Abstract
The main focus of thesis work addresses one of the functional key points of Cooperative Collision Warning application which is an accurate estimation of the range data of neighboring vehicles during persistent GPS outages under both line-of-sight (LOS) and non-line-of-sight (NLOS) situations. Cooperative Collision Warning, based on vehicle-to-vehicle radio communications and GPS systems, is one promising active safety application that has attracted considerable research interest. One of the severe estimation error is due to NLOS that can be mitigated by applying biased Kalman filter on range measurements. For our algorithm these inter-vehicle distances are measured from using one of the radio-based ranging techniques. Main objective is to establish an accurate map of positions for neighboring vehicles in the persistance of GPS outages. GPS outages can be possible in multipath environments where NLOS component is introduced to the true range measurements. These position estimates mainly depend on two factors: (i) Preprocessed inter-vehicle distances (range data is processed from biased Kalman filter); (ii) Road constraints (the vehicle uncertainty is more in the direction of road than the uncertainty in the direction opposite the road); This thesis suggests smoothing and mitigating the NLOS for radio-based ranging measurements under multipath conditions. In order to find accurate positions of neighboring vehicles an extended Kalman filter is implemented along with road constraints. Unbiased Kalman filter, biased Kalman filter and extended Kalman filter performances are experimentally verified using Matlab simulation tool with random number of vehicles at unknown random distinct positions in some physical region along a section of road for vehicular environment.
Highlights
This chapter provides an overview of the thesis
Automated Highway Systems (AHS): The concept of AHS is based on the belief that an appropriate integration of sensing, communication and control technologies placed on the vehicle and on the highway can significantly decrease the average longitudinal spacing between vehicles and lead to a large improvement in capacity and safety without requiring a significant amount of additional right-of-way which improves the efficiency of automatic control systems for individual vehicles through V2V communication [13], [14]
Relative global positioning systems (GPS) is one of the approach to improve the accuracy in position estimation [24]
Summary
Distance is measured based on the attenuation introduced by the propagation of the signal from Tx to Rx [48). RSS is the least expensive to implement in the cooperative collision warning systems in the vehicular communications as it uses known mathematical channel path loss models, special hardware is not required [49). Distance can be extracted by using free-space large scale path loss models between the vehicles for inter-vehicular LOS distances of less than lOOm. The primary source of error for RSS-based position systems is multipath fading and shadowing. Signal power decays proportional to d- 2 , where d is the distance between the transmitter and receiver. For real-world environment, the mean received power for an obstructed channel decays proportional to d-np, where np is the path-loss exponent (np varies between 2 to 4 depending on the environment). The RSS technique alone is not accurate method, and its adoption is confined to the applications that require coarse ranging
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