Abstract
To elucidate a realistic traffic assignment scenario, a multi-criterion decision system is essential. A traffic assignment model designed to simulate real-life situation may therefore utilize absolute and/or relative impedance. Ideally, the decision-making process should identify a set of traffic impedances (factors working against the smooth flow of traffic) along with pertinent parameters in order for the decision system to select the most optimal or the least-impeded route. In this study, we developed geospatial algorithms that consider multiple impedances. The impedances utilized in this study included, traffic patterns, capacity and congestion. The attributes of the decision-making process also prioritize multi-traffic scenarios by adopting first-in-first-out prioritization method. We also further subdivided classical impedance into either relative impedance or absolute impedance. The main advantage of this innovative multi-attribute, impedance-based trip assignment model is that it can be implemented in a manner of algebraic approach to utilize shortest path algorithm embedded in a Geographic Information Systems (GIS)—Graphical User Interface tool. Thus, the GIS package can therefore handle the multi-attribute impedance effectively. Furthermore, the method utilized in this paper displays flexibility and better adaptation to a multi-modal transportation system. Transportation, logistics, and random events, such as terrorism, can be easily analyzed with pertinent impedance.
Highlights
A traffic assignment model (TAM) employs various approaches in issues-of-scale with respect to modal transportation networks
User choices are made according to a random utility model for a stochastic user equilibrium model, and link travel times are dependent on the link flows
Classical impedance was determined and categorized into link impedance and node impedance. This was done to develop an innovative multi-attribute impedance-based modified all-or-nothing traffic assignment model. The advantage of this approach is to eliminate the efforts of removing unconnected segments physically and logically at the pre-processing stage of network analysis
Summary
A traffic assignment model (TAM) employs various approaches in issues-of-scale with respect to modal transportation networks. Wardrop’s first principle [1], which can be surmised as: In equilibria, there is no unilateral gain for a driver to reduce his/her travel costs by selecting another feasible route. Since the user equilibrium can vary due to random perceptive components, such as user preference, experience, and time of travel, it is necessary to include other routes that may meet a set threshold. To account for this randomness, stochastic user equilibrium assignment can be utilized since it incorporates unilateral route changes. User choices are made according to a random utility model for a stochastic user equilibrium model, and link travel times are dependent on the link flows
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