Transport simulation : beyond traditional approaches

In recent years, the transport simulation of large road networks has become far more rapid and detailed, and many exciting developments in this field have emerged. In this perspective, the authors describe the simulation of automobile, pedestrian and rail traffic, coupled to new applications, such as the embedding of traffic simulation into driving simulators, to give a more realistic environment of driver behavior surrounding the subject vehicle.

Traffic Simulation for Proactive Traffic Management

Presentation on intelligent transport systems profects and traffic engineering,simulation and modelling by QUT researchers

N2O emissions from agricultural lands: a synthesis of simulation approaches

Nitrous oxide (N2O) is primarily produced by the microbially-mediated nitrification and denitrification processes in soils. It is influenced by a suite of climate (i.e. temperature and rainfall) and soil (physical and chemical) variables, interacting soil and plant nitrogen (N) transformations (either competing or supplying substrates) as well as land management practices. It is not surprising that N2O emissions are highly variable both spatially and temporally. Computer simulation models, which can integrate all of these variables, are required for the complex task of providing quantitative determinations of N2O emissions. Numerous simulation models have been developed to predict N2O production. Each model has its own philosophy in constructing simulation components as well as performance strengths. The models range from those that attempt to comprehensively simulate all soil processes to more empirical approaches requiring minimal input data. These N2O simulation models can be classified into three categories: laboratory, field and regional/global levels. Process-based field-scale N2O simulation models, which simulate whole agroecosystems and can be used to develop N2O mitigation measures, are the most widely used. The current challenge is how to scale up the relatively more robust field-scale model to catchment, regional and national scales. This paper reviews the development history, main construction components, strengths, limitations and applications of N2O emissions models, which have been published in the literature. The three scale levels are considered and the current knowledge gaps and challenges in modelling N2O emissions from soils are discussed.

Computer simulation and modeling in railway applications

An electrified railway system includes complex interconnections and interactions of several subsystems. Computer simulation is the only viable means for system evaluation and analysis. This paper discusses the difficulties and requirements of effective simulation models for this specialized industrial application; and the development of a general-purpose multi-train simulator.

Issues and concerns of microscopic calibration process at different network levels : case study of Pacific Motorway

Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such microcalibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, lane distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.

A traffic simulation standard based on data marts

Traffic Simulation models tend to have their own data input and output formats. In an effort to standardise the input for traffic simulations, we introduce in this paper a set of data marts that aim to serve as a common interface between the necessaary data, stored in dedicated databases, and the swoftware packages, that require the input in a certain format. The data marts are developed based on real world objects (e.g. roads, traffic lights, controllers) rather than abstract models and hence contain all necessary information that can be transformed by the importing software package to their needs. The paper contains a full description of the data marts for network coding, simulation results, and scenario management, which have been discussed with industry partners to ensure sustainability.

Considering weather in simulation traffic

The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.

A safety adapted car following model for traffic safety studies

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time To Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.

Environmental and economic evaluation of N fertilizer rates in a maize crop in Italy : a spatial and temporal analysis using crop models

Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.

Evaluation of the GHR car following model for traffic safety studies

Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

Design, simulation and analysis of a parallel hybrid electric propulsion system for unmanned aerial vehicles

Aerial Vehicles (UAV) has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors have seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. This paper presents the development of a parallel Hybrid Electric Propulsion System (HEPS) on a small fixed-wing UAV incorporating an Ideal Operating Line (IOL) control strategy. A simulation model of an UAV was developed in the MATLAB Simulink environment, utilising the AeroSim Blockset and the in-built Aerosonde UAV block and its parameters. An IOL analysis of an Aerosonde engine was performed, and the most efficient (i.e. provides greatest torque output at the least fuel consumption) points of operation for this engine were determined. Simulation models of the components in a HEPS were designed and constructed in the MATLAB Simulink environment. It was demonstrated through simulation that an UAV with the current HEPS configuration was capable of achieving a fuel saving of 6.5%, compared to the ICE-only configuration. These components form the basis for the development of a complete simulation model of a Hybrid-Electric UAV (HEUAV).

Modeling bus rapid transit station bus queuing for operational analysis

This paper presents mathematical models for BRT station operation, calibrated using microscopic simulation modelling. Models are presented for station capacity and bus queue length. No reliable model presently exists to estimate bus queue length. The proposed bus queue model is analogous to an unsignalized intersection queuing model.

Efficiency comparison of Markov Chain Monte Carlo simulation with subset simulation (MCMC/ss) to standard Monte Carlo Simulation (sMC) for extreme event scenarios

Standard Monte Carlo (sMC) simulation models have been widely used in AEC industry research to address system uncertainties. Although the benefits of probabilistic simulation analyses over deterministic methods are well documented, the sMC simulation technique is quite sensitive to the probability distributions of the input variables. This phenomenon becomes highly pronounced when the region of interest within the joint probability distribution (a function of the input variables) is small. In such cases, the standard Monte Carlo approach is often impractical from a computational standpoint. In this paper, a comparative analysis of standard Monte Carlo simulation to Markov Chain Monte Carlo with subset simulation (MCMC/ss) is presented. The MCMC/ss technique constitutes a more complex simulation method (relative to sMC), wherein a structured sampling algorithm is employed in place of completely randomized sampling. Consequently, gains in computational efficiency can be made. The two simulation methods are compared via theoretical case studies.

A review of pedestrian group dynamics and methodologies in modelling pedestrian group behaviours

Observations conducted by researchers revealed that the group interaction within crowds is a common phenomenon and has great influence on pedestrian behaviour. However, most research currently undertaken by various researchers failed to consider the group dynamics when developing pedestrian flow models. This paper presented a critical review of pedestrian models that incorporates group behaviour. Models reviewed in this paper are mainly created by microscopic modelling approaches such as social force, cellular automata, and agent-based method. The purpose of this literature review is to improve the understanding of group dynamics among pedestrians and highlight the need for considering group dynamics when developing pedestrian simulation models.

Analyzing busway station potential capacity under mixed stopping and non-stopping operation

Busway stations are the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses manoeuvring into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on busway capacity. This study uses microscopic simulation to treat the busway station operation and to analyse the relationship between station potential capacity where all buses stop, and Mixed Potential Capacity where there is a mixture of stopping and non-stopping buses. First, the micro simulation technique is used to analyze the All Stopping Buses (ASB) scenario and then statistical model is tuned and calibrated for a specified range of controlled scenarios of dwell time characteristics Subsequently, a mathematical model is developed for Mixed Stopping Buses (MSB) Potential Capacity by introducing different proportions of express (or non-stopping) buses. The proposed models for a busway station bus capacity provide a better understanding of operation and are useful to transit agencies in busway planning, design and operation.