An Information-Theoretic Sensor Location Model for Traffic Origin-Destination Demand Estimation Applications

被引:87
作者
Zhou, Xuesong [1 ]
List, George F. [2 ]
机构
[1] Univ Utah, Dept Civil & Environm Engn, Salt Lake City, UT 84112 USA
[2] N Carolina State Univ, Dept Civil Construct & Environm Engn, Raleigh, NC 27695 USA
关键词
origin-destination demand estimation; sensor network design; traffic counts; automatic vehicle identification counts; AUTOMATIC VEHICLE IDENTIFICATION; MATRICES; OPTIMIZATION; ALGORITHMS; SELECTION;
D O I
10.1287/trsc.1100.0319
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
To design a transportation sensor network, the decision maker needs to determine what sensor investments should be made, as well as when, how, where, and with what technologies. This paper focuses on locating a limited set of traffic counting stations and automatic vehicle identification (AVI) readers in a network, so as to maximize the expected information gain for the subsequent origin-destination (OD) demand estimation problem. The proposed sensor design model explicitly takes into account several important error sources in traffic OD demand estimation, such as the uncertainty in historical demand information, sensor measurement errors, as well as approximation errors associated with link proportions. Based on a mean square measure, this paper derives analytical formulations to describe estimation variance propagation for a set of linear measurement equations. A scenario-based (SB) stochastic optimization procedure and a beam search algorithm are developed to find suboptimal point and point-to-point sensor locations subject to budget constraints. This paper also provides a number of illustrative examples to demonstrate the effectiveness of the proposed methodology.
引用
收藏
页码:254 / 273
页数:20
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