Consecutive traffic signals produce vehicle stops and acceleration/deceleration maneuvers on arterial roads, which may increase vehicle fuel consumption levels significantly. Eco-cooperative adaptive cruise control (Eco-CACC) systems can improve vehicle energy efficiency using connected vehicle (CV) technology. In this thesis, an Eco-CACC system is proposed to compute a fuel-optimized vehicle trajectory while traversing multiple signalized intersections. The proposed system utilizes signal phasing and timing (SPaT) information together with real-time vehicle dynamics data to compute the optimal acceleration/deceleration levels and cruise speeds for connected-technology-equipped vehicles while approaching and leaving signalized intersections, while considering vehicle queues upstream of the intersections. The INTEGRATION microscopic traffic simulation software was used to conduct a comprehensive sensitivity analysis of a set of variables, including different levels of CV market penetration rates (MPRs), demand levels, phase splits, offsets, and distances between intersections to assess the benefits of the proposed algorithm. Based on the analysis, fuel consumption saving increase with an increase in MPRs and a decrease in the cycle length. At a 100% equipped-vehicle MPR, the fuel consumption is reduced by as much as 13.8% relative to the base no Eco-CACC control. The results demonstrate an existence of optimal values for demand levels and the distance between intersections to reach the maximum fuel consumption reduction. Moreover, if the offset is near the optimal values for that specific approach, the benefits from the algorithm are reduced. The algorithm is limited to under-saturated conditions, so the algorithm should be enhanced to deal with over-saturated conditions. / Master of Science / Consecutive traffic signals produce vehicle stops and acceleration/deceleration maneuvers on arterial roads, increasing vehicle fuel consumption levels. Drivers approaching signals are unaware of the signal status and may accelerate/decelerate aggressively to respond to traffic signal indications and thus increasing their fuel consumption. Research has been conducted to provide the driver with an optimal speed recommendations to reduce fuel consumption. Connected vehicle (CV) technology can be used to create a communication between the vehicle and traffic signals to provide information about the traffic light status and how many vehicles are waiting in the queue. In this thesis, an Eco-cooperative adaptive cruise control (Eco-CACC) system is proposed, which is a system that uses signal information to provide speed advice to the driver. This speed advice will not make the vehicle stop at any intersection, and this will reduce fuel consumption levels. The INTEGRATION software was used to test the effectiveness of the system in many scenarios. These scenarios include how many vehicles are equipped with this system, how many vehicles are in the system, the length of the green interval of the traffic signal, and distance between intersections. If we equip all vehicles with the system, the savings in fuel consumption can reach up to 13.8%. The system is designed for a network that is not extremely congested (over-saturated), implying that queues dissipate in a single traffic light cycle. The system needs to be further developed to deal with over-saturated conditions.