Accurate Vehicle Localization Research Articles

A Novel approach for Implementing Security over Vehicular Ad hoc network using Signcryption through Network Grid

Security over Vehicular ad hoc network and identifying accurate vehicle location has always been a major challenge over VANET. Even though GPS system can be used to identify the location of the vehicle they too suffer from major drawbacks. A novel approach has been suggested by the author wherein the VANET is made more secured by using Signcryption technique and at the same time unique approach of using Network Grid to flawlessly identify the location of the vehicle has been proposed.

Vehicle Positioning for Improving Road Safety

Vehicle positioning is a key requirement for many safety applications. Active safety systems require precise vehicle positioning in order to assess the safety threats accurately, especially for those systems which are developed for warning/intervention in safety critical situations. When warning drivers of a local hazard (e.g. an accident site), accurate vehicle location information is important for warning the right driver groups at the right time. Global positioning system and digital maps have become major tools for vehicle positioning providing not only vehicle location information but also geometry preview of the road being used. Advances in wireless communication have made it possible for a vehicle to share its location information with other vehicles and traffic operation centres which greatly increases the opportunities to apply vehicle positioning technologies for improving road safety. This paper presents a state‐of‐the‐art review of vehicle positioning requirements for safety applications and vehicle positioning technologies. The paper also examines key issues relating to current and potential future applications of vehicle positioning technologies for improving road safety.

Intervehicle-Communication-Assisted Localization

Vehicle localization is a key issue that has recently attracted attention in a wide range of applications. Navigation, vehicle tracking, emergency calling, and location-based services are examples of emerging applications with a great demand for location information. The Global Positioning System (GPS) has been the de facto standard solution for the vehicle-localization problem. Nevertheless, GPS-based localization is inaccurate and unreliable due to GPS' inherent poor performance in vertical positioning and the prevalent horizontal movement, in addition to anomalies caused by line-of-sight occlusions and multipath issues in urban canyons. Although augmenting GPS localization with inertial sensory data has demonstrated significant performance improvements, there remain situations that give rise to degraded localization accuracy-a deficiency that many applications cannot tolerate. In this paper, we propose intervehicle-communication-assisted localization, a localization technique that takes advantage of the emerging vehicle ad hoc networks environments. Communication among vehicles is utilized to compute a relative vehicle location, the integration of which with motion information and GPS location estimates leading to highly accurate vehicle localization. This proposed localization technique is tested in various simulated road-segment scenarios. It is evident from the simulation results that intervehicle communication has the potential to lead to the improvement of the robustness and accuracy of vehicle-location estimation.

A Hidden Markov Model-Based Map-Matching Algorithm for Wheelchair Navigation

Application of map-matching techniques to GPS positions can provide accurate vehicle location information in challenging situations. The Hidden Markov Model (HMM) is a statistical model that is well known for providing solutions to temporal recognition applications such as text and speech recognition. This paper introduces a novel map-matching algorithm based on HMM for GPS-based wheelchair navigation. Given GPS positions, a hidden Markov chain model is established by using both geometric data and the topology of sidewalk segments. The map-matching algorithm employs the Viterbi algorithm to estimate correct sidewalk segments as hidden states in a HMM in order to match GPS trajectory on the corresponding segment sequence. The HMM-based map-matching algorithm was validated on a campus sidewalk network for wheelchair navigation. The results show an improvement in tracking a wheelchair in dense urban conditions both in accuracy and in computational time.

A Map Matching Method for GPS Based Real-Time Vehicle Location

Accurate vehicle location is essential for various applications in the field of intelligent transportation systems (ITS). Existing vehicle location systems rely on multiple positioning sensors and powerful computing devices to execute complex map matching algorithms. There exists a strong need for exploring a solution for vehicle location that relies on a GPS receiver as the sole means of positioning and does not require complex computations. Towards this end, the error characteristics of the GPS signal were studied through the analysis of GPS data collected during test drives. Based on the inferences drawn and a simple fuzzy rule set, a novel yet simple map matching algorithm was developed. Due to the difficulties in testing the algorithm through on-road trials, a simulation environment that is capable of reproducing the field conditions in the laboratory was developed. Simulation results confirm that the proposed algorithm overcomes many of the inadequacies of the existing methods and is capable of achieving high accuracy with minimal computational requirements.

An Optical Localization System for Mobile Robots Based on Active Beacons

The standard method for controlling the trajectories of AGVs in industrial applications is based on wire-guide systems. It is robust but it lacks a flexible and economical localization svstem which is essential for the development of intelligent navigation capabilities and the evolution of AGVs to cooperating autonomous agents. This paper describes an active localization system developed for indoor applications that allows an accurate localization of mobile vehicles in static and dvnamic operation. Simulations and experimental results with a prototype implementation are described.