Rerepresenting Autonomated Vehicles in a Macroscopic Transportation Model

The main goal of this article is to determine a comprehensive and well applicable model architecture, which is adequate to estimate the system level advantages with regard to automated transportation and which is appropriate to determine possible costs and losses with regard to the approach of such transport modes. In the study the Budapest Transportation Model is applied. Taking autonomous vehicle penetration into account as an external variable, in the analysis a constant growth is assumed in the penetration of automated vehicles. This article has taken the most relevant factors of transportation network into account with regard to automated cars. It is also important to mention that the paper presents the most important modelling phases, where automated cars can be taken into account during the macroscopic modelling process. In the first step of the process during the network definition phase it is possible to consider the effect of automated vehicles on the transport system (e.g. separated routes). The next phase where the effect of automated vehicles should be taken into consideration is the mode choice step (e.g. different demand segments). And finally traffic assignment step, where the effect of automated vehicles can be represented. The easiest way for this is the modification of passenger car units through the parameter of assigned traffic per capacity ratio

Comparison and Assessment of Two Emission inventories for the Madrid Region

Emission inventories are databases that aim to describe the polluting activities that occur across a certain geographic domain. According to the spatial scale, the availability of information will vary as well as the applied assumptions, which will strongly influence its quality, accuracy and representativeness. This study compared and contrasted two emission inventories describing the Greater Madrid Region (GMR) under an air quality simulation approach. The chosen inventories were the National Emissions Inventory (NEI) and the Regional Emissions Inventory of the Greater Madrid Region (REI). Both of them were used to feed air quality simulations with the CMAQ modelling system, and the results were compared with observations from the air quality monitoring network in the modelled domain. Through the application of statistical tools, the analysis of emissions at cell level and cell – expansion procedures, it was observed that the National Inventory showed better results for describing on – road traffic activities and agriculture, SNAP07 and SNAP10. The accurate description of activities, the good characterization of the vehicle fleet and the correct use of traffic emission factors were the main causes of such a good correlation. On the other hand, the Regional Inventory showed better descriptions for non – industrial combustion (SNAP02) and industrial activities (SNAP03). It incorporated realistic emission factors, a reasonable fuel mix and it drew upon local information sources to describe these activities, while NEI relied on surrogation and national datasets which leaded to a poorer representation. Off – road transportation (SNAP08) was similarly described by both inventories, while the rest of the SNAP activities showed a marginal contribution to the overall emissions

Modelling Traffic Congestion as a Spreading Phenomenon

The spread of traffic jams in urban networks has long been viewed as a complex spatio-temporal phenomenon that often requires computationally intensive microscopic models for analysis purposes. This dissertation presents frameworks to describe the dynamics of congestion propagation and dissipation of traffic in cities using a simple contagion process, inspired by those used to model infectious disease spread in a population. Specifically, we model the spread of congestion in urban networks by adapting a classical epidemic model to include a propagation and dissipation mechanism dependent on time-varying travel demand and consistent with the fundamentals of network traffic flow theory. We describe the dynamics of congestion spread using two macroscopic new parameters (propagation rate β and recovery rate μ) embedded within a system of ordinary differential equations, similar to the well-known susceptible-infected-recovered (SIR) model. For simplicity, we initially assumed the topological distribution of road networks to be homogeneous. The proposed contagion-based dynamics are verified through empirical multi-city analysis. In addition to the simplistic homogeneous SIR approach, we also explored the significance of the degree of heterogeneity in urban street networks using both empirical and simulation-based traffic data. However, this approach inherently assumes an undirected network with uniform recovery rate compared to a road network, which usually displays directed flow and topological reliance on congestion recovery. Keeping in view of these constraints, we proposed a modification to the heterogeneous mean-field model to describe the spreading process of congestion in urban street networks. A practical application of the proposed model is also tested in this dissertation in the context of signal optimisation using cycle length as a controlling function. The experiments helped quantify the characteristic differences between two widely used traffic assignment models, i.e. Dynamic User Equilibrium (DUE) and Stochastic Route Choice (SRC). Comparison has been made at two levels: link-level flows and network-level congestion patterns. Furthermore, we explored an alternative approach for congestion dynamic modelling, namely the "Reaction-Diffusion (RD) model", with a similar concept as our proposed frameworks but at link-level. This model, with its complexity, requires higher computation time with detailed link-level information of congestion dynamics

Design Related Investigations for Media Access Control Protocol Service Schemes in Wavelength Division Multiplexed All Optical Networks

All-optical networks (AON) are emerging through the technological advancement of various optical components, and promise to provide almost unlimited bandwidth. To realise true network utilisation, software solutions are required. An active area of research is media access control (MAC) protocol. This protocol should address the multiple channels by wavelength division mutiplexing (WDM) and bandwidth management. Token-passing (TP) is one such protocol, and is adopted due to its simplicity and collisionless nature. Previously, this protocol has been analysed for a single traffic type. However, such a study may not substantiate the protocol's acceptance in the AON design. As multiple traffic types hog the network through the introduction multimedia services and Internet, the MAC protocol should support this traffic. Four different priority schemes are proposed for TP protocol extension, and classified as static and dynamic schemes. Priority assignments are a priori in static scheme, whereas in the other scheme, priority reassignments are carried out dynamically. Three different versions of dynamic schemes are proposed. The schemes are investigated for performance through analytical modelling and simulations. The semi-Markov process (SMP) modelling approach is extended for the analyses of these cases. In this technique, the behaviour of a typical access node needs to be considered. The analytical results are compared with the simulation results. The deviations of the results are within the acceptable limits, indicating the applicability ofthe model in all-optical environment. It is seen that the static scheme offers higher priority traffic better delay and packet loss performance. Thus, this scheme can be used beneficially in hard real-time systems, where knowledge of priority is a priori. The dynamic priority scheme-l is more suitable for the environments where the lower priority traffic is near real-time traffic and loss sensitive too. For such a scheme, a larger buffer with smaller threshold limits resulted in improved performance. The dynamic scheme-2 and 3 can be employed to offer equal treatment for the different traffic types, and more beneficial in future AONs. These schemes are also compared in their performance to offer constant QoS level. New parameters to facilitate the comparison are proposed. It is observed that the dynamic scheme-l outperforms the other schemes, and these QoS parameters can be used for such QoS analysis. It is concluded that the research can benefit the design of the protocol and its service schemes needed in AON system and its applications

A critical look at power law modelling of the Internet

This paper takes a critical look at the usefulness of power law models of the Internet. The twin focuses of the paper are Internet traffic and topology generation. The aim of the paper is twofold. Firstly it summarises the state of the art in power law modelling particularly giving attention to existing open research questions. Secondly it provides insight into the failings of such models and where progress needs to be made for power law research to feed through to actual improvements in network performance.Comment: To appear Computer Communication

Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads

Bot recognition in a Web store: An approach based on unsupervised learning

Abstract Web traffic on e-business sites is increasingly dominated by artificial agents (Web bots) which pose a threat to the website security, privacy, and performance. To develop efficient bot detection methods and discover reliable e-customer behavioural patterns, the accurate separation of traffic generated by legitimate users and Web bots is necessary. This paper proposes a machine learning solution to the problem of bot and human session classification, with a specific application to e-commerce. The approach studied in this work explores the use of unsupervised learning (k-means and Graded Possibilistic c-Means), followed by supervised labelling of clusters, a generative learning strategy that decouples modelling the data from labelling them. Its efficiency is evaluated through experiments on real e-commerce data, in realistic conditions, and compared to that of supervised learning classifiers (a multi-layer perceptron neural network and a support vector machine). Results demonstrate that the classification based on unsupervised learning is very efficient, achieving a similar performance level as the fully supervised classification. This is an experimental indication that the bot recognition problem can be successfully dealt with using methods that are less sensitive to mislabelled data or missing labels. A very small fraction of sessions remain misclassified in both cases, so an in-depth analysis of misclassified samples was also performed. This analysis exposed the superiority of the proposed approach which was able to correctly recognize more bots, in fact, and identified more camouflaged agents, that had been erroneously labelled as humans

Microsimulation models incorporating both demand and supply dynamics

There has been rapid growth in interest in real-time transport strategies over the last decade, ranging from automated highway systems and responsive traffic signal control to incident management and driver information systems. The complexity of these strategies, in terms of the spatial and temporal interactions within the transport system, has led to a parallel growth in the application of traffic microsimulation models for the evaluation and design of such measures, as a remedy to the limitations faced by conventional static, macroscopic approaches. However, while this naturally addresses the immediate impacts of the measure, a difficulty that remains is the question of how the secondary impacts, specifically the effect on route and departure time choice of subsequent trips, may be handled in a consistent manner within a microsimulation framework. The paper describes a modelling approach to road network traffic, in which the emphasis is on the integrated microsimulation of individual trip-makers’ decisions and individual vehicle movements across the network. To achieve this it represents directly individual drivers’ choices and experiences as they evolve from day-to-day, combined with a detailed within-day traffic simulation model of the space–time trajectories of individual vehicles according to car-following and lane-changing rules and intersection regulations. It therefore models both day-to-day and within-day variability in both demand and supply conditions, and so, we believe, is particularly suited for the realistic modelling of real-time strategies such as those listed above. The full model specification is given, along with details of its algorithmic implementation. A number of representative numerical applications are presented, including: sensitivity studies of the impact of day-to-day variability; an application to the evaluation of alternative signal control policies; and the evaluation of the introduction of bus-only lanes in a sub-network of Leeds. Our experience demonstrates that this modelling framework is computationally feasible as a method for providing a fully internally consistent, microscopic, dynamic assignment, incorporating both within- and between-day demand and supply dynamic

Extending TRANSIMS Technology to an Integrated Multilevel Representation

The TRANSIMS system developed at Los Alamos in the USA over the past decade is a world leader in providing an integrated land-use transportation dynamical model for large areas with a million or more inhabitants. TRANSIMS uses standard survey data to create synthetic micropopulations, including family structure, to simulate trip making and emergent traffic dynamics. We propose to extend TRANSIMS by adapting it to a new multi-level representation, allowing dynamics to be algebraically integrated at the micro-, meso- and macro-levels. The new representation builds a lattice hierarchy in a way that integrates non-partitional hierarchies of links and routes based on the usual hierarchy of geographical zones, e.g. neighbourhoods, districts, cities, counties and countries. Applying the representation to a big city starts by defining sets of zones at different levels. At the first level, N, is the street. This can be subdivided to building plots at level N-1, buildings at level N-2, and even rooms at level N-3. At level N+1 are the neighbourhoods, at level N+2 is the set of district zones (each of them containing the different neighbourhoods in the previous level), and at the top level N+3 (in this case), is just one zone, the city itself. If a larger study area is to be considered, we would have a whole set of N+3 zones defining N+4-level areas, and so on, extending to the level of counties, countries or even continents. This paper will explain the fundamentals of TRANSIMS technology and compare it to other systems. We will show how TRANSIMS and the new multi-level representation can be brought together to give new insights into the macro-dynamics of very large road systems such as London, England and even the whole of Europe