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In recent years, the development of connected and automated vehicle (CAV) technology has inspired numerous advanced applications targeted at improving existing transportation systems. As one of the widely studied applications of CAV technology, connected eco-driving takes advantage of Signal Phase and Timing (SPaT) information from traffic signals to enable CAVs to approach and depart from signalized intersections in an energy-efficient manner. However the majority of the connected eco-driving studies have been numerical or microscopic traffic simulations. Only few studies have implemented the application on real vehicles, and even fewer have been focused on heavy-duty trucks. In this study, we developed a connected eco-driving system and equipped it on a heavy-duty diesel truck using cellular-based wireless communications. Field trials were conducted in the City ofCarson, California, along two corridors with six connected signalized intersections capable of communicating their SPaT information. Early results showed the benefits of the system in smoothing the speed profiles of the equipped truck when approaching the connected signalized intersections.
Connected and Automated Vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the Eco-Driving problem seeks to design
Connected and Automated Hybrid Electric Vehicles have the potential to reduce fuel consumption and travel time in real-world driving conditions. The eco-driving problem seeks to design optimal speed and power usage profiles based upon look-ahead info
Connected and Automated Vehicles (CAVs) rely on the correctness of position and other vehicle kinematics information to fulfill various driving tasks such as vehicle following, lane change, and collision avoidance. However, a malicious vehicle may se
The fast-slow dynamics of an eco-evolutionary system are studied, where we consider the feedback actions of environmental resources that are classified into those that are self-renewing and those externally supplied. We show although these two types
Unmanned aerial vehicles (UAVs) play an increasingly important role in military, public, and civilian applications, where providing connectivity to UAVs is crucial for its real-time control, video streaming, and data collection. Considering that cell