کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1131952 1488986 2013 25 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Designing heterogeneous sensor networks for estimating and predicting path travel time dynamics: An information-theoretic modeling approach
موضوعات مرتبط
علوم انسانی و اجتماعی علوم تصمیم گیری علوم مدیریت و مطالعات اجرایی
پیش نمایش صفحه اول مقاله
Designing heterogeneous sensor networks for estimating and predicting path travel time dynamics: An information-theoretic modeling approach
چکیده انگلیسی


• Study sensor location problem jointly with travel time estimation/prediction models.
• Develop a unified framework to consider uncertainty in a heterogeneous sensor network.
• Propose new measures of information to emphasis end-to-end travel time prediction quality.
• Develop a convex programming model for traffic sensor location problems.

With a particular emphasis on the end-to-end travel time prediction problem, this paper proposes an information-theoretic sensor location model that aims to minimize total travel time uncertainties from a set of point, point-to-point and probe sensors in a traffic network. Based on a Kalman filtering structure, the proposed measurement and uncertainty quantification models explicitly take into account several important sources of errors in the travel time estimation/prediction process, such as the uncertainty associated with prior travel time estimates, measurement errors and sampling errors. By considering only critical paths and limited time intervals, this paper selects a path travel time uncertainty criterion to construct a joint sensor location and travel time estimation/prediction framework with a unified modeling of both recurring and non-recurring traffic conditions. An analytical determinant maximization model and heuristic beam-search algorithm are used to find an effective lower bound and solve the combinatorial sensor selection problem. A number of illustrative examples and one case study are used to demonstrate the effectiveness of the proposed methodology.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part B: Methodological - Volume 57, November 2013, Pages 66–90
نویسندگان
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