Article

An empirical study of short range communications for vehicles

Authors:

Hao Wu,

Joonho KoAuthors Info & Claims

VANET '05: Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks

Pages 83 - 84

https://doi.org/10.1145/1080754.1080769

Published: 02 September 2005 Publication History

Get Access

Abstract

This paper presents a detailed measurement study of short range communications between vehicles and between vehicles and roadside stations in a realistic highway scenario. We show the expected wireless communication characteristics in a driving environment and identify factors that significantly affect communication performance. We also illustrate the benefits of multi-hop communication in improving communication performance.

References

[1]

ALANR. Iperf, 2004.

Google Scholar

[2]

Lettieri, P. and Srivastava, M.B., Adaptive frame length control for improving wireless link throughput, range, and energy efficiency. in INFOCOM, (1998).

Crossref

Google Scholar

[3]

Moske, M., Fubler, H., Hartenstein, H. and Franz, W., Performance Measurements of a Vehicular Ad Hoc Network. in VTC/Spring, (2004).

Crossref

Google Scholar

[4]

Ott, J. and Kutscher, D., Drive-thru Internet: IEEE 802.11b for "Automobile" Users. in INFOCOM'04, (2004).

Crossref

Google Scholar

[5]

Singh, J.P., Bambos, N., Srinivasan, B. and Clawin, D., Wireless LAN Performance under varied stress conditions in vehicular traffic scenarios. in IEEE VTC Fall 2002, (2002).

Crossref

Google Scholar

Cited By

View all

Amiri PPierre S(2023)An Ensemble-Based Machine Learning Model for Forecasting Network Traffic in VANETIEEE Access10.1109/ACCESS.2023.325362511(22855-22870)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3253625
Sepasgozar SPierre S(2022)A Comparative Study of Artificial Intelligence Algorithms for Network Traffic Prediction in VANET2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)10.1109/WiMob55322.2022.9941664(431-436)Online publication date: 10-Oct-2022
https://doi.org/10.1109/WiMob55322.2022.9941664
Sepasgozar SPierre S(2022)Fed-NTP: A Federated Learning Algorithm for Network Traffic Prediction in VANETIEEE Access10.1109/ACCESS.2022.322197010(119607-119616)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3221970
Show More Cited By

Index Terms

An empirical study of short range communications for vehicles
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

Recommendations

Connected car overview: solutions, challenges and opportunities
IML '17: Proceedings of the 1st International Conference on Internet of Things and Machine Learning

In this paper, we defined the key concepts of IoV as application of IoT: connected car and an overview of the different communication cases leaded from vehicle to-x namely, vehicle-to-vehicle (V2V), vehicle -to- Internet (V2I), and vehicle-to-road ...
PROMPT: A cross-layer position-based communication protocol for delay-aware vehicular access networks

Vehicular communication systems facilitate communication devices for exchange of information among vehicles and between vehicles and roadside equipment. These systems are used to provide a myriad of services ranging from traffic safety application to ...
V2V and V2I Communications for Traffic Safety and CO₂ Emission Reduction: A Performance Evaluation
Abstract
In this paper, we consider a special scenario where connected (V2V and V2I) vehicular technologies are used to alert motorists when they approach a hazardous zone, such as a low visibility area, and recommend proper speeds. We present the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

VANET '05: Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks

September 2005

106 pages

ISBN:1595931414

DOI:10.1145/1080754

General Chairs:
Ken Laberteaux
Toyota Technical Center
,
Hannes Hartenstein
University of Karlsruhe, Germany
,
Program Chairs:
David B. Johnson
Rice University
,
Raja Sengupta
University of California, Berkeley

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 September 2005

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

Vanet05

Sponsor:

Vanet05: Vehicular Ad-hoc Networks Workshop 2005

September 2, 2005

Cologne, Germany

Acceptance Rates

Overall Acceptance Rate 26 of 64 submissions, 41%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

30
Total Citations
View Citations
982
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Amiri PPierre S(2023)An Ensemble-Based Machine Learning Model for Forecasting Network Traffic in VANETIEEE Access10.1109/ACCESS.2023.325362511(22855-22870)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3253625
Sepasgozar SPierre S(2022)A Comparative Study of Artificial Intelligence Algorithms for Network Traffic Prediction in VANET2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)10.1109/WiMob55322.2022.9941664(431-436)Online publication date: 10-Oct-2022
https://doi.org/10.1109/WiMob55322.2022.9941664
Sepasgozar SPierre S(2022)Fed-NTP: A Federated Learning Algorithm for Network Traffic Prediction in VANETIEEE Access10.1109/ACCESS.2022.322197010(119607-119616)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3221970
Sepasgozar SPierre S(2022)Network Traffic Prediction Model Considering Road Traffic Parameters Using Artificial Intelligence Methods in VANETIEEE Access10.1109/ACCESS.2022.314411210(8227-8242)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3144112
Garg SMehrotra DPandey HPandey S(2021)Accessible review of internet of vehicle models for intelligent transportation and research gaps for potential future directionsPeer-to-Peer Networking and Applications10.1007/s12083-020-01054-614:2(978-1005)Online publication date: 18-Jan-2021
https://doi.org/10.1007/s12083-020-01054-6
Doone MCotton SMatolak DOestges CHeaney SScanlon W(2019)Pedestrian-to-Vehicle Communications in an Urban Environment: Channel Measurements and ModelingIEEE Transactions on Antennas and Propagation10.1109/TAP.2018.288546167:3(1790-1803)Online publication date: Mar-2019
https://doi.org/10.1109/TAP.2018.2885461
Al-Mayouf YAbdullah NMahdi OKhan SIsmail MGuizani MAhmed S(2018)Real-Time Intersection-Based Segment Aware Routing Algorithm for Urban Vehicular NetworksIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2018.282331219:7(2125-2141)Online publication date: Jul-2018
https://doi.org/10.1109/TITS.2018.2823312
Yang BZheng RYin YYamabe SNakano K(2016)Analysis of influence on driver behaviour while using in‐vehicle traffic lights with application of head‐up displayIET Intelligent Transport Systems10.1049/iet-its.2015.017910:5(347-353)Online publication date: Jun-2016
https://doi.org/10.1049/iet-its.2015.0179
Xiao GZhang HHassan HChen YHuang ZSun N(2016)A cooperative offloading game on data recovery for reliable broadcast in VANETConcurrency and Computation: Practice and Experience10.1002/cpe.393829:14Online publication date: 16-Sep-2016
https://doi.org/10.1002/cpe.3938
Tornell SPatra SCalafate CCano JManzoni P(2015)GRCBoxInternational Journal of Distributed Sensor Networks10.1155/2015/4780642015(5-5)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1155/2015/478064
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Connected car overview: solutions, challenges and opportunities

PROMPT: A cross-layer position-based communication protocol for delay-aware vehicular access networks

V2V and V2I Communications for Traffic Safety and CO₂ Emission Reduction: A Performance Evaluation