Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies-Reference-Cited by-同舟云学术

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Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies

Published:2018-12 Issue:6 Volume:52 Page:1299-1326
ISSN:0041-1655
Container-title:Transportation Science
language:en
Short-container-title:Transportation Science

Author:

Park Hyoshin (John)¹^ORCID,Haghani Ali²,Gao Song³,Knodler Michael A.³,Samuel Siby⁴

Affiliation:

1. Department of Computational Science and Engineering, North Carolina A&T State University, Greensboro, North Carolina 27411

2. Department of Civil and Environmental Engineering, University of Maryland, College Park, Maryland 20742

3. Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003

4. Department of Systems Design Engineering, University of Waterloo, Ontario N2L 3G1, Canada

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Transportation,Civil and Structural Engineering

Reference51 articles.

1. Connected vehicle penetration rate for estimation of arterial measures of effectiveness

2. Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin–Destination Flows

3. Optimal Number and Location of Node-Based Sensors for Collection of Travel Time Data in Networks

4. Location-Routing Problems with Distance Constraints

5. Combinatorial aspects of the sensor location problem

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Routing of Heterogeneous Users After Traffic Disruptions Under a Mixed Information Framework;Frontiers in Future Transportation;2022-05-18

2. Scalable information-theoretic path planning for a rover-helicopter team in uncertain environments;International Journal of Advanced Robotic Systems;2021-03-01

3. Online optimization with look-ahead for freeway emergency vehicle dispatching considering availability;Transportation Research Part C: Emerging Technologies;2019-12

4. Is dynamic traffic sensor network profitable for network-level real-time information prediction?;Transportation Research Part C: Emerging Technologies;2019-05

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