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INSTRUCTORS:
Mukundham Narasimhan
Byungkyu Brian Park
Yi Zhang
Mutasem A.Alzoubaidi, Ph.D., P.E.
Mahgam Tabatabaei
Purpose and Background
These presentations were recorded at the International Conference on Transportation & Development 2025.
CAV Platoon Formation in Mixed Traffic: Analytical Control Design and Realistic Numerical Validation (20 minutes)
This presentation explores the formation of Connected and Autonomous Vehicle (CAV) platoons within mixed traffic conditions, focusing on minimizing safety risks and maintaining macroscopic traffic flow. The speaker presents a novel platoon control method using a nonlinear Spring-Mass-Damper (SMD) model and a protocol network called the STPF algorithm. These tools enable intelligent vehicle pairing, safe maneuvering, and dynamic lane changes to accommodate real-world traffic scenarios. A realistic freeway simulation based on I-75 in Gainesville, Florida demonstrates the operational feasibility and benefits of the proposed system. The results indicate travel time improvements and smoother driving experiences for both individual users and the broader vehicle system, even at varying CAV penetration levels. The approach also limits reliance on roadside infrastructure by maximizing onboard sensing and communication.
Addressing Adaptive Cruise Control Limitations via Human-in-the-loop Connected Cruise Control (15 minutes)
This session introduces Human-in-the-loop Connected Cruise Control (H3C), a novel method designed to overcome limitations of traditional Adaptive Cruise Control (ACC) systems. By combining human driving behavior with connected vehicle data, H3C enhances smooth following and string stability. The approach uses the intended acceleration of the vehicle ahead to adjust the ego vehicle’s movement in real time, correcting over- or under-reactions by the human driver. A Virtual Reality-based driving simulator using BeamNG was developed to create a more immersive and realistic testing environment than traditional simulators. Preliminary results showed significant improvements in acceleration smoothness and fuel efficiency, particularly in electric vehicle settings. This research paves the way for improved driver comfort and safety in transitional automation.
Unveil Short-Term Traffic Change in Baltimore After Francis Scott Key Bridge Collapse (11 minutes)
This presentation analyzes the short-term traffic impacts following the collapse of the Francis Scott Key Bridge in Baltimore. Using a combination of real-time speed data and over 160,000 GPS-based vehicle trajectories, the study evaluates congestion patterns, bottleneck development, and trip duration changes. The collapse forced traffic rerouting to other corridors, notably I-895 and I-95, causing significant delays, especially for trucks restricted from using tunnels. The analysis highlights regional patterns of congestion, particularly during peak hours, and recommends mitigation strategies such as optimizing arterial signal timing and promoting telecommuting. The speaker emphasizes the importance of long-term traffic monitoring to understand ongoing infrastructure disruptions.
Novel Continuous Green T Application at Partial Cloverleaf Interchanges: A Comprehensive Assessment (18 minutes)
This talk introduces the Continuous Green T (CGT) concept as applied to partial cloverleaf (Parclo A) interchanges, a rarely implemented but highly efficient design for reducing delays and improving flow. The CGT Parclo A design removes one signal phase and introduces an acceleration lane, enabling through movement along the arterial without stopping. Using microsimulation in VISSIM, the presentation compares the CGT design against other alternatives like diverging diamond and SPDI under both current and projected traffic volumes. Results show significant reductions in delays, stops, and travel times while maintaining future scalability. The session also addresses implementation feasibility with existing infrastructure and signal optimization strategies.
Defining LOS Criteria for Congested Traffic Conditions (16 minutes)
This presentation challenges the conventional definition of Level of Service (LOS) F by proposing new subcategories within congested traffic conditions using real-world data. The study focuses on uninterrupted freeway segments, employing k-means clustering and Van Aerde speed-density modeling to segment LOS F into four levels of congestion severity. Data was obtained from the PEMS system on a California freeway segment, with validation using subsequent years’ data. The work addresses the limitations of traditional HCM definitions and presents new thresholds that better inform traffic operations, particularly for segments experiencing prolonged or recurring congestion.
Benefits and Learning Outcomes
Upon completion of this course, you will be able to:
- Explain how CAV platoons can be safely and efficiently formed in mixed traffic environments using control algorithms and protocol networks.
- Discuss how integrating human behavior with connected vehicle data improves cruise control performance and driver experience.
- Identify short-term traffic behavior changes and bottlenecks caused by sudden infrastructure failures using traffic data analysis.
- Describe the benefits and operational principles of the Continuous Green T Parclo A interchange design.
- Explain how clustering and modeling techniques can redefine LOS F to better represent varying degrees of traffic congestion.
Assessment of Learning Outcomes
Students' achievement of the learning outcomes will be assessed via a short post-test assessment (true-false, multiple choice, and/or fill in the blank questions).
Who Should Attend?
- Transportation Engineers
- Transportation Professionals
- Traffic engineers
- Highway engineers
- Materials engineers
- Construction engineers
How to Earn Your CEUs/PDHs and Receive Your Certificate of Completion
To receive your certificate of completion, you will need to complete a short post-test and receive a passing score of 70% or higher within 1 year of purchasing the course.
How do I convert CEUs to PDHs?
1.0 CEU = 10 PDHs [Example: 0.1 CEU = 1 PDH]