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Vehicle-based interactive management

Vehicle-based interactive management with multi-agent approach, Under the energy crisis and global warming, mass transportation becomes more important than before. The disadvantages of mass transportation, plus the high flexibility and efficiency of taxi and with the revolution of technology, electric-taxi is the better transportation choice for metropolis. On the other hand, among the many taxi service types, dial-a-ride (DAR) service system is the better way for passenger and taxi. However the electricity replenishing of electric-taxi is the biggest shortage and constraint for DAR operation system. In order to more effectively manage the electric-taxi DAR operation system and the lots of disadvantages of physical system and observe the behaviors and interactions of simulation system, multi-agent simulation technique is the most suitable simulation technique. Finally, we use virtual data as the input of simulation system and analyze the simulation result. We successfully obtain two performance measures: average waiting time and service rate. Result shows the average waiting time is only 3.93 seconds and the service rate (total transport passenger number / total passenger number) is 37.073%. So these two performance measures can support us to make management decisions. The multiagent oriented model put forward in this article is the subject of an application intended in the long term to supervise the user information system of an urban transport network.

To resist global warming, mass transportation plays an important role in metropolis (Government of Hong Kong, 2005). Public can travel by taking mass transportation rather than driving a car. In this way, public can reduce the CO2 generation and air pollution (GreenPartyTaiwan, 2007). In order to reduce the operation cost of mass transportation, Transportation Company has to abandon the flexibility and efficiency (Wu, 2006). However taxi just compensates the disadvantages of mass transportation, because it has the features of high flexibility and efficiency (GreenPartyTaiwan, 2007). So far, most of passengers stand beside road and wait for a taxi. In this condition, there are three disadvantages. First, passenger doesn’t know how long he/she has to wait until a taxi passes by. Secondly, passenger is not sure the coming taxi is free or not. Thirdly, taxi needs to go around and look for passenger. Hence the operation utility is too low so that causes the energy waste (Wu, 2005). Contrary, dial-a-ride (DAR) system is a good solution to solve this problem. In DAR system, passengers use wireless communication tool (mobile phone) to call for a pick-up and delivery service-to-service center (control center). Then, service center assigns an idle taxi to perform the task. Using this kind of service system, passenger doesn’t need to wait longer than before. And taxi driver can save the taxi energy. Hence, Dial-a-ride system is very important in taxi operation system (Wu, 2005). On the other hand, with the technological revolution of power, electric-taxi comes with the tide of fashion (Taiwan Environmental Information Center, 2009; BigSolar, 2005). Electric taxi means a taxi is driven by electricity. It has two advantages. First, for the earth, electric taxi can reduce the air pollution and global warming, because it can’t emit CO2 (the electric taxi we talk about is driven by pure electricity. The pure electricity means that it doesn’t emit CO2 and its source doesn’t involve any organic compound of carbon, like hydrogen-battery. For hydrogen-battery itself, its waste is “water” so it indeed can reduce the emission of CO2. (iCo2l, 2008)). Secondly, for taxi driver, electric-taxi can reduce the fuel cost, especially for oil, due to the cost of replenishing electricity is lower than gas or gasoline. Hence electric taxi is an important transportation for metropolises.

Contrary, electric-taxi also has disadvantage. The worst disadvantage in electric-taxi is the electricity that’s also the biggest limitation (Galus et al., 2009). During the electric-taxi traveling period, the electricity of taxi is decreasing. When the electricity of electric-taxi is not enough to do the next service, electric-taxi has to replenish its’ electricity in the electric station. During the replenishing period, electric-taxi can’t do any task and passenger still waits for service. Under this condition, that will cause the reduction of taxi company’s revenue and passenger satisfaction (GreenPartyTaiwan, 2007). However, revenue and passenger satisfaction are the most important performance measures for Taxi Company. So Electric-taxi Company has to propose some management policies to deal with the electric replenishing problem (Galus et al., 2009).

Hence how to manage the electric-taxi DAR operation system becomes a very important problem with management policies (GreenPartyTaiwan, 2007; Taiwan Environmental Information Center, 2009). In order to manage the electric-taxi DAR operation system, we have to construct an electric-taxi DAR operation simulation system. There is a lack in multi-agent transportation simulation, such as allowing cars move based on shortest path and dispatching operations. In fact, the traffic jams management is considerable for electric-taxi DAR operation system (Ezzedine et al., 2005; Kok & Lucassen, 2007; Lansdowne, 2006; Cubillos et al., 2008). So this paper takes into account the shortages of existing methods to reinforce our multi-agent simulation. On the other hand, due to the impracticable and costly weaknesses of physical system (Ali, 2006), multi-agent simulation technique is the most suitable simulation technique for our research.

The main purposes of this study are as follows: First purpose is to provide a series of management policies to manage the electric-taxi DAR operation system and analyze the phenomenon of simulation. Second purpose is to compensate the shortages of existing methods to reinforce our multi-agent simulation. The main contribution of this paper is that we successfully obtain the performance measures (average waiting time and service rate) to support the decision making for manager.

The rest of this paper is described as follows. Section 2 is the literature review. Section 3 introduces the electric-taxi DAR operation system. Section 4 creates the simulation system and describes the environment setting. Section 5 is to collect and analyze the data obtained from simulation. The last section will make a conclusion that includes the contributions of this research and describe the future work.

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