Research on Merging Pattern after Toll Based on Simulation
Yusong Wang, Jingxin Ning, Shang Li
Available Online July 2017.
- https://doi.org/10.2991/essaeme-17.2017.103How to use a DOI?
- Merging pattern, Cellular automaton, Dynamic Weighted Synthetic Evaluation (DWSE).
- We establish a fan-in system (including combination area design, merging pattern and so on) which can best prevent accidents, improve throughput and minimize the cost. To achieve our goal, first cellular automaton is used to stimulate the actual toll plaza and establish some kinds of combination area with different shapes and sizes so that we can estimate the cost of construction. In this process, we also use Nagel-Schreckenberg (NS) vehicle-following model and select 3 merging patterns to determine the movements of our "cars". By doing this, we get sufficient data from simulation, such as average velocity of moving cars, sharp braking frequency, throughput, etc. Finally, we establish social cost analysis model to obtain a relatively objective evaluation. We calculate the economic cost of accident per year, the time cost per year measured by money and the construction fee of the whole plaza shared by each year. Thus, we can compare different solutions and reach the optimization. The best solution is the symmetrical narrowing shape, Merging as soon as possible. To test our solution, we put it in different conditions including various traffic density, self-driving cars. We also find out the divergent influence of different kinds of tollbooth. One more interesting results is that by applying basic optimizing model and some simple simulations. we can at last find the best proportion of ECT, AT and MTC under certain circumstances.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yusong Wang AU - Jingxin Ning AU - Shang Li PY - 2017/07 DA - 2017/07 TI - Research on Merging Pattern after Toll Based on Simulation BT - Proceedings of the 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017) PB - Atlantis Press SN - 2352-5398 UR - https://doi.org/10.2991/essaeme-17.2017.103 DO - https://doi.org/10.2991/essaeme-17.2017.103 ID - Wang2017/07 ER -