subject: ccat subject: Truck platooning type: dataset
10.4231/2EEQ-3R20
Amir Kazemi , Aravind Ramakrishnan , Ashraf Alrajhi , Egemen Okte , Hadi Meidani , Hasan Ozer , Imad L. Al-Qadi , Jeffery R. Roesler , Rui Feng She , Sachindra Dahal , Yanfeng Ouyang
01/04/2022
This project have four different blocks. Block I: Real Time Optimization, Block II: Road Network Optimization of ACT Platoons, Block III: Resting Period and Pavement Damage, Block IV: Passive Sensing Paving Material
asphalt pavement autonomous and connected vehicles ccat Network Optimization Passive Sensing Platooning Truck platooning
10.4231/JVXT-YQ42
09/05/2023
A data-driven surrogate model was proposed to predict the drag force and fuel-consumption rate of truck platoons.
autonomous and connected vehicles ccat Platooning Truck platooning
10.4231/WEYJ-EG42
Aravind Ramakrishnan , Ashraf Alrajhi , Hasan Ozer , Imad Al-Qadi
09/05/2023
The main goal of the study was to understand the effect of truck platoons qualitatively and quantitatively on pavement distresses.
10.4231/Z5RS-KZ82
Angeli Jayme , Aravind Ramakrishnan , Fangyu Liu , Imad Al-Qadi
12/02/2024
This study utilized a conventional Burger’s model, incorporating a nonlinear power-law dashpot. A new load-pass approach enabled a reduction in computational domain and cost. A graph neural network was established to extend the framework.
Display #
Results 1 - 4 of 4