TRAFFIC OPERATIONS AND MANAGEMENT
TRAFFIC OPERATIONS AND MANAGEMENT
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UNIVERSITY OF MARYLAND
Variable Speed Limit Control
Variable Speed Limit Control
Our research on Variable Speed Limit (VSL) systems focuses on developing proactive speed control strategies to mitigate congestion and enhance traffic efficiency at recurrent freeway bottlenecks. By embedding macroscopic traffic flow models and predictive optimization frameworks, we designed a dynamic VSL system capable of computing time-varying optimal speed limits based on real-time traffic conditions. To address uncertainties in driver behavior and measurement noise, we integrated Kalman Filter-based state estimation into the control architecture. We evaluated multiple control objectives, such as minimizing total travel time and reducing speed variance, and found that optimizing for speed variance provides robust performance improvements across various traffic scenarios. Simulation results demonstrate that the enhanced VSL models can significantly reduce vehicle stops, improve speed stability, and lower travel times, supporting their potential for field implementation in intelligent transportation systems.
Ramp Metering Control
Ramp Metering Control
Our research focuses on advancing ramp metering strategies to enhance freeway efficiency and safety by optimally controlling the rate at which vehicles enter the mainline. We develop and evaluate coordinated ramp metering (CRM) algorithms that adjust metering rates based on real-time traffic conditions across multiple ramps, aiming to alleviate downstream bottlenecks and prevent system-wide congestion. Leveraging high-resolution traffic datasets and microscopic traffic simulation models such as VISSIM, we identify critical bottlenecks and assess the operational and safety impacts of various ramp metering strategies. Our findings show that CRM strategies—such as the Bottleneck algorithm—can significantly reduce mainline delays and improve traffic flow, though they introduce trade-offs in on-ramp delays. This research provides valuable insights for deploying intelligent ramp metering systems that balance freeway throughput with local access and safety considerations.
Highway Debris Collection
Highway Debris Collection
M-TRAIL leads research to improve the safety, efficiency, and effectiveness of roadway debris clearance operations, particularly for emergency response teams such as CHART. Our team conducted an in-depth evaluation of current practices and emerging technologies through structured field experiments that considered various real-world factors, including debris type, environmental conditions, operating speed, and equipment configurations. The study provided critical insights into how operational parameters influence debris removal performance and responder safety, especially in adverse weather and high-risk environments. By identifying key trade-offs between speed, effectiveness, and safety, and by recommending standardized procedures and training protocols, our research supports the development of resilient and scalable strategies for highway incident management. This work exemplifies M-TRAIL’s commitment to advancing transportation system performance through applied engineering solutions and technology-driven innovation.
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