Carpooling, an eco-friendly transportation option, has long been overlooked in Taiwan partially due to the absence of a tool facilitating rides with similar travel needs. This research addresses this gap by developing an app for real-time carpool matches. The process contains three steps: 1) Users sign up for the app with personal information, and the genetic algorism determines a fitness value based on the routing cost and user preferences such as interaction, dining, and smoke odor in the car; 2) After posting individual carpool demands, users receive a system-suggested carpool match; 3) The app generates a carpool fee with a discount for additional passengers, employing second-degree price discrimination. This app creates a mutually beneficial scenario: drivers earn a fee ranging from the public transit fare C as the price floor to 2.8C as the ceiling, covering gas costs and freeway tolls; passengers pay up to C and receive a 10% discount with an additional co-rider. The app and supporting measures propose a mechanism to alleviate traffic congestion in Taipei's science park corridor.
Relation:
Journal of Applied Science and Engineering 28(3), p.629-637
