Transit Signal Optimization

Introduction and Problem Definition

The City of Kingston aims to decrease the number of automotive vehicles on the roads and to have active transportation to be 20% and transit to be 15% of the transportation community by 2034. To achieve this, the Traffic Signal Priority (TSP) system will be introduced as a trial at three intersections on bus routes 501 and 502, providing green lights for buses for 15 seconds and decreasing the transition time from a red light to a green light for transit buses by five seconds when a bus approaches an intersection and is 150 meters away. The implementation of the TSP system has major stakeholders that include the city of Kingston, the environment, transit users, and general commuters. The team will analyze how TSP affects traffic flow and bus travel times and suggest new timings for the signals that allow for a faster transit experience and a lower carbon emission factor. The team will validate the models to ensure they apply accurately to the real physical system. The team also researched the health impacts of diesel fuel on humans and found that public transit users generally get more physical activity when walking to and from stops along the route, and areas with accessible public transportation generally experience fewer traffic accidents and decreased emissions.

Analysis

The analysis of the report provides technical information on the proposed Traffic Signal Priority (TSP) system aimed at reducing CO2 emissions from automobiles in Kingston. The report identifies three possible solutions: maintaining the current timings set by Kingston City, optimizing the timings or distance settings, and changing the entire functionality of the system. The solution to implement would depend on the outcome of data analysis. The TSP system, installed at three intersections in the city, is expected to decrease bus travel times and, hopefully, increase public transportation usage. If the data analysis indicates a significant decrease in CO2 emissions, the team will continue with the current timings of a 15-second green light extension (GLE) and five-second red light truncation (RLT). The results will be compared with case studies obtained through research to validate the findings. If the analysis shows that the current timings could be optimized, new timings will be proposed, and further analysis conducted to determine their advantages over the current ones. The new timings will also be compared to other case studies to validate the results. If the analysis indicates that the current system is not working as expected, new systems may be considered. For instance, a priority system may be introduced to prioritize late buses, which can increase reliability, and encourage the use of public transportation.

Another section discusses decision making and proposes dividing the problem into three sub-models: an idling time and traffic analysis, a CO2 emission and fuel consumption analysis, and a validation model. The idling time model was created using MATLAB and outputted the new idling times of buses and cars at the intersections. The CO2 and gas emission model aimed to determine the new emissions after installing the TSP system and compare it to fuel consumption before the installation for both buses and cars. The model uses data from Kingston Transit, including the number of vehicles passing through the busiest intersections to determine the net effect of greenhouse gas emissions. To validate the models, the traffic software VISSIM was used to run live simulations of the intersections. The software excluded the TSP system, allowing the team to compare the base idling time model with the model created earlier. The final outputs were compared to case studies completed on TSP systems in other cities to ensure they were consistent with the results observed there.

The implementation of the system was analyzed, starting with intersection analysis, which examines the idling times of traffic with and without the use of TSP. The team subdivides the analysis into six different cases, depending on the bus traffic flow direction. For each direction, three cases were considered: activating RLT, activating GLE, and traveling through the intersection without activating TSP. The report also provides a detailed breakdown of the idling time program, which is mainly governed by the phase signaling and the GLE and RLT parameters at an intersection. By determining the total length of a phase and the number of cycles in an hour, the program can calculate the phase parameters. The team's analysis aims to reduce the number of vehicles idling at intersections, as this significantly contributes to CO2 emissions. The TSP system can help reduce idling times by prioritizing buses and reducing travel times, thereby encouraging the use of public transportation. The report concludes that implementing the proposed TSP system can significantly reduce CO2 emissions from automobiles in Kingston.

Conclusion

The report evaluates the performance of TSP by simulating the traffic environment of the three intersections using VISSIM. The study describes how the model was created, highlighting various features such as conflict areas, advanced left turn, and stop sign. The report presents the data obtained from each intersection, including queue length, maximum queue length, vehicle delay, stop delay, CO emissions, and fuel consumption. The report concludes that the three intersections varied in terms of vehicle count, and their signal timings and design had an impact on TSP's efficiency.