文章基本信息

标题：MC-TES: An Efficient Mobile Phone Based Context-Aware Traffic State Estimation Framework
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作者：Quang Tran Minh ; Muhammad Ariff Baharudin ; Eiji Kamioka 等
期刊名称：Information and Media Technologies
电子版ISSN：1881-0896
出版年度：2013
卷号：8
期号：1
页码：137-150
DOI：10.11185/imt.8.137
出版社：Information and Media Technologies Editorial Board
摘要：This paper proposes a notable m obile phone based c ontext-aware traffic state es timation (MC-TES) framework whereby the essential issues of low and uncertain penetration rate are thoroughly resolved. A novel i ntelligent c ontext-aware velocity-density i nference c ircuit (ICIC) and a practical artificial neural network (ANN) based prediction approach are proposed. The ICIC model not only improves the traffic state estimation effectiveness but also minimizes the critical penetration rate required in the m obile phone based t raffic state es timation (M-TES). The ANN-based prediction approach is considered as a complement of the ICIC in cases of an unacceptably low or unknown penetration rate. In addition, the difficulty in selecting the “right” traffic state estimation model, namely among the ICIC and the ANN, under the condition of an uncertain penetration rate is resolved. The experimental evaluations confirm the effectiveness, the feasibility as well as the robustness of the proposed approaches. As a result, this research contributes to accelerating the realization of mobile phone-based intelligent transportation systems (M-ITSs) or of the M-TES systems in specific.
关键词：mobile phone based ITS;traffic state estimation;mobile context-aware;penetration rate;inference circuit