Using Multi-Attribute Decision Factors for a Modified All-or-Nothing Traffic Assignment

Abstract

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.

Evaluation of Traffic Assignment Models through Simulation

“…A number of modifications have been made to this "base" methodology, such as the one by Lee & Oduor [52], which includes parameters from a GIS network that improve the model's results.…”

GIS for Sustainable Urban Transport

“…The real-time monitoring of such assets will be potentially of great use for the management of the underground railway system. Eunsu Lee and Peter Oduor [5] have looked at the problem of traffic assignment, the part of the transport modelling process in which forecasted traffic is assigned to specific sections of the network. They have developed a number of geospatial algorithms that consider different kinds of network impedances, categorized into absolute and relative impedance, depending on the situation to be modelled.…”

“…We see application of typical GIS strengths, such as digital map production (articles 1 and 2) [1,2], dynamic modelling (article 3) [3], spatial inventory of facilities/events (articles 1, 2, 4, 5 and 6) [1,2,[4][5][6], spatial data integration (articles 1, 2 and 5) [1,2,5] and spatial analysis (articles 1, 2, 4 and 6) [1,2,4,6], where it can be noted that several authors are using these GIS capabilities in combination and in integration with various statistical techniques (articles 1, 3 and 5) [1,3,5].…”

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

“…If the insertion is performed, u is updated with v. The best insertion place is defined as the one that minimizes the added total travel length and the total value of the end time window violation as Equation (3), where j denotes the next visited node of i. is a random value in [0. 5,2]. It should be noted that the arrival time at v, j should not be before the start time, as Equations (4) and (5):…”

“…Flexible transportation service not only reduces travel cost, but also alleviates related energy and environmental concerns, such as traffic congestion, energy consumption, and carbon emission [1,2]. With the advancement of geographic information science (GIS), space-related problem decision-making has been embedded in spatial decision support systems (SDSSs) to provide flexible transportation service in both public and private sectors [3], such as the design of school bus routes [4], collection of solid waste [5,6], distribution of goods in chain business [7], design of police patrol routes [8], and planning express deliveries [9].…”