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DGPS-based lane assist system for transit buses

Identifieur interne : 006C55 ( Main/Exploration ); précédent : 006C54; suivant : 006C56

DGPS-based lane assist system for transit buses

Auteurs : Lee Alexander [États-Unis] ; Pi-Ming Cheng [États-Unis] ; Max Donath [États-Unis] ; Alec Gorjestani [États-Unis] ; Bryan Newstrom [États-Unis] ; Craig Shankwitz [États-Unis] ; Walter Jr Trach [États-Unis]

Source :

RBID : Pascal:06-0013080

Descripteurs français

English descriptors

Abstract

Metro Transit and the Minnesota DOT cooperatively operate a BRT-like system throughout the Twin Cities, Minnesota, metropolitan area. During peak congestion periods, buses operate on specially designated road shoulders (albeit at speeds significantly lower than limits posted for the adjacent highway). This allows buses to bypass congested roadways, enabling the bus to maintain its schedule regardless of traffic conditions. One of the problems faced by drivers using the shoulders is that the shoulders are typically no more than 3.1m wide; a 12m long transit bus measures 2.9m across the rear view mirrors, and 2.6m across the rear dual wheels. These narrow lanes require that a driver maintain a lateral error of less than 0.15m to avoid collisions. This is a difficult task under the best conditions, and degrades to nearly impossible during conditions of bad weather, low visibility, high traffic congestion, etc. Metro Transit drivers are not required to use the shoulders; shoulder use is left to their discretion. When poor conditions are encountered, many drivers choose not to use the shoulder. However, these poor conditions offer the greatest benefit of the bus-only shoulder use, creating an operational paradox. To minimize the effect of poor conditions on the use of bus-only shoulders, a lane assist system has been developed by the Intelligent Vehicles Lab at the University of Minnesota to help bus drivers under these difficult conditions. The system uses carrier phase, dual frequency differential GPS, a lane-level, high density, high accuracy geospatial database, and a lateral control algorithm for lateral assistance, radar for obstacle detection (critical in low visibility), and graphical, haptic, and tactile driver interfaces to provide guidance information to a driver. In addition to the system description, performance of the system on a operational bus-only shoulder is provided.


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<div type="abstract" xml:lang="en">Metro Transit and the Minnesota DOT cooperatively operate a BRT-like system throughout the Twin Cities, Minnesota, metropolitan area. During peak congestion periods, buses operate on specially designated road shoulders (albeit at speeds significantly lower than limits posted for the adjacent highway). This allows buses to bypass congested roadways, enabling the bus to maintain its schedule regardless of traffic conditions. One of the problems faced by drivers using the shoulders is that the shoulders are typically no more than 3.1m wide; a 12m long transit bus measures 2.9m across the rear view mirrors, and 2.6m across the rear dual wheels. These narrow lanes require that a driver maintain a lateral error of less than 0.15m to avoid collisions. This is a difficult task under the best conditions, and degrades to nearly impossible during conditions of bad weather, low visibility, high traffic congestion, etc. Metro Transit drivers are not required to use the shoulders; shoulder use is left to their discretion. When poor conditions are encountered, many drivers choose not to use the shoulder. However, these poor conditions offer the greatest benefit of the bus-only shoulder use, creating an operational paradox. To minimize the effect of poor conditions on the use of bus-only shoulders, a lane assist system has been developed by the Intelligent Vehicles Lab at the University of Minnesota to help bus drivers under these difficult conditions. The system uses carrier phase, dual frequency differential GPS, a lane-level, high density, high accuracy geospatial database, and a lateral control algorithm for lateral assistance, radar for obstacle detection (critical in low visibility), and graphical, haptic, and tactile driver interfaces to provide guidance information to a driver. In addition to the system description, performance of the system on a operational bus-only shoulder is provided.</div>
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