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Edge computing - enabled road condition monitoring : system development and evaluation
(University of Missouri--Columbia, 2023)
learning models including Random Forest, LightGBM and XGBoost were trained to predict International Roughness Index (IRI) at every 0.1-mile segment. XGBoost has the highest accuracy with an RMSE and MAPE of 16.89in/mi and 20.3 percent, respectively...
AI-based framework for automatically extracting high-low features from NDS data to understand driver behavior
(University of Missouri--Columbia, 2022)
finally provides a high-level interface for video content playback. To achieve objective two, we formulated the problem as both a classification and time-series segmentation problem. This is due to the fact that the majority of existing driver maneuver...
Multi-headed self-attention mechanism-based Transformer model for predicting bus travel times across multiple bus routes using heterogeneous datasets
(University of Missouri--Columbia, 2023)
Bus transit is a crucial component of transportation networks, especially in urban areas. Bus agencies must enhance the quality of their real-time bus travel information service to serve their passengers better and attract ...
Detection and quantification of delamination in concrete via time-lapse thermography with machine learning
(University of Missouri--Columbia, 2021)
of the sub-surface defects. The results of this study show that the detection of deeper defects (3 in. and beyond) can be improved by analyzing the time-frequency response of surface temperature variations over a period of time. Compared to traditional lock...
Interactive, multi-purpose traffic prediction platform using connected vehicles dataset
(University of Missouri--Columbia, 2022)
on tabular data is compared to state-of-the-art models. GC-GRU's Mean Absolute Percentage Error (MAPE) was very close to Transformer (3.16 vs 3.12) while achieving the fastest inference time and a six-fold faster training time than Transformer, although Long...
TITAN : an interactive, web-based platform for transportation, data integration, and analytics
(University of Missouri--Columbia, 2020)
State transportation agencies regularly collect and store various types of data for different uses such as planning, traffic operations, design, and construction. These large datasets contain treasure troves of information ...
TMA (Truck Mounted Attenuators) alert system-development and testing
(University of Missouri--Columbia, 2022)
of crashes with the TMA truck while maintaining the safety of the work zone workers. In this study, we aim to alarm the drivers following the TMA truck to avoid collisions and consequently, decrease the number and severity of the crashes. We used Unity 3D...