A Multi-Module Eco-Driving Control Framework for Platoons of Connected Autonomous Electric Vehicles in Mixed Traffic Environments Near Signalized Intersections

Activity: Talk or presentationTalk or presentation at a conference


The majority of the literature is regarding multi-objective eco-driving problems aiming to improve energy efficiency and travel time. This can be done in a hierarchical manner that minimizes the total vehicle delay or travel time at the upper level and energy consumption at the lower level. There are other studies in the literature that have attempted to minimize the summation or a weighted sum of energy consumption and travel time. Also, other research works have minimized the energy consumption itself, a function of instantaneous power, or a variable that represents the energy consumption, such as the absolute value of acceleration.
Therefore, the predominant theme in the literature is centered on the aim of reducing energy consumption. It encompasses various models designed for estimating energy consumption. These models vary based on the vehicle’s propulsion system, which could be either fuel-based or electric. Virginia Tech Comprehensive Power-based Fuel Consumption Model (VTCPFM), an instantaneous fuel consumption model developed by Akcelik and Virginia Tech microscopic energy and emission model (VT-micro) are exclusively usable in fuel-based vehicles. On the other hand, the instantaneous power consumption model developed by Wu, et al that is used in and the Comprehensive Power-based EV Energy consumption Model (CPEM) are exclusive energy consumption estimation models for EVs. Another important factor in the technical literature of multiple vehicles eco-driving is the combination of the vehicles. It can be homogeneous traffic, in which all of the vehicles are CAVs, or heterogeneous traffic in which both CAVs and human-driven vehicles (non-CAVs) are included in the system
model. In a homogeneous traffic-based study, Feng, et al grouped the vehicles into platoons with the criteria of passing the intersection in the same traffic signal cycle. They calculated the optimal trajectory for the leading vehicle of each platoon through optimal control, and the following vehicles apply the Next Generation Simulation (NGSIM) car-following model to follow the leading vehicle. In a similar study, a group of vehicles that cross the intersection within the same lane during a single cycle were considered a platoon. Similarly, the platoon leading vehicle’s trajectory was optimized by optimal control. The following vehicles used Newell’s car-following model to follow the preceding vehicle. In a more complicated study regarding mixed traffic environment, all Connected Electric Vehicles (CEVs) optimal trajectories were calculated by an optimal control method. He, et al assumed that all of the vehicles of the mixed traffic environment, either Intelligent Connected Vehicles (ICVs) or Human-driven Vehicles (HVs), are connected and can receive information and optimize their trajectory through a control or advisory system. In another study, the CAVs’ optimal trajectory was calculated by optimal control, and non-CAVs follow the CAVs through the Intelligent Driver Model (IDM).
Period10 Nov 2023
Event titleGlobal Cleaner Production Conference
Event typeConference
LocationShanghai, China
Degree of RecognitionInternational