テーマパークでの混雑情報と優先搭乗パスの効果に関するマルチエージェントによる検討

抄録

We have investigated ways to reduce congestion in a theme park with multi-agents. We constructed a theme park model called Digital Park 1.0 with twenty-three attractions similar in form to Tokyo Disney Sea. We consider not only congestion information (number of vistors standing in line at each attraction) but also the advantage of a priority boarding pass, like Fast Pass which is used at Tokyo Disney Sea. The congestion-information-usage ratio, which reflects the ratio of visitors who behave according to congestion information, was changed from 0% to 100% in both models, with and without priority boarding pass. The “mean stay time of visitors" is a measure of satisfaction. The smaller mean stay time, the larger degree of satisfaction. Here, a short stay time means a short wait time. The resluts of each simulation are averaged over ten trials. The main results are as follows. (1) When congestion-information-usage ratio increased, the mean stay time decreases. When 20% of visitors behaved according to congestion information, the mean stay time was reduced by 30%. (2) A priority boarding pass reduced congestion, and mean stay time was reduced by 15%. (3) When visitors used congestion information and a priority boarding pass, mean stay time was further reduced. When the congestion-information-usage ratio was 20%, mean stay time was reduced by 35%. (4) When congestion-information-usage ratio was over 50%, the congestion reduction effects reached saturation.