Traffic Demand Management In Three Historic Cities: Results Of A Multivariate Analysis of Business Attitudes.

The problem of traffic congestion and pollution in cities has become a major focus of UK transport policy in recent years. The government consultation paper, Breaking the Logjam (DETR, 1998), considered two specific traffic demand management policies: road user charges (RUC) and workplace parking levies (WPL). Legislation is now before Parliament to allow local authorities to introduce these policies. A major issue affecting the introduction of traffic demand management policies is the possible economic impacts on the urban business sector. There has been little research on the link between transport factors and urban business performance. There is general evidence that firms located in conurbations tend to perform more poorly than firms located in other areas (see, for example, Moore et al., 1980; Fothergill and Gudgin, 1982; Fothergill et al., 1984). There is also evidence that inner city firms perform more poorly than those in outer city locations. For example, Dobson and Gerrard (1991) find that engineering firms located in the inner Leeds area tend to have a lower level of profitability than engineering firms located in the outer Leeds area. Transport problems are one possible important cause of these location effects on business performance. This is supported directly by evidence that transport factors are an important influence on commercial location decisions (Nelson et al., 1994). Of all of the possible business reactions to the introduction of traffic demand management policies in urban areas, the potentially most important in economic terms is the relocation of businesses out of the urban core. Any significant degree of business evacuation of the urban core would have a profound impact on the ability of the urban economy to support the local population. In addition, any spatial restructuring of the local economy would have implications for traffic flows, shifting the locations of major traffic attractors from the urban core to the periphery. Although this may alleviate congestion in the urban core, it may serve only to create congestion elsewhere rendering traffic demand management policies somewhat counter-productive in the long run. The objective of this paper is to report the results of a multivariate analysis of business perceptions of current transport conditions and attitudes to traffic demand management policies based on a survey of firms in three historic cities - Cambridge, Norwich and York. A key component of the survey is the information provided on whether firms are currently considering relocation and the likely impact of the introduction of RUC and WPL on the next location decision. Basic data analysis of the survey responses indicates that the overwhelming majority of firms would definitely or possibly consider relocation as a response to the introduction of traffic demand management. The multivariate analysis seeks to identify those factors that have a statistically significant effect on the probability of relocation as a response. The structure of the paper is as follows. Section 2 briefly outlines the methodology of the multivariate analysis. Section 3 provides details of the data set used for the multivariate analysis. Section 4 presents the results of the multivariate analysis of the factors influencing the perception of acute transport problems, current relocation considerations, and relocation as a response to RUC and WPL. The final section provides a summary of the findings and a discussion of the policy implications

Geometrical and functional criteria as a methodological approach to implement a new cycle path in an existing Urban Road Network: A Case study in Rome

Most road accidents occur in urban areas and notably at urban intersections, where cyclists and motorcyclists are the most vulnerable. In the last few years, cycling mobility has been growing; therefore, bike infrastructures should be designed to encourage this type of mobility and reduce motorized and/or private transport. The paper presents a study to implement a new cycle path in the existing cycle and road network in Rome, Italy. The geometric design of the new path complies with Italian standards regarding the technical characteristics of bicycle paths, while the Highway Capacity Manual has been considered for the traffic analysis. In particular, a before-after approach has been adopted to examine and compare the traffic flow at more complex and congested intersections where the cycle path will pass. Trams, buses, cars, bikes and pedestrians were the traffic components considered in each analysis. The software package PTV VISSIM 8 allowed the simulations of traffic flows at traffic-light intersections; an original linear process has been proposed to model dynamic intelligent traffic controls, which are not admitted by the software used. The traffic analysis allowed the identification of the best option for each of the five examined intersections. Particularly, the maximum queue length value and the total number of passed vehicles have been considered in order to optimize the transport planning process. The results of this study highlight the importance of providing engineered solutions when a cycle path is implemented in a complex road network, in order to avoid negative impacts on the citizens and maximize the expected advantages

Frontier impedance effects and the growth of international exchanges: an empirical analysis for France

On the European Union scale, international traffic is growing faster than intra-national traffic. This phenomenon is often viewed as a consequence of the abatement of the frontier effect. In this article the frontier effect is analyzed, on the basis of data available for road traffic between France and its neighbors and of freight transport data available at the EU level. The concept is discussed in the light of this empirical analysis. The shortcomings of the static approach lead to a critical revaluation by means of a longitudinal approach. In the conclusion some potential directions for future research are discussed.Frontier ; frontier effect ; international flow ; passengers transport ; goods transport ; Europe

Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

Understanding mobile traffic patterns of large scale cellular towers in urban environment is extremely valuable for Internet service providers, mobile users, and government managers of modern metropolis. This paper aims at extracting and modeling the traffic patterns of large scale towers deployed in a metropolitan city. To achieve this goal, we need to address several challenges, including lack of appropriate tools for processing large scale traffic measurement data, unknown traffic patterns, as well as handling complicated factors of urban ecology and human behaviors that affect traffic patterns. Our core contribution is a powerful model which combines three dimensional information (time, locations of towers, and traffic frequency spectrum) to extract and model the traffic patterns of thousands of cellular towers. Our empirical analysis reveals the following important observations. First, only five basic time-domain traffic patterns exist among the 9,600 cellular towers. Second, each of the extracted traffic pattern maps to one type of geographical locations related to urban ecology, including residential area, business district, transport, entertainment, and comprehensive area. Third, our frequency-domain traffic spectrum analysis suggests that the traffic of any tower among the 9,600 can be constructed using a linear combination of four primary components corresponding to human activity behaviors. We believe that the proposed traffic patterns extraction and modeling methodology, combined with the empirical analysis on the mobile traffic, pave the way toward a deep understanding of the traffic patterns of large scale cellular towers in modern metropolis.Comment: To appear at IMC 201

The influence of heavy goods vehicle traffic on accidents on different types of Spanish interurban roads

This paper illustrates a methodology developed to analyze the influence of traffic conditions, i.e. volume and composition on accidents on different types of interurban roads in Spain, by applying negative binomial models. The annual average daily traffic was identified as the most important variable, followed by the percentage of heavy goods vehicles, and different covariate patterns were found for each road type. The analysis of hypothetical scenarios of the reduction of heavy goods vehicles in two of the most representative freight transportation corridors, combined with hypotheses of total daily traffic mean intensity variation, produced by the existence or absence of induced traffic gives rise to several scenarios. In all cases a reduction in the total number of accidents would occur as a result of the drop in the number of heavy goods transport vehicles, However the higher traffic intensity, resulting of the induction of other vehicular traffic, reduces the effects on the number of accidents on single carriageway road segments compared with high capacity roads, due to the increase in exposure. This type of analysis provides objective elements for evaluating policies that encourage modal shifts and road safety enhancements

Multi-Output Gaussian Processes for Crowdsourced Traffic Data Imputation

Traffic speed data imputation is a fundamental challenge for data-driven transport analysis. In recent years, with the ubiquity of GPS-enabled devices and the widespread use of crowdsourcing alternatives for the collection of traffic data, transportation professionals increasingly look to such user-generated data for many analysis, planning, and decision support applications. However, due to the mechanics of the data collection process, crowdsourced traffic data such as probe-vehicle data is highly prone to missing observations, making accurate imputation crucial for the success of any application that makes use of that type of data. In this article, we propose the use of multi-output Gaussian processes (GPs) to model the complex spatial and temporal patterns in crowdsourced traffic data. While the Bayesian nonparametric formalism of GPs allows us to model observation uncertainty, the multi-output extension based on convolution processes effectively enables us to capture complex spatial dependencies between nearby road segments. Using 6 months of crowdsourced traffic speed data or "probe vehicle data" for several locations in Copenhagen, the proposed approach is empirically shown to significantly outperform popular state-of-the-art imputation methods.Comment: 10 pages, IEEE Transactions on Intelligent Transportation Systems, 201

Analysis of passenger traffic in large transport hubs

В статье рассмотрены основные направления развития внутригородских и пригородно-городских пассажирских перевозок в крупных транспортных узлах. Выполнен ана- лиз состояния пассажирских перевозок в крупных транс- портных узлах и анализ развития и функционирования транспортно-пересадочных узлов. Освещены основные причины изменения функций и структуры транспортно- пересадочных узлов. Выполнен анализ отечественного опыта формирования и развития транспортно- пересадочных узлов. Рассмотрены основные причины, определяющие выбор пассажиром способа перемещения и вида транспортных средств. Предложены методики сокращения времени поездки пассажиров внутри города, мегаполиса, пригорода.У статті розглянуті основні напрямки розвитку внутрішньоміських, приміських і міських пасажирських перевезень у великих транспортних вузлах. Виконано ана- ліз стану пасажирських перевезень у великих транспорт- них вузлах і аналіз розвитку і функціонування транспорт- но-пересадочних вузлів. Висвітлено основні причини зміни функцій і структури транспортно-пересадочних вузлів. Виконано аналіз вітчизняного досвіду формування і роз- витку транспортно-пересадочних вузлів. Розглянуто ос- новні чинники, що визначають вибір пасажиром способу переміщення та виду транспортних засобів. Запропоно- вано методики скорочення часу поїздки пасажирів всере- дині міста, мегаполіса, передмістя.In article basic directions of development urban and pe- ri-urban passenger transport in major transport hubs. The analysis state passenger transport in major transport hubs and analysis development and operation transport hubs. When covering the main causes of changes in the functions and structure transport hubs. The analysis national experience in the formation and development transportation hubs. The main factors determining choice of method passenger movement and type vehicle. The techniques reducing travel time of pas- sengers within city, city, suburb. Optimal organization of public transport heavily dependent on transportation factors. In the case uncontrolled development individual transport, resulting in overloading road network and deterioration ecological environment, to improve the traffic situation at the same time measures should be aimed at limiting use of individual transport. Currently, passengers using urban and suburban public transport, can be divided into three groups according to their priorities, determining the attractiveness particular mode of transport

Uncovering Vulnerable Industrial Control Systems from the Internet Core

Industrial control systems (ICS) are managed remotely with the help of dedicated protocols that were originally designed to work in walled gardens. Many of these protocols have been adapted to Internet transport and support wide-area communication. ICS now exchange insecure traffic on an inter-domain level, putting at risk not only common critical infrastructure but also the Internet ecosystem (e.g., DRDoS~attacks). In this paper, we uncover unprotected inter-domain ICS traffic at two central Internet vantage points, an IXP and an ISP. This traffic analysis is correlated with data from honeypots and Internet-wide scans to separate industrial from non-industrial ICS traffic. We provide an in-depth view on Internet-wide ICS communication. Our results can be used i) to create precise filters for potentially harmful non-industrial ICS traffic, and ii) to detect ICS sending unprotected inter-domain ICS traffic, being vulnerable to eavesdropping and traffic manipulation attacks

Statistical Traffic State Analysis in Large-scale Transportation Networks Using Locality-Preserving Non-negative Matrix Factorization

Statistical traffic data analysis is a hot topic in traffic management and control. In this field, current research progresses focus on analyzing traffic flows of individual links or local regions in a transportation network. Less attention are paid to the global view of traffic states over the entire network, which is important for modeling large-scale traffic scenes. Our aim is precisely to propose a new methodology for extracting spatio-temporal traffic patterns, ultimately for modeling large-scale traffic dynamics, and long-term traffic forecasting. We attack this issue by utilizing Locality-Preserving Non-negative Matrix Factorization (LPNMF) to derive low-dimensional representation of network-level traffic states. Clustering is performed on the compact LPNMF projections to unveil typical spatial patterns and temporal dynamics of network-level traffic states. We have tested the proposed method on simulated traffic data generated for a large-scale road network, and reported experimental results validate the ability of our approach for extracting meaningful large-scale space-time traffic patterns. Furthermore, the derived clustering results provide an intuitive understanding of spatial-temporal characteristics of traffic flows in the large-scale network, and a basis for potential long-term forecasting.Comment: IET Intelligent Transport Systems (2013