The highest fuel consumption on urban arterials is associated with driving in congested traffic, characterized by higher speed fluctuations and frequent stops at intersections. One way to reduce excessive stop-and-go driving on urban streets is to optimize signal timings. More recently, new methods in traffic signal optimization have incorporated changes in drivers' behavior to achieve optimum performance at signalized intersections. Connected vehicles technology provides a two-way wireless communication environment enabling vehicle-to-vehicle and vehicle-to-infrastructure communications, which can be used for a variety of mobility and safety applications. One such application is called the green light optimized speed advisory (GLOSA). This system uses timely and accurate information about traffic signal timing and traffic signal locations to guide drivers (through infrastructure-to-vehicle communication) with speed advice for a more uniform commute with less stopping time through traffic signals. A GLOSA implementation was evaluated for two types of traffic signal timing: predictable fixed-time signal timing and unpredictable actuatedcoordinated signal timing. A two-intersection traffic network was modeled in VISSIM to achieve trustworthy results calibrated in the field. A comprehensive modal emission model was used to accurately estimate emissions. Experiments included various infrastructure-to-vehicle penetration rates and GLOSA activation frequencies. Results indicated that actuatedcoordinated signal timings were not dependable for use in GLOSA systems. For fixed-time signals, higher penetration rates and more frequent GLOSA activations resulted in better traffic performance. GLOSA caused only minor improvements in fuel consumption, and average delay in vehicles stopped was improved significantly.