Integrated Determination of Network Origin–Destination Trip Matrix and Heterogeneous Sensor Selection and Location Strategy

Hu, Shou-Ren; Peeta, Srinivas; Liou, Han-Tsung

doi:10.1109/tits.2015.2473691

Cited by 26 publications

(11 citation statements)

References 38 publications

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“…TC-6 and TC-10 are not focused on real-time and predictive applications that require reasoning on specific characteristics of moving objects at any given point in time (e.g velocity and acceleration), such as collision monitoring and prevention. The proposed calculi are especially suitable for any application that relies on trajectory databases to reason about the relations among large numbers of trajectories such as Origin/Destination (O/D) analysis (Hu et al 2016;Andrienko et al 2017), transportation demand discovery (Wang et al 2017;Moreira-Matias et al 2013) and stream of population monitoring (Ma et al 2017).…”

Section: Introductionmentioning

confidence: 99%

A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

Baryannis¹,

Tachmazidis²,

Batsakis³

et al. 2018

Theory and Practice of Logic Programming

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Spatial information is often expressed using qualitative terms such as natural language expressions instead of coordinates; reasoning over such terms has several practical applications, such as bus routes planning. Representing and reasoning on trajectories is a specific case of qualitative spatial reasoning that focuses on moving objects and their paths. In this work, we propose two versions of a trajectory calculus based on the allowed properties over trajectories, where trajectories are defined as a sequence of non-overlapping regions of a partitioned map. More specifically, if a given trajectory is allowed to start and finish at the same region, 6 base relations are defined (TC-6). If a given trajectory should have different start and finish regions but cycles are allowed within, 10 base relations are defined (TC-10). Both versions of the calculus are implemented as ASP programs; we propose several different encodings, including a generalised program capable of encoding any qualitative calculus in ASP. All proposed encodings are experimentally evaluated using a real-world dataset. Experiment results show that the best performing implementation can scale up to an input of 250 trajectories for TC-6 and 150 trajectories for TC-10 for the problem of discovering a consistent configuration, a significant improvement compared to previous ASP implementations for similar qualitative spatial and temporal calculi.

show abstract

Section: Introductionmentioning

confidence: 99%

A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

Baryannis¹,

Tachmazidis²,

Batsakis³

et al. 2018

Theory and Practice of Logic Programming

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show abstract

“…Yang et al [ 18 ] and Chen et al [ 19 ] proposed different methods to address the screen line-based traffic counting location problem. Hu et al [ 20 ] introduced a bi-level optimization model to identify the optimal deployment strategy for license plate recognition and vehicle detector sensors.…”

Section: Introductionmentioning

confidence: 99%

Integrating Optimal Heterogeneous Sensor Deployment and Operation Strategies for Dynamic Origin-Destination Demand Estimation

Zhu

Guo

Chen

et al. 2017

Sensors

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Most existing network sensor location problem (NSLP) models are designed to identify the number of sensors with fixed costs and installation locations, and sensors are assumed to be installed permanently. However, sometimes sensors are carried by individuals to collect traffic data measurements manually at fixed locations. Hence, their duration of operation for which traffic data measurements are collected is limited, and their costs are not fixed as they are correlated with the duration of operation. This paper proposes a NSLP model that integrates optimal heterogeneous sensor deployment and operation strategies for the dynamic O-D demand estimates under budget constraints. The deployment strategy consists of the numbers of link and node sensors and their installation locations. The operation strategy includes sensors’ start time and duration of operation, which has not been addressed in previous studies. An algorithm is developed to solve the proposed model. Numerical experiments performed on a network from a part of Chennai, India show that the proposed model can identify the optimal heterogeneous sensor deployment and operation strategies with the maximum dynamic O-D demand estimation accuracy.

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“…SLPs in traffic networks, corridors, or critical nodes have been widely researched in the past two decades such as before 2000 [5][6][7], 2001-2010 [8][9][10][11][12][13][14][15][16][17], and 2011-2016 [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35]. Researchers and engineers have built models, proposed algorithms, and demonstrated experimental results in an attempt to find optimal sensor placement.…”

Section: Introductionmentioning

confidence: 99%

“…The objective functions or metrics always have least squares, likelihood, possible relative error, or mean absolute relative error. In 2016, Hu et al [31] studied the heterogeneous sensor selection and location strategy for determining network origin-destination (OD) trip matrix. Xu et al [34] and Shao et al [35] addressed the traffic SLP for traffic flow acquisition.…”

Section: Introductionmentioning

confidence: 99%

Sensor layout strategy and sensitivity analysis for macroscopic traffic flow parameter acquisition

Qin

Chang

et al. 2017

IET Intelligent Transport Systems

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Integrated Determination of Network Origin–Destination Trip Matrix and Heterogeneous Sensor Selection and Location Strategy

Cited by 26 publications

References 38 publications

A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

Integrating Optimal Heterogeneous Sensor Deployment and Operation Strategies for Dynamic Origin-Destination Demand Estimation

Sensor layout strategy and sensitivity analysis for macroscopic traffic flow parameter acquisition

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