Simulation analysis of decision-making policy for on-demand transport systems

• Published in: Applied intelligence (Dordrecht, Netherlands) Vol. 31; no. 3; pp. 225 - 233
• Main Authors: Mukai, Naoto, Watanabe, Toyohide
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.12.2009; Springer Nature B.V
• Subjects: Artificial Intelligence; Classification; Competition; Computer Science; Decision making; Drivers; Machines; Manufacturing; Mechanical Engineering; Policies; Processes; Profits; Risk; Simulation; Studies; Transport; Vehicles; Simulation analysis; Decision-making; Intelligent transportation system; Profit analysis; On-demand transportation system
• ISSN: 0924-669X; 1573-7497
• DOI: 10.1007/s10489-008-0125-z

In recent years, on-demand transport systems (such as a demand-bus system) are focused as a new transport service in Japan. An on-demand vehicle visits pick-up and delivery points by door-to-door according to the occurrences of requests. This service can be regarded as a cooperative (or competitive) profit problem among transport vehicles. Thus, a decision-making for the problem is an important factor for the profits of vehicles (i.e., drivers). However, it is difficult to find an optimal solution of the problem, because there are some uncertain risks, e.g., the occurrence probability of requests and the selfishness of other rival vehicles. Therefore, this paper proposes a transport policy for on-demand vehicles to control the uncertain risks. First, we classify the profit of vehicles as “assured profit” and “potential profit”. Second, we propose a “profit policy” and “selection policy” based on the classification of the profits. Moreover, the selection policy can be classified into “greed”, “mixed”, “competitive”, and “cooperative”. These selection policies are represented by selection probabilities of the next visit points to cooperate or compete with other vehicles. Finally, we report simulation results and analyze the effectiveness of our proposal policies.