United States Department of Transportation
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Evaluating the Safety and Mobility Impacts of American Dream Complex: Phase I (Feasibility Study, and Data Acquisition)
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2021-04-01
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[PDF-13.68 MB]
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Corporate Contributors:Rutgers University. Center for Advanced Infrastructure and Transportation ; New Jersey. Dept. of Transportation. Division of Highway Traffic Safety ; North Jersey Transportation Planning Authority ; United States. Department of Transportation. Federal Highway Administration ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; ... More +
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Edition:Final Report 12/01/2019 – 03/31/2021
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Abstract:Traffic congestion and motor vehicle crashes are perceived as pivotal concerns that are particularly difficult to manage in high-density urban areas. Thus, mitigating traffic congestion and improving users' safety on roadways are top priorities of the United States Department of Transportation (USDOT). American Dream Complex, located outside New York City, is an entertainment and retail center that was officially opened in October 2019. The complex is expected to attract over 40 million annual visitors once fully operational, which may potentially result in substantial mobility and safety issues for road users in the area. The present research work evaluates the mobility and safety concerns of the transportation network in the vicinity of the American Dream Complex due to its partial official opening. In terms of mobility, the performance of four surrounding corridors was explored by incorporating travel time inflation (TI) as a performance measure. Based on the results obtained from the mobility analysis, no considerable congestion was observed on the opening day of the American Dream Complex on surrounding corridors. Additionally, StreetLight data was also explored for Interstate 95, NJ Route 3, and NJ Route 120 for a period of 120 days before and 120 days after the opening of the complex. Findings showed an increase in the trips made after the opening; however, the travel duration was not significantly impacted due to the opening. To achieve the second goal of this study, the research team developed an innovative artificial intelligence (AI)-based video analytic tool to assess intersection safety using surrogate safety measures. To extract the trajectory data, the proposed work integrates a real-time AI detection algorithm, YOLO-V5, with tracking using the Deep SORT algorithm. The proposed approach achieved a relative accuracy between 95 and 98 percent in detecting and tracking vehicle trajectories.
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