Multimodal Traffic Modeling in Riyadh, Saudi Arabia: a Coevolutionary, Best Case Analysis
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Navigational systems lack an option that allow users to choose a route from source to destination regardless of travel modes as long as the time is minimized. This implies that navigational systems might not search all feasible routes for minimizing the objective function in this type of routing problem. In this study, we developed two shortest path models; one is time-dependent “car” mode shortest path model and the other is time-dependent “mixed” mode shortest path model. Both models respect capacities of the modes, whether it is the street network or the train vehicles, when recommending the shortest path. Both models respect the queueing phenomenon by which users who make first arrival to a node or a link get to depart before those who make a latter arrival. We tested both models using a real transportation network. We used a multiagent transportation simulation software called MATSim to simulate traffic on this network and test our shortest path models. Towards this endeavor, we showed a methodology of how to convert and model multimodal transportation datasets from their original shapefile format to a MATSim network format. Then we tested both models to find out more insight about the computational complexity and resulting trips’ durations of the mixed-mode route guidance application compared to the car mode. We found that it is possible to construct a route-finding system that allows for a mixed-modes travel option (with capacity and scheduling constraints) and takes into account the temporal aspect of travel network behaviors, while limiting the computational requirements to a level at which the system could be implemented in the real-world urban environment of a portable navigational device or a cell phone. We also found that such system can result in significant time savings for users who use it. In addition, we presented the critical role of network structure and capacities, or traffic loads, in calculating the shortest path. The more traffic jams in a city, the stronger the case of using a mixed-mode route guidance application becomes.