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Transportation System Optimization

> Research > Transportation System Optimization





Traffic demand in urban areas has rapidly increased along with the growth of population and economic activity. Because road infrastructure has slowly expanded due to the limited space available in urban areas, roadway networks have become more and more crowded. Therefore, it is essential to manage transportation systems (traffic signal plus infrastructure) in an optimal way. The aim of this research is to investigate the governing principles of the traffic systems through computational analysis and to determine the optimal traffic signal operation and infrastructure planning in order to improve their traffic performances.








Queue forming in a downstream link can deteriorate the performance of the adjacent upstream links. If traffic signal and infrastructure are optimized to minimize the difference between discharging capacity and traffic demand at each link, it is possible to balance the rates of queue growth (or equalize them in an ideal case) in a network and therefore minimize the risk of a spill-over due to localized, intense demand. This strategy for queue growth equalization (QGE) can also provide the maximum utilization of road infrastructure at the network level.





In any urban transportation network, traffic signal settings have a significant impact on the activation and evolution of urban gridlock, as well as on the capacity of the network. The goal of this research is to develop a signal optimization algorithm that can equalize queue growth rates across links in order to postpone queue spill-over.
* K. Jang, H. Kim, and I. G. Jang, “Traffic Signal Optimization for Oversaturated Urban Networks: Queue Growth Equalization,” IEEE Trans. Intell. Transp. Syst., vol. 16, no. 4, pp. 2121-2128, Aug. 2015.


Transportation infrastructure is the fundamental facilities and systems serving human and vehicle mobility. It typically characterizes technical structures such as roads, bridges, and tunnels. However, it requires a rational decision making due to the high costs and limited space. This research seek for engineering solutions for analyzing and evaluating transportation infrastructure system.