Development of Reward-Based Crowd Management System and Field Evaluation of Safety and Profitability

Abstract

For railroad operators with a highly public nature, ensuring the safety of passengers and revitalizing the areas along the line are both tasks to be accomplished. To enhance passenger safety, it is necessary to keep congestion levels below a certain level on platforms and trains. Since traffic congestion generally occurs at certain times, such as in the morning, it is important to disperse traffic congestion during rush hours. In the past, railroad operators have encouraged passengers to voluntarily commute off-peak, but this has not worked as an incentive for passengers simply by improving comfort. Because of this failure, rail operators are considering a method of setting fare prices based on the time of day and congestion levels. However, past studies suggest that few users change their behavior because those who choose the time of day to use the railroads do not always coincide with the fare payers. Therefore, we devised a crowd management system in which coupons redeemable at stores along the rail line are given directly to the customers, encouraging voluntary off-peak commuting and stimulating the local economy. This system features dynamic updating of coupon ranks based on congestion forecast information from measured congestion levels to enhance the effectiveness of the service. The results of a three-month verification experiment that cooperated with Shizuoka Railway confirmed that 7.1% of passengers took congestion avoidance actions and that passengers who obtained coupons got off at a specific station an average of 29% more often.