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SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory

Published: 28 June 2011 Publication History
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  • Abstract

    While traffic signals are necessary to safely control competing flows of traffic, they inevitably enforce a stop-and-go movement pattern that increases fuel consumption, reduces traffic flow and causes traffic jams. These side effects can be alleviated by providing drivers and their onboard computational devices (e.g., vehicle computer, smartphone) with information about the schedule of the traffic signals ahead. Based on when the signal ahead will turn green, drivers can then adjust speed so as to avoid coming to a complete halt. Such information is called Green Light Optimal Speed Advisory (GLOSA). Alternatively, the onboard computational device may suggest an efficient detour that will save the driver from stops and long waits at red lights ahead.
    This paper introduces and evaluates SignalGuru, a novel software service that relies solely on a collection of mobile phones to detect and predict the traffic signal schedule, enabling GLOSA and other novel applications. Our SignalGuru leverages windshield-mounted phones to opportunistically detect current traffic signals with their cameras, collaboratively communicate and learn traffic signal schedule patterns, and predict their future schedule.
    Results from two deployments of SignalGuru, using iPhones in cars in Cambridge (MA, USA) and Singapore, show that traffic signal schedules can be predicted accurately. On average, SignalGuru comes within 0.66s, for pre-timed traffic signals and within 2.45s, for traffic-adaptive traffic signals. Feeding SignalGuru's predicted traffic schedule to our GLOSA application, our vehicle fuel consumption measurements show savings of 20.3%, on average.

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    cover image ACM Conferences
    MobiSys '11: Proceedings of the 9th international conference on Mobile systems, applications, and services
    June 2011
    430 pages
    ISBN:9781450306430
    DOI:10.1145/1999995
    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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    Published: 28 June 2011

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    Author Tags

    1. cameras
    2. detection
    3. green light optimal speed advisory
    4. mobile phones
    5. opportunistic sensing
    6. prediction
    7. signalguru
    8. traffic signal
    9. transition filtering

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    • (2024)Bi-Objective Incentive Mechanism for Mobile Crowdsensing With Budget/Cost ConstraintIEEE Transactions on Mobile Computing10.1109/TMC.2022.322947023:1(223-237)Online publication date: Jan-2024
    • (2024)A Meta Meeting Mountain based opportunistic message forwarding strategyAd Hoc Networks10.1016/j.adhoc.2023.103374154:COnline publication date: 12-Apr-2024
    • (2023)Signal Phasing and Timing Prediction Using Connected Vehicle DataTransportation Research Record: Journal of the Transportation Research Board10.1177/036119812311719092678:1(662-673)Online publication date: 24-May-2023
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