At the Department of Civil and Environmental Engineering, Mississippi State University, undergraduate students in Traffic Engineering class have learned and used ETFOMM to analysis level of services for intersections with actuated control traffic signals and freeway sections with weaving, merging and diverting. Students also collect field data to update traffic signal timing plans and evaluate alternative timing plans in ETFOMM.
In Traffic Simulation and Traffic Management course and Traffic Flow Theory course, graduate students created their own algorithms to interface with ETFOMM. Finally, one Ph.D. student created traffic signal optimization models using connected vehicle. His models and algorithms used many ETFOMM API functions and interfaced with ETFOMM. Two Ph.D. students are working to interface their traffic optimization models with ETFOMM.
In the Saxton Transportation Operations Lab, ETFOMM is used to develop, debug, test and evaluate innovative safety and mobility applications:
In the first project, an arterial traffic progression/optimization model is established by changing split and offset at coordinated signalized intersections. The model combines traditional traffic detection and information from Basic Safety Message sent from Connected Vehicles, propagates traffic signals from one intersection to another, optimizes offset and adjusts split in real time. The real time traffic signal timing plans are sent back to API at actuated traffic signal controller inside ETFOMM, which generates the measures of effectiveness. In a case study, the proposed algorithms outperform TRANSYT-7F by about 50% at major streets and at least 25% in control delay with Connected Vehicle penetration rates as small as 10%.
In the second study, ETFOMM is used to provide detector and traffic signal status for DCS originally developed by the Texas Transportation Institute that enhances the dilemma zone safety. Once DCS decides to extend or terminate the green time to avoid vehicles trapped in the dilemma zone, it sends back the request to the actuated signal controller inside ETFOMM. Multiple runs of simulation and statistical analysis of simulation results indicates that DCS reduces the number of stops and red light runners.
In the third task, detector data from ETFOMM provide inputs for a model to minimize the total freeway and ramp delay. The model outputs the speed reductions for freeway vehicles in order to create gaps for ramp vehicles to merge. The proposed speed reductions are implemented in ETFOMM. Evaluation from ETFOMM indicates the strategy can significantly reduce delays and increase the throughput.
A Research Project Sponsored by Office of Operations Research and Development
FHWA through US DOT Small Business Innovative Research