Modelling South African traffic for large networks - an extension of the gravity model for traffic demand modelling

[摘要] ENGLISH SUMMARY : Traffic congestion is a growing burden on society. Due to the complexity of modelling transportation, many approaches do not scale efficiently. Assumptions are made to estimate the locality and quantity of traffic that passes through, leaves or enters a study area. Infrastructure investment based on inaccurate transportation modelling could potentially increase congestion. Furthermore, the effects of changes in infrastructure outside a study area are also unknown. It is therefore necessary to model transportation networks at a larger scale than required before. This thesis presents a large scale traffic modelling framework, potentially capable of modelling the impact of public transport and infrastructure investment for the South African context. The framework builds on the basic procedure of the Four-Step Modelling methodology. To address the shortcomings of static trip distribution models, a proposed, temporally adjusted, doubly constrained gravity model is formulated. Kernel density functions are fitted from survey data to dene unique impedance of travel functions for each travel analysis zone. Route selection is determined by a heuristic approach to dynamic traffic assignment which is implemented in a mesoscopic traffic simulator. The proposed gravity model is iteratively calibrated using the output of the traffic simulator in a positive feedback loop to produce a trip distribution that approaches an equilibrium assignment. The gravity model calibration and validation shows that the proposed gravity model is more accurate than the single impedance of travel gravity model. The framework produces OD trip matrices, inter- and intra-zonal routes, quarter-hourly traffic flows and a measure of congestion, all which can be visualised in a GIS environment.

[发布机构] Stellenbosch University