This invention discloses a MaaS dynamic
bus route and
station planning method and a trip optimization method based on spatiotemporal clustering. The MaaS
algorithm based on spatiotemporal clustering, within a defined boundary area of no more than 25 square kilometers, determines
bus routes and stops based on existing
public transport demand where both origin and destination are within this area, according to established spatiotemporal clustering rules. It then returns the determined
bus routes, stops, and estimated arrival times to passengers using the planned bus routes and stops. The application of this invention maximizes the convenience of
public transport, reduces unnecessary
waiting time and connection distances, increases bus occupancy rates, reduces the probability of empty bus runs, and minimizes stops at unnecessary stops, thereby improving operational efficiency.