Academic literature on the topic 'Traffic flow Australia'

The impact of inclement weather on traffic flow has been extensively studied in the literature. However, little research has unveiled how local weather conditions affect real-time traffic flows both spatially and temporally. By analysing the real-time traffic flow data of Traffic Signal Controllers (TSCs) and weather information in Brisbane, Australia, this paper aims to explore weather’s impact on traffic flow, more specifically, rainfall’s impact on traffic flow. A suite of analytic methods has been applied, including the space-time cube, time-series clustering, and regression models at three different levels (i.e., comprehensive, location-specific, and aggregate). Our results reveal that rainfall would induce a change of the traffic flow temporally (on weekdays, Saturday, and Sunday and at various periods on each day) and spatially (in the transportation network). Particularly, our results consistently show that the traffic flow would increase on wet days, especially on weekdays, and that the urban inner space, such as the central business district (CBD), is more likely to be impacted by inclement weather compared with other suburbs. Such results could be used by traffic operators to better manage traffic in response to rainfall. The findings could also help transport planners and policy analysts to identify the key transport corridors that are most susceptible to traffic shifts in different weather conditions and establish more weather-resilient transport infrastructures accordingly.

All established models in transportation engineering that estimate the numbers of trips between origins and destinations from vehicle counts use some form of a priori knowledge of the traffic. This paper, in contrast, presents a new origin–destination flow estimation model that uses only vehicle counts observed by traffic count sensors; it requires neither historical origin–destination trip data for the estimation nor any assumed distribution of flow. This approach utilises a method of statistical origin–destination flow estimation in computer networks, and transfers the principles to the domain of road traffic by applying transport-geographic constraints in order to keep traffic embedded in physical space. Being purely stochastic, our model overcomes the conceptual weaknesses of the existing models, and additionally estimates travel times of individual vehicles. The model has been implemented in a real-world road network in the city of Melbourne, Australia. The model was validated with simulated data and real-world observations from two different data sources. The validation results show that all the origin–destination flows were estimated with a good accuracy score using link count data only. Additionally, the estimated travel times by the model were close approximations to the observed travel times in the real world.

Public transit is widely recognized to reduce urban traffic congestion, as it encourages automobile travelers off the road. However, streetcars have been criticized for causing traffic congestion because large trams must operate in mixed traffic on narrow, congested streets. At the same time, streetcars reduce congestion by encouraging automobile drivers to use trams. So what is the net effect of streetcars on congestion? This paper presents a new method for assessing the net traffic congestion effects associated with streetcar operations in Melbourne, Australia, which has the largest streetcar network in the world. Impacts were determined with the use of a traffic network model to compare congestion with trams and without trams. The positive impacts of trams were estimated by using mode shift from tram to automobile when tram services were removed. Negative impacts were explored by considering streetcar traffic operations, the impact of curbside tram stops, and the effect of exclusive priority tram lanes on traffic flow. Findings show that the streetcar network in inner Melbourne results in a net congestion benefit to traffic; a 3.4% decrease in vehicle time traveled and total delay on the road network was established. The streetcar network also contributes to reducing the number of moderately congested links by 16%. Areas for future research are suggested, such as exploring the spatial distribution of the mode shift to automobile and the long-term effect of trams on traffic.

Papers in the December 2018 issue of the Journal include discussion on 5G security, what’s next for the National Broadband Network, a technical paper on the conflicts in routing and UAV autonomy, HTTP traffic flow load balancing and an insight into how the use of location information affects privacy. The history of Australian telecommunications paper on impressions of an overseas visit by a lines engineer provides an insight into how knowledge transfer improves with the opportunity to study telecommunications in Europe, North America and Australia. The Journal welcomes contributions.

Papers in the December 2018 issue of the Journal include discussion on 5G security, what’s next for the National Broadband Network, a technical paper on the conflicts in routing and UAV autonomy, HTTP traffic flow load balancing and an insight into how the use of location information affects privacy. The history of Australian telecommunications paper on impressions of an overseas visit by a lines engineer provides an insight into how knowledge transfer improves with the opportunity to study telecommunications in Europe, North America and Australia. The Journal welcomes contributions.

This paper presents the development and evaluation of short-term traffic prediction models using unidirectional and bidirectional deep learning long short-term memory (LSTM) neural networks. The unidirectional LSTM (Uni-LSTM) model provides high performance through its ability to recognize longer sequences of traffic time series data. In this work, Uni-LSTM is extended to bidirectional LSTM (BiLSTM) networks which train the input data twice through forward and backward directions. The paper presents a comparative evaluation of the two models for short-term speed and traffic flow prediction using a common dataset of field observations collected from multiple freeways in Australia. The results showed BiLSTM performed better for variable prediction horizons for both speed and flow. Stacked and mixed Uni-LSTM and BiLSTM models were also investigated for 15-minute prediction horizons resulting in improved accuracy when using 4-layer BiLSTM networks. The optimized 4-layer BiLSTM model was then calibrated and validated for multiple prediction horizons using data from three different freeways. The validation results showed a high degree of prediction accuracy exceeding 90% for speeds up to 60-minute prediction horizons. For flow, the model achieved accuracies above 90% for 5- and 10-minute prediction horizons and more than 80% accuracy for 15- and 30-minute prediction horizons. These findings extend the set of AI models available for road operators and provide them with confidence in applying robust models that have been tested and evaluated on different freeways in Australia.

Trails shared by hikers, bicyclists, and joggers present the unusual traffic flow situation of a facility serving three classes of users with distinctly different flow characteristics. Data on typical trail volumes are summarized. A procedure developed by Botma to describe quality of flow on shared pedestrian/bicycle paths is then discussed. Data from two sites, the MKT Trail in Columbia, Missouri, and a riverside trail in Brisbane, Australia, were collected to describe speed and passing time characteristics on shared trails. The frequency of desired overtakings (passes) and potential conflicts on trails are estimated based on measured speeds and passing times using basic relationships of traffic flow theory. These estimates are then compared with measured values of overtaking frequency and delayed overtakings. The estimates for passing demand and potential conflicts were higher than the measured values for hikers passing hikers and joggers passing hikers. However, estimates for bike passing bike, bike passing jogger, bike passing hiker, and jogger passing jogger were found to be similar to the measured values. The results support the Botma framework for describing quality of flow on shared pedestrian/bicycle paths.

AbstractThis paper presents a novel method to estimate queue length at signalised intersections using connected vehicle (CV) data. The proposed queue length estimation method does not depend on any conventional information such as arrival flow rate and parameters pertaining to traffic signal controllers. The model is applicable for real-time applications when there are sufficient training data available to train the estimation model. To this end, we propose the idea of “k-leader CVs” to be able to predict the queue which is propagated after the communication range of dedicated short-range communication (the communication platform used in CV system). The idea of k-leader CVs could reduce the risk of communication failure which is a serious concern in CV ecosystems. Furthermore, a linear regression model is applied to weigh the importance of input variables to be used in a neural network model. Vissim traffic simulator is employed to train and evaluate the effectiveness and robustness of the model under different travel demand conditions, a varying number of CVs (i.e. CVs’ market penetration rate) as well as various traffic signal control scenarios. As it is expected, when the market penetration rate increases, the accuracy of the model enhances consequently. In a congested traffic condition (saturated flow), the proposed model is more accurate compared to the undersaturated condition with the same market penetration rates. Although the proposed method does not depend on information of the arrival pattern and traffic signal control parameters, the results of the queue length estimation are still comparable with the results of the methods that highly depend on such information. The proposed algorithm is also tested using large size data from a CV test bed (i.e. Australian Integrated Multimodal Ecosystem) currently underway in Melbourne, Australia. The simulation results show that the model can perform well irrespective of the intersection layouts, traffic signal plans and arrival patterns of vehicles. Based on the numerical results, 20% penetration rate of CVs is a critical threshold. For penetration rates below 20%, prediction algorithms fail to produce reliable outcomes.

We proposed a new crash surrogate metric, i.e., the maximum disturbance that a car following scenario can accommodate, to represent potential crash risks with a simple closed form. The metric is developed in consideration of traffic flow dynamics. Then, we compared its performance in predicting the rear-end crash risks for motorway on-ramps with other two surrogate measures (time to collision and aggregated crash index). To this end, a one-lane on-ramp of Pacific Motorway, Australia, was selected for this case study. Due to the lack of crash data on the study site, historical crash counts were merged according to levels of service (LOS) and then converted into crash rates. In this study, we used the societal risk index to represent the crash surrogate indicators and built relationships with crash rates. The final results show that (1) the proposed metric and aggregated crash index are superior to the time to collision in predicting the rear-end crash risks for on-ramps; (2) they have a relatively similar performance, but due to the simple calculation, the proposed metric is more applicable to some real-world cases compared with the aggregated crash index.

TRAF-NETSIM and its successor CORSIM are comprehensive micro-simulation environments that have been widely used to model the urban traffic environment in the United States and abroad. CORSIM is employed in this study to simulate and evaluate the effects of pedestrian flows on right-turn saturation flow rates at signalized intersections. The saturation flow rates returned by CORSIM were compared with field data collected throughout the United States and with three existing analytical models in the United States, Australia, and Canada. These comparisons indicated that CORSIM models pedestrian interference with the turning vehicles more severely than the three analytical methods, but with a smaller effect than the empirical data indicate. Further, the empirical data exhibit a logarithmic relationship between saturation flow rate and opposing pedestrian volume, compared with the linear relationship used in the simulation and analytical models. Implications for the design and analysis of signalized intersections are presented.

The Australian road freight industry is moving towards improved efficiency and competitiveness through the use of larger and more innovative multi-combination vehicles (MCVs). However, this move has brought about concern over the interaction of these new vehicles with the environment, existing infrastructure and other road users. The aim of this research project was to assess the impacts of MCVs on traffic operation and safety. This was undertaken by initially reviewing cunent literature on MCVs. It was recognised that the Australian heavy vehicle fleet had modernised since a number of performance levels were established and the review highlighted the need for greater research to obtain current data and either develop new performance levels or validate previous research. This study selected four characteristics for analysis: passenger car equivalence (PCE), clearance time, acceleration, and tracking ability on a straight path. These characteristics were considered to be the most influential on the interaction between MCVs and other road users. Vehicle operational data was collected between April and August 2001, for each characteristic, via a series of three in-field test programs located on controlled road sections in Queensland: south of Charters Towers; west of Toowoomba; and at the Mount Cotton Training Centre, south-east of Brisbane. All tested MCVs recorded a PCE greater than 2 for a through-movement on a flat grade with no adjacent traffic lanes. It was determined that assuming a constant PCE does not account for the variation in values attained for different MCV types. Under circumstances where MCV volumes are significant, it would be more accurate to establish the average PCE value of each relevant movement at the intersection based on PCEs across the traffic spectrum and using the values provided in Table 5.4. Further testing is needed to establish PCE values on grades, turning movements, non-standard lane widths, and for vehicles such as Double Road Trains, AB-Triples and AAB-Quads. The intersection clearance time characteristics proposed by NRTC (2001) were found to be conservative for the MCV s tested. To cover a greater range of operating conditions, clearance time requirements for a MCV on a particular grade may be derived from the trajectory curves provided in Figures 6.3 to 6.6. Further in-field testing should be undertaken to obtain additional trajectory curves for MCVs with lower powered engines. Speed curves were developed (Figures 6.9 to 6.12) which may be used with the above trajectory curves to derive vehicle speeds at specific distances, on particular grades. This would enable assessors to determine the minimum entry lane length required to allow a MCV to attain adequate speed to merge into moving traffic, and also indicate whether an overtaking lane is required on a steep ascending grade. Further testing should be undertaken to establish speed curves over a higher speed and distance range . . Queensland Department of Main Roads (1998b) recommended an average acceleration rate for use in sight distance calculations. This was found from testing to be generally conservative for a B-Double, although too high for all the other MCVs tested. The trajectory curves provided in Figures 6.15 to 6.18 were developed to examine the variation in acceleration as test vehicles depart from rest. These may be used to determine average acceleration rates, over specific distances and on particular grades. Alternatively, sight distance requirements may be determined from equation (6.9), using clearance times established from equation (6.5) or Figures 6.3 to 6.6. Data on tracking ability of MCVs on a straight path was collected. It is recommended that further work be conducted to analyse the data, determine lane width requirements, and variations in tracking ability between separate trailers. The findings should be compared with Prem et al. (2000) and NRTC (2001) values. Further work is also required to identify which factors most influence lateral displacement of the rear trailer. It is expected that the research findings will be used to inform development of Queensland Department of Main Roads' Route Assessment Guidelines and potentially those of other authorities.

"In many cities around the world traffic congestion has been increasing faster than can be dealt with by new road construction. To resolve this problem traffic management devices and technology such as ramp meters are increasingly being utilized."--leaf 1.
Masters of Information Technology

"In many cities around the world traffic congestion has been increasing faster than can be dealt with by new road construction. To resolve this problem traffic management devices and technology such as ramp meters are increasingly being utilized."--leaf 1.
Masters of Information Technology

To achieve safe and unobstructed traffic flow at roundabouts and their approaches, the important condition that needs to be met is adequate visibility. Namely, a clear line of sight must be ensured to enable a driver without the right of way to engage in the roundabout traffic flow safely and to note on time the position of the vehicle in front of him. The issue of sight distance evaluation on suburban single-lane roundabouts will be analysed in this paper. A critical review of several roundabout design standards and guidelines (Australian, Croatian, and Italian) that describe procedures for determining the necessary sight distance at these intersections will be given. Influential parameters for defining clear sight areas will be presented in detail, with an emphasis on the diversity of roundabout sight distance evaluation approaches. Key issues of the existing Croatian guidelines will be identified, and recommendations for the improvement will be given. Test results obtained on a theoretical example of a suburban roundabout will also be commented on.