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Using Probabilistic Estimates to Guarantee Reliability in Crossroad VANETs

Published: 21 November 2017 Publication History

Abstract

We consider an intelligent crossroad where conventional traffic lights are substituted by a roadside unit (RSU), which synchronizes vehicles at the intersection, minimizing waiting time and energy consumption (by avoiding unnecessary braking and accelerating). Clearly, in this case, a reliable communication needs to be guaranteed between vehicles and the RSU, for which we investigate the design and analysis of specialized Vehicular Ad Hoc Networks (VANETs). It turns out that reliability strongly depends on the number of vehicles at the crossroad, i.e., the more vehicles, the more interference and, hence, the lesser reliability. As a result, to guarantee a desired level of reliability, we first need to estimate the worst-case number of vehicles at the crossroad. However, straightforward, deterministic approaches --- computing the maximum number of vehicles that physically fit into the crossroad's area --- lead to a great amount of pessimism and overdesign. In this paper, we propose using probabilistic estimations for the number of vehicles instead, which greatly reduces the amount of pessimism while still guaranteeing safety. Our approach is based on vehicles' statistical information and allows computing the probability of having a certain number of vehicles at the crossroad in the worst case. We incorporate this probabilistic estimate into the VANET's design and analysis to derive guarantees on reliability. Finally, we illustrate the benefits of the proposed approach by means of a detailed case study and simulations using OMNeT++.

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Cited By

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  • (2023)A Two-Speed Synchronous Traffic Protocol for Intelligent Intersections: From Single-Vehicle to Platoon CrossingACM Transactions on Cyber-Physical Systems10.1145/35712897:2(1-21)Online publication date: 19-Apr-2023
  • (2019)Space-Efficient Traffic Protocols for Intelligent Crossroads2019 IEEE Intelligent Vehicles Symposium (IV)10.1109/IVS.2019.8814043(1099-1104)Online publication date: Jun-2019
  • (2019)Analyzing the Impact of Probabilistic Estimates on Communication Reliability at Intelligent Crossroads2019 22nd Euromicro Conference on Digital System Design (DSD)10.1109/DSD.2019.00039(206-213)Online publication date: Aug-2019
  • Show More Cited By

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Published In

cover image ACM Conferences
DIVANet '17: Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications
November 2017
160 pages
ISBN:9781450351645
DOI:10.1145/3132340
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]

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Publication History

Published: 21 November 2017

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Author Tags

  1. intelligent crossroad
  2. omnet++
  3. reliability
  4. simulation
  5. vanet

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Overall Acceptance Rate 70 of 308 submissions, 23%

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Cited By

View all
  • (2023)A Two-Speed Synchronous Traffic Protocol for Intelligent Intersections: From Single-Vehicle to Platoon CrossingACM Transactions on Cyber-Physical Systems10.1145/35712897:2(1-21)Online publication date: 19-Apr-2023
  • (2019)Space-Efficient Traffic Protocols for Intelligent Crossroads2019 IEEE Intelligent Vehicles Symposium (IV)10.1109/IVS.2019.8814043(1099-1104)Online publication date: Jun-2019
  • (2019)Analyzing the Impact of Probabilistic Estimates on Communication Reliability at Intelligent Crossroads2019 22nd Euromicro Conference on Digital System Design (DSD)10.1109/DSD.2019.00039(206-213)Online publication date: Aug-2019
  • (2019)Toward an Efficient Deployment of Open Source Software in the Internet of Vehicles FieldArabian Journal for Science and Engineering10.1007/s13369-019-03870-244:11(8939-8961)Online publication date: 7-May-2019
  • (2018)A Deep Reinforcement Learning-based Trust Management Scheme for Software-defined Vehicular NetworksProceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3272036.3272037(1-7)Online publication date: 25-Oct-2018

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