Generalized Evidence Theory

Conflict management is still an open issue in the application of Dempster Shafer evidence theory. A lot of works have been presented to address this issue. In this paper, a new theory, called as generalized evidence theory (GET), is proposed. Compared with existing methods, GET assumes that the general situation is in open world due to the uncertainty and incomplete knowledge. The conflicting evidence is handled under the framework of GET. It is shown that the new theory can explain and deal with the conflicting evidence in a more reasonable way.Comment: 39 pages, 5 figure

Robust Report Level Cluster-to-Track Fusion

In this paper we develop a method for report level tracking based on Dempster-Shafer clustering using Potts spin neural networks where clusters of incoming reports are gradually fused into existing tracks, one cluster for each track. Incoming reports are put into a cluster and continuous reclustering of older reports is made in order to obtain maximum association fit within the cluster and towards the track. Over time, the oldest reports of the cluster leave the cluster for the fixed track at the same rate as new incoming reports are put into it. Fusing reports to existing tracks in this fashion allows us to take account of both existing tracks and the probable future of each track, as represented by younger reports within the corresponding cluster. This gives us a robust report-to-track association. Compared to clustering of all available reports this approach is computationally faster and has a better report-to-track association than simple step-by-step association.Comment: 6 pages, 5 figure

The total belief theorem

In this paper, motivated by the treatment of conditional constraints in the data association problem, we state and prove the generalisation of the law of total probability to belief functions, as finite random sets. Our results apply to the case in which Dempster’s conditioning is employed. We show that the solution to the resulting total belief problem is in general not unique, whereas it is unique when the a-priori belief function is Bayesian. Examples and case studies underpin the theoretical contributions. Finally, our results are compared to previous related work on the generalisation of Jeffrey’s rule by Spies and Smets

A novel intelligent vehicle risk assessment method combined with multi-sensor fusion in dense traffic environment

Purpose - The purpose of this paper is to accurately capture the risks which are caused by each road user in time. Design/methodology/approach - The authors proposed a novel risk assessment approach based on the multi-sensor fusion algorithm in the real traffic environment. Firstly, they proposed a novel detection-level fusion approach for multi-object perception in dense traffic environment based on evidence theory. This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was accurately obtained. Then, they conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated. The prediction steering angle and trajectory were considered in the determination of traffic risk influence area. Findings - The results of multi-object perception in the experiments showed that the proposed fusion approach achieved low false and missing tracking, and the road traffic risk was described as a field of equivalent force. The results extend the understanding of the traffic risk, which supported that the traffic risk from the front and back of the vehicle can be perceived in advance. Originality/value - This approach integrated four states of track life into a generic fusion framework to improve the performance of multi-object perception. The information of object type, position and velocity was used to reduce erroneous data association between tracks and detections. Then, the authors conducted several experiments in real dense traffic environment on highways and urban roads, which enabled them to propose a novel road traffic risk modeling approach based on the dynamic analysis of vehicles in a variety of driving scenarios. By analyzing the generation process of traffic risks between vehicles and the road environment, the equivalent forces of vehicle–vehicle and vehicle–road were presented and theoretically calculated

Use of Evidence theory for the fusion and the estimation of relevance of data sources : application to an alcoholic bioprocess

In this paper, we present an application of the evidence theory for the classification of physiological states in a bioprocess. We are particularly interested by the relevance of the data sources which are here biochemical parameters measured during the bioprocess. The evidence theory, and more particularly the notion of conflict is used to evaluate the relevance of each data source. An other measure of conflict, based on a distance, is also used, and provides in some cases, better results than the classical notion of conflict of the evidence theory. Results are presented for two kinds of bioprocesses : batch process (which corresponds to a supervised classification) and fed-batch process (which corresponds to an unsupervised classification).Dans cet article, nous présentons une application de la théorie des fonctions de croyance pour la classification d’états physiologiques dans un bioprocédé. Nous nous intéressons surtout à la pertinence des sources d’informations qui sont ici des paramètres biochimiques mesurés durant le procédé. La théorie des fonctions de croyance, et plus particulièrement la notion de conflit est utilisée pour évaluer la pertinence de chaque source d’information. Une autre mesure du conflit, basée sur une distance, est utilisée comme alternative, et fournit dans certains cas, des résultats plus cohérents qu’avec le conflit défini dans la théorie de Demspter et Shafer. Les résultats concernant deux types de bioprocédés (procédé batch correspondant à une classification supervisée, et procédé fed-batch correspondant à une classification non supervisée) sont présentés