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Using mobile probes to inform and measure the effectiveness of macroscoopic traffic control strategies on urban networks.
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2015-06-01
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[PDF-1.96 MB]
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Edition:Final report
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Abstract:Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this
congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work has
shown that these complicated systems can be modeled in relatively simple ways by leveraging consistent relationships that
exist between network-wide averages of pertinent traffic properties, such as average network flow, network density and the
rate at which trips are completed. Using these “macroscopic” traffic models, various control strategies can be developed to
mitigate congestion and improve network performance. However, the effectiveness of many of these strategies depends on the
ability to estimate traffic conditions on the network in real-time. This jointly proposed research between Penn State and Virginia
Tech investigated how real-time mobile vehicle probes can be combined with macroscopic urban traffic models to inform more
efficient network-wide traffic control strategies. Additionally, this work will examine how the effectiveness of these strategies
can be directly measured in the field using only mobile vehicle probe data. These two efforts can lead to more efficient control
of downtown traffic networks and a reduction in vehicular delay during rush hour periods.
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