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Title: City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts

Abstract

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. Here, the results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also showsmore » that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.« less

Authors:
 [1];  [1]
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  1. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States). Center for Sustainable Mobility
Publication Date:
Research Org.:
Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1494834
Report Number(s):
DOE-VT-0008209-C03
Journal ID: ISSN 1424-8220; SENSC9
Grant/Contract Number:  
EE0008209
Resource Type:
Accepted Manuscript
Journal Name:
Sensors
Additional Journal Information:
Journal Volume: 19; Journal Issue: 2; Journal ID: ISSN 1424-8220
Publisher:
MDPI AG
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 54 ENVIRONMENTAL SCIENCES; 42 ENGINEERING; 97 MATHEMATICS AND COMPUTING; ITS; VANET; eco-routing; large-scale network; smart cities; penetration ratio; connected vehicles, vehicular networks

Citation Formats

Elbery, Ahmed, and Rakha, Hesham. City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts. United States: N. p., 2019. Web. doi:10.3390/s19020290.
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Elbery, Ahmed, & Rakha, Hesham. City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts. United States. https://doi.org/10.3390/s19020290
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Elbery, Ahmed, and Rakha, Hesham. Tue . "City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts". United States. https://doi.org/10.3390/s19020290. https://www.osti.gov/servlets/purl/1494834.
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@article{osti_1494834,
title = {City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts},
author = {Elbery, Ahmed and Rakha, Hesham},
abstractNote = {Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. Here, the results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.},
doi = {10.3390/s19020290},
journal = {Sensors},
number = 2,
volume = 19,
place = {United States},
year = {Tue Jan 01 00:00:00 EST 2019},
month = {Tue Jan 01 00:00:00 EST 2019}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.3390/s19020290
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Citation Metrics:
Cited by: 11 works
Citation information provided by
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Figures / Tables:

Figure 1 Figure 1: Eco-routing without the Communication modeling
All figures and tables (20 total)
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Works referenced in this record:

VANET Communication Impact on a Dynamic Eco-Routing System Performance: Preliminary Results
conference, May 2018

  • Elbery, Ahmed; Rakha, Hesham A.
  • 2018 IEEE International Conference on Communications Workshops (ICC Workshops)
  • DOI: 10.1109/ICCW.2018.8403557

Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach
journal, October 2017

  • Chen, Yuche; Zhu, Lei; Gonder, Jeffrey
  • Transportation Research Part C: Emerging Technologies, Vol. 83
  • DOI: 10.1016/j.trc.2017.08.003

INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results
journal, September 2012

  • Rakha, Hesham A.; Ahn, Kyoungho; Moran, Kevin
  • International Journal of Transportation Science and Technology, Vol. 1, Issue 3
  • DOI: 10.1260/2046-0430.1.3.259

Eco-Routing Navigation System Based on Multisource Historical and Real-Time Traffic Information
journal, December 2012

  • Boriboonsomsin, Kanok; Barth, Matthew J.; Zhu, Weihua
  • IEEE Transactions on Intelligent Transportation Systems, Vol. 13, Issue 4
  • DOI: 10.1109/TITS.2012.2204051

Large-scale Agent-based Multi-modal Modeling of Transportation Networks - System Model and Preliminary Results [Large-scale Agent-based Multi-modal Modeling of Transportation Networks - System Model and Preliminary Results]
conference, March 2018

  • Elbery, Ahmed; Dvorak, Filip; Du, Jianhe
  • Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems
  • DOI: 10.5220/0006690301030112

Optimizing route choice for lowest fuel consumption – Potential effects of a new driver support tool
journal, December 2006

  • Ericsson, Eva; Larsson, Hanna; Brundell-Freij, Karin
  • Transportation Research Part C: Emerging Technologies, Vol. 14, Issue 6
  • DOI: 10.1016/j.trc.2006.10.001

Derivation of a fundamental diagram for urban traffic flow
journal, March 2009

Optimizing route choice for lowest fuel consumption – Potential effects of a new driver support tool
journal, December 2006

  • Ericsson, Eva; Larsson, Hanna; Brundell-Freij, Karin
  • Transportation Research Part C: Emerging Technologies, Vol. 14, Issue 6
  • DOI: 10.1016/j.trc.2006.10.001

Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach
journal, October 2017

  • Chen, Yuche; Zhu, Lei; Gonder, Jeffrey
  • Transportation Research Part C: Emerging Technologies, Vol. 83
  • DOI: 10.1016/j.trc.2017.08.003

INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results
journal, September 2012

  • Rakha, Hesham A.; Ahn, Kyoungho; Moran, Kevin
  • International Journal of Transportation Science and Technology, Vol. 1, Issue 3
  • DOI: 10.1260/2046-0430.1.3.259
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    Works referencing / citing this record:

    Multi-Factor Taxonomy of Eco-Routing Models and Future Outlook
    journal, January 2020

    Multi-Level Taxonomy and Critical Review of Eco-Routing Methods
    preprint, January 2019

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      Figures / Tables found in this record:

      Figure 1 (p. 5)figure
      Figure 2 (p. 8)figure
      Table 1 (p. 8)table
      Figure 3 (p. 10)figure
      Figure 4 (p. 10)figure
      Figure 5 (p. 11)figure
      Figure 6 (p. 12)figure
      Figure 7 (p. 13)figure
      Figure 8 (p. 13)figure
      Figure 10 (p. 14)figure
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      Figure 12 (p. 14)figure
      Figure 9 (p. 14)figure
      Figure 13 (p. 16)figure
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      Figure 16 (p. 16)figure
      Figure 17 (p. 16)figure
      Figure 18 (p. 16)figure
      Figure 19 (p. 17)figure
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