Abstract
This paper is focused on calibration of an intelligent network simulation model (INSIM) with real-life transportation network to analyse the INSIM’s feasibility in simulating commuters’ travel choice behaviour under the influence of real-time integrated multimodal traveller information (IMTI). A transportation network model for the central and western areas of Singapore was simulated in PARAMICS and integrated with INSIM expert system by means of an application programming interface to form the INSIM. Upon calibration, INSIM was able to realistically present complicated scenarios in which real-time IMTI was provided to commuters and the network performance measures being recorded.
Highlights
Empirical findings of travel behaviour studies have provided evidence that commuters presented with integrated multimodal traveller information (IMTI) in congested travel environment, exhibited a certain degree of mode switching [1,2,3,4]
This paper is focused on calibration of an intelligent network simulation model (INSIM) with reallife transportation network to analyse the INSIM’s feasibility in simulating commuters’ travel choice behaviour under the influence of real-time integrated multimodal traveller information (IMTI)
This approach utilises an external element that is integrated with the system to rationalise the ‘‘if-’’ process within the system. Such an approach is known as the agent-based simulation and has been shown to have the potential to model complicated cognitive processes. This is the approach taken in order to fill the gap of existing simulation research into the impact of IMTI system, the authors have developed a rule-based mode choice model, the intelligent network simulation model (INSIM), as reported in an earlier study [22]
Summary
Empirical findings of travel behaviour studies have provided evidence that commuters presented with integrated multimodal traveller information (IMTI) in congested travel environment, exhibited a certain degree of mode switching [1,2,3,4]. Such an approach is known as the agent-based simulation and has been shown to have the potential to model complicated cognitive processes This is the approach taken in order to fill the gap of existing simulation research into the impact of IMTI system, the authors have developed a rule-based mode choice model, the intelligent network simulation model (INSIM), as reported in an earlier study [22]. A heuristic algorithm is developed to solve the uncertainty problem and generate a suitable decision for the provided facts This ability of the IES allows it to provide a solution even when the provided information is not 100 % accurate or is incomplete. The details of public mode of transport were collected from Singapore Mass Rapid Transit’s website [35]
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