Work

BISOS: Backwards Incremental System Optimum Search algorithm for fast socially optimal traffic assignment

Year: 2016

Type: conference-paper

Abstract: This paper presents an algorithm, called the Backwards Incremental System Optimum Search (BISOS) for achieving system near-optimum traffic assignment by incrementally limiting accessibility of roads for a chosen set of agents. The described algorithm redistributes traffic volumes homogeneously around the city and converges significantly faster than existing methods for system optimum computation in current literature. Furthermore, as previous methods have mainly been developed for theoretical purposes, the solutions provided by them do not contain all the necessary information for a practical implementation such as explicit paths for the commuting population. In contrast, the BISOS algorithm preserves the information about the exact paths of all commuters, throughout the whole process of computing the system optimum assignment. Furthermore, a realistic traffic scenario is simulated using Singapore as a case study by utilizing survey and GPS traffic data. The BISOS routing method needs 15 times less routing computations to get within 1% of the optimal solution for a simulated scenario compared to conventional methods for system optimum computation.

Source: IEEE International Conference on Intelligent Transportation Systems (ITSC)

DOI: 10.1109/itsc.2016.7795902

Authors: Jordan Ivanchev, Daniel Zehe, Vaisagh Viswanathan, Suraj Nair, Alois Knoll

Institution: TUM CREATE

Language: English

Topic: Transportation Planning and Optimization

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: green

Funders: National Research Foundation, National Research Foundation Singapore