RESUMEN
In this paper, a comprehensive deterministic Eco-Driving strategy for Connected and Autonomous Vehicles (CAVs) is presented. In this setup, multiple driving modes calculate speed profiles that are ideal for their own set of constraints simultaneously to save fuel as much as possible, while a High-Level (HL) controller ensures smooth and safe transitions between the driving modes for Eco-Driving. This Eco-Driving deterministic controller for an ego CAV was equipped with Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) algorithms. This comprehensive Eco-Driving strategy and its individual components were tested by using simulations to quantify the fuel economy performance. Simulation results are used to show that the HL controller ensures significant fuel economy improvement as compared to baseline driving modes with no collisions between the ego CAV and traffic vehicles, while the driving mode of the ego CAV was set correctly under changing constraints. For the microscopic traffic simulations, a 6.41% fuel economy improvement was observed for the CAV that was controlled by this comprehensive Eco-Driving strategy.
RESUMEN
Connectivity between ground vehicles can be utilized and expanded to include aerial vehicles for coordinated missions. Using Vehicle-to-Everything (V2X) communication technologies, a communication link can be established between Connected and Autonomous vehicles (CAVs) and Unmanned Aerial vehicles (UAVs). Hardware implementation and testing of a ground-to-air communication link are crucial for real-life applications. In this paper, the V2X communication and coordinated mission of a CAV & UAV are presented. Four methods were utilized to establish communication between the hardware and software components, namely Dedicated Short Range communication (DSRC), User Datagram Protocol (UDP), 4G internet-based WebSocket and Transmission Control Protocol (TCP). These communication links were used together for a real-life use case scenario called Quick Clear demonstration. In this scenario, the first aim was to send the accident location information from the CAV to the UAV through DSRC communication. On the UAV side, the wired connection between the DSRC modem and Raspberry Pi companion computer was established through UDP to get the accident location from CAV to the companion computer. Raspberry Pi first connected to a traffic contingency management system (CMP) through TCP to send CAV and UAV location, as well as the accident location, information to the CMP. Raspberry Pi also utilized WebSocket communication to connect to a web server to send photos that were taken by the camera that was mounted on the UAV. The Quick Clear demonstration scenario was tested for both a stationary test and dynamic flight cases. The latency results show satisfactory performance in the data transfer speed between test components with UDP having the least latency. The package drop percentage analysis shows that the DSRC communication showed the best performance among the four methods studied here. All in all, the outcome of this experimentation study shows that this communication structure can be utilized for real-life scenarios for successful implementation.