Network Modelling & Optimisation

Network Modelling & Optimisation

Transportation systems consist of multiple interacting modes including pedestrians, non-motorized vehicles, cars, taxis, and more productive modes, such as buses or trams.

Despite the different features of motorized modes in terms of passenger occupancy, driving behaviour, duration of travel, and scheduled vs. non-scheduled service, their common characteristic is that they all cause delays to the transportation system as a whole.

Modelling and controlling the dynamics of multimodal urban network is challenging in different levels of aggregation.

We intend to investigate a multimodal approach that considers the interactions and conflicts among different transport modes, the influence of each mode in the overall network performance (expressed as network passenger flows), and heterogeneity among users, with respect to their trip route, transport mode, and depart time choices.

See the City Science research group for more information.

City Science

ITS Staff contacts

Current Research Activities

Stochastic Traffic Assignment of Electric Vehicle with Path Distance Constraint

This research addresses a general stochastic user equilibrium (SUE) traffic assignment problem for transport network with electric vehicles (EV), where the paths EV users can choose are restricted by their driving range limit. A minimization model for path-constrained SUE is first proposed, which extends the existing general SUE models with link-based side constraints to path-based constraints. The resulting model and solution method can be applied to various conditions with similar path-based constraints. The equilibrium conditions of the problem reveal that any path cost in the network is the sum of corresponding link costs and a path specific out-of-range penalty term. A modified method of successive averages (MSA) method with a predetermined step size sequence is developed for logit model and probit-based loading procedure is also modified for solving this problem. K-shortest paths algorithm is incorporated to generate the path set on a need basis. Finally, a numerical example is presented to verify the proposed model and solution algorithm.


Reliable Sensor Deployment for Transport System Surveillance in A Two-Dimensional Space

High-accuracy object positioning based on satellites (e.g. Global Positioning System (GPS)) or cellular phones has been playing a critical role in various application contexts such as vehicle navigation, driver guidance and aircraft tracking. In recent years, massive availability of mobile devices has stimulated demand for indoor location aware applications, including in building guidance and location-based advertising in shopping malls, elderly navigation in nursing homes and etc. Indoor positioning systems utilize radio waves, Wi-Fi, Bluetooth, magnetic fields or other sensory information collected by the mobile devices. The effectiveness of such a positioning system highly depends on the quality (working range and precision level) and quantity of sensor coverages in the spatial area. Nevertheless, high-precision sensors are generally expensive to deploy, and installed sensors could be disrupted from time to time due to technological defects or deliberate sabotages. The objective is to optimize sensor deployment locations that maximize the overall system-wide surveillance or positioning benefits under the risk of sensor failures.

Contact: Dr Kun An

A potential ITS application to predict urban railway level crossing delays

The Victorian government has embarked on an eight year program to grade separate 50 level crossings around metropolitan Melbourne at an estimated cost of $AUD 5 to 6 B. A primary motivation of this program is to reduce delays to private motorists, freight vehicles and public transport services. As is common in an urban context, the existing level crossings are protected by boom barriers that control road traffic movements to ensure safe rail operation. Some of those crossings are effectively closed to traffic for up to three quarters of the peak hour. While this extensive capital works program will reduce delays at those locations, around 125 level crossings will be left untreated by the current grade separation project. This research examines the potential for Intelligent Transport Systems to reduce delays at urban railway level crossings. The characteristics of the current control system are examined to identify factors that contribute to delays to road users and a simulation model is used to model how ITS technology could be used reduce crossing closure times. The model highlights the value of improved train speed data and more accurate data on whether a particular train is to stop at a station adjacent to the crossing or run express through the level crossing.