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Recent Advances on Context-Awareness and Data/Information Fusion in ITS

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Abstract

Intelligent transportation systems (ITS) involve various emerging technologies and applications. This paper presents a comprehensive review of recent advances on data/information fusion and context-awareness referring to ITS. Data/Information fusion is necessary to fuse the data from different sensors and thereby extract relevant information on the target sources. On the other hand, context-aware information processing provides awareness of the driving environments by deploying intelligent query processing and smart information dissemination. The fusion and context-awareness should help in improving ITS operations with better road-awareness service, traffic monitoring, vehicle detection as well as development of new methods. This paper is centered on data fusion and context aware methodologies developed recently in the areas of ITS rather than on their ITS applications. We found that the recent progresses in ITS fusion are devoted to the potential cooperative approaches providing real-time/dynamic vehicle sensing technologies, whereas the recent context awareness techniques are deploying service concepts (e.g. location aware service) and frameworks. It is believed that the newly developed advanced fusion/context-aware techniques are becoming more effective to tackle complex traffic scenarios (e.g. traffic intersection) as well as complex urban environments.

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Notes

  1. Intersections are the most complex driving environments and often cause injury/fatal traffic accidents.

  2. Vehicle cluster consists of vehicles where all pairwise distance measurements between the vehicle are known.

  3. VANET is a special type of Ad-hoc network, which is structure-free as well as it has fixed and mobile nodes. VANET can be viewed as an intelligent component of ITS as the vehicles communicate with each other as well as with the roadside base stations/roadside units (RSU) located at critical points of the road, such as intersections or construction sites. A comprehensive well-organized VANET is responsible for extracting, managing and interpreting the information to achieve knowledge, and making it available for travelers. VANET differs notably from other types of ad-hoc networks, such as wireless sensor networks (WSN) or mobile ad-hoc networks (MANET) [59] in terms of node dynamics and heterogeneity. The detailed description of the properties, features and applications of VANET can be found in [60, 67]

  4. The task of the middleware in VANETs is to collect, aggregate and store the data from different sources (such as sensors (e.g. radar, camera) data inside a car as well as information from other vehicles or RSUs) while working as the main data repository in a vehicle. The fused (aggregated) stored data are then utilized by control algorithms for ITS applications. It has the other important task for cross-layer information exchange to provide access-control (privacy and security).

  5. It contains the Environment Ontology representing the points of interests (POI) consists of service areas like restaurants/hotels, gas stations, or attractive places for tourists including museums, shopping mall, etc.

  6. Inference is a process when context rules are applied over each of the drivers’ profiles to match them with the relevant POIs using the Environmental ontology. of relevant services are taking place. Moreover, the user has to subscribe the provided services.

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  1. Department of Electrical & Computer Engineering, University of Waterloo, Ontario, Canada

    F. Sattar, F. Karray, M. Kamel, L. Nassar & K. Golestan

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Sattar, F., Karray, F., Kamel, M. et al. Recent Advances on Context-Awareness and Data/Information Fusion in ITS. Int. J. ITS Res. 14, 1–19 (2016). https://doi.org/10.1007/s13177-014-0097-9

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