Free Vehicle Localization Framework via an INS-Assisted Single RSU

Abstract

Collision avoidance and road safety applications require highly accurate vehicle localization techniques. Unfortunately, the existing localization techniques are not suitable for road safety applications as they rely on the error-prone Global Positioning System (GPS). Likewise, cooperative localization techniques that use intervehicle communications experience high errors due to hidden vehicles and the limited sensing/communication range. Recently, GPS-free localization based on vehicle communication with a low cost infrastructure installed on the roadsides has emerged as a more accurate alternative. However, existing techniques require the vehicle to communicate with two roadside units (RSUs) in order to achieve high localization accuracy. In contrast, this paper presents a GPS-free localization framework that uses two-way time of arrival to locate the vehicles based on communication with a single RSU. Furthermore, our framework uses the vehicle kinematics information obtained via the vehicle's onboard inertial navigation system (INS) to further improve the accuracy of the vehicle location using Kalman filters. Our results show that the localization error of the proposed framework is as low as 1.8 meters. The resulting localization accuracy is up to 65% and 47.5% better than GPS-based techniques used without/with INS, respectively. This accuracy gain becomes around 73.3% when compared to existing RSU-based techniques.

Geometry-Based Localization for GPS Outage in Vehicular Cyber Physical Systems

“…The distance is converted into the location of vehicle using the known location of RSUs. An enhancement in RSU based localization has been suggested by reducing the number of RSU requirement from two RSUs to one RSU [15]. Kalman filter has been utilized to enhance the estimated location by fusing range based distance and vehicle's kinematics information.…”

“…Considerable performance degradation in GPS-based localization has been observed in case of GPSoutage 1 in VCPS environments with high rise buildings, multilevel flyovers and different types of road trajectories [16]. This has resulted as the development of infrastructure-based GPS-free localization techniques [11][12][13][14][15].…”

“…GPS-free localization includes received signal strength indicator (RSSI) based localization [11], radio frequency identification (RFID) based localization [12,13], and RSU based localization [14,15]. These GPS-free localizations are based on either radio ranging techniques including RSSI, and Time of Arrival (TOA), or RFID techniques.…”

Localization for mobile sensor network based on unscented Kalman filter with clipping and uncorrelated conversion

“…In the localization of mobile sensor network, the Global Positioning System (GPS)/inertial navigation system (INS) information are generally used, and many algorithms have been proposed, see for example, localization algorithm based on joint distribution stateinformation filter 9 and localization algorithm via an inertial navigation system-assisted single roadside unit. 10 However, the GPS/INS devices are not only expensive but also unreliable in some practical conditions.…”

A time-recordable cross-layer communication protocol for the positioning of Vehicular Cyber-Physical Systems

“…This method poses a novel idea for vehicular positioning, but does not employ a RSU as a base station, despite the fact that the RSU's reference 95 position is usually more precise than that of the mobile vehicle. Meanwhile, a positioning method based on inter-vehicle distance measurements has been proposed to improve the accuracy of position estimation by using the available VANET and existing communication devices in [23]. This method assumes the vehicle can estimate its own position independently, and employs VANET to 100 share the position information to adjacent vehicle.…”