Using Mobile Probes to Inform and Measure the Effectiveness of Traffic Control Strategies on Urban Networks

Using mobile probes to inform and measure the effectiveness of traffic control strategies on urban networks 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. Disclaimer The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. Urban traffic congestion in the United States is a significant drain on productivity and the environment. One study estimates that urban drivers spend about 36 hours annually stuck in congestion and that results in waste of about 24 gallons of fuel [1]. While in the past this congestion has been mitigated by expanding the roadway network, roadway infrastructure investments are incredibly expensive and have been shown to actually exacerbate congestion [2, 3] Instead, network-wide control strategies that seek to manage traffic on the network are slowly gaining traction. For example, several cities have implemented congestion pricing strategies that charger users to enter the downtown area [4, 5, 6]. Adaptive signal control strategies are also used in Zurich to restrict flow into congested portions of the network and instead direct this flow to underutilized areas [7]. However, the effects of these strategies have been difficult to predict due to the complexity of urban street networks. For this reason, there has been a …