TRIM: Platform-Independent Framework for Speed Trajectory Refinement in Emission Modeling

Generating risk scenarios adverse to cooperative vehicle-infrastructure perception: An optimization-based framework.

Existing approaches for concrete scenario generation and assessment primarily focus on trajectory-level interactions while neglecting physical perception constraints, such as sensor field-of-view limitations and occlusions from surrounding objects, leading to unrealistic risk representations. To fill this gap, this stu...

Validating car-following behaviors of autonomous vehicles by structural assessment with empirical data

Using large-scale naturalistic autonomous vehicle trajectory data, an optimization-based calibration framework is developed that jointly estimates feedback delay in perception/decision and parasitic lag in actuation, and accommodates both linear constant-time-headway and nonlinear intelligent-driver-model controllers.

Nonlinear car-following dynamics modeling and uncertainty quantification for following vehicle trajectory generation in mixed traffic environments

Dynamics-informed causal inverse filtering for vertical track irregularity identification from multi-level vehicle accelerations

Track irregularity affects vehicle dynamic performance, ride quality and maintenance planning, yet its identification from vehicle responses remains challenging because the geometric excitation is embedded in coupled wheel–rail interaction and suspension dynamics. This study proposes a dynamics-informed causal inverse...

Radar-Based Evaluation of Car-Following Behavior and Fuel Consumption Across Vehicle Categories in SUMO

Results highlighting the importance of category-aware behavioral modeling when microsimulation outputs are used for energy and emissions assessment in mixed traffic highlight the importance of category-aware behavioral modeling.

Friction-Feasible Trajectory Prediction for Vehicles on Winter Roads: A Warm-Up Physics Loss with Velocity-Space Learning

Vehicle trajectory prediction on icy and snowy roads is safety-critical because reduced tyre–road adhesion compresses the set of dynamically feasible manoeuvres and can substantially increase braking distances relative to dry pavement. The objective of this study is to develop a lightweight physics-enhanced predictor t...