This research aims to optimize the traffic signal cycle and the green light time per traffic signal cycle at ramps and intersections in arterials to maximize the passing traffic volume and minimize the delaying traffic volume in freeway corridors. For this purpose, we developed the MATDYMO (multi-agent for traffic simulation with vehicle dynamics model) and validated it with comparison to commercial software, TRANSYT-7F, for an interrupted flow model and to URFSIM (urban freeway traffic simulation model) for an uninterrupted flow model. These comparisons showed that MATDYMO is able to estimate the traffic situation with only incoming traffic volume. Using MATDYMO, ramp metering and traffic signal control can be optimized simultaneously. We extracted 80 sampling points from the DOE (Design of Experiment) and derived each response from MATDYMO. Then, a neural network was adopted to approximate the objective function, and simulated annealing was used as an optimization method. There are three cases of the objective function: maximization of the freeway traffic volume, minimization of the delay of ramps and arterials, and the satisfaction of both cases. The optimization results showed that traffic flow in freeway corridors can be maintained to a steady stream by ramp metering and signal control.
In most previous studies of topology optimization, commercial programs, such as Optistruct, ANSYS, and MSC Patran, usually were used during implementation. Such commercial programs are not easy to use and entail time and cost. In addition, it is difficult to confirm results with reference to individual stages of optimization. For addressing this disadvantage, a topology optimization program, which is based on the C language, is developed in this study. This is a very convenient and powerful program for users to conduct topology optimization by using all density methods and homogenization methods in compliance with the methodology. For verifying the developed program, first of all, topology optimization was implemented by using density methods to evaluate the strain energy density of a cantilever plate and a simply supported plate, which are simple models. The feasibility of the program was verified through a comparison of the results with those from Optistruct, which is a commercial program. Finally, topology optimization was implemented with regard to the rolling-stock leading-cab, which is an application model. Through the Ls-Dyna program, the collision characteristic was also confirmed. Next, through homogenization methods, crash analysis was implemented in the rollingstock leading-cab. By the use of the internal energy density as deduced from the collision interpretation, topology optimization was implemented. The optimal values, by which the internal energy was maximized per unit weight, of the parameters of homogenization methods were deduced. By the use of Ls-Dyna program for the optimum model, where internal energy is maximized per unit weight, the crash characteristic was confirmed on the basis of the optimization result and the feasibility of the result was verified. This methodology deduces the axis compression deformation by implementing the role of a crash initiator during collision. In addition, the economic advantage of light-weight cars also can be deduced.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.