848 resultados para Public transport demand
Resumo:
Current knowledge about the relationship between transport disadvantage and activity space size is limited to urban areas, and as a result, very little is known about this link in a rural context. In addition, although research has identified transport disadvantaged groups based on their size of activity space, these studies have, however, not empirically explained such differences and the result is often a poor identification of the problems facing disadvantaged groups. Research has shown that transport disadvantage varies over time. The static nature of analysis using the activity space concept in previous research studies has lacked the ability to identify transport disadvantage in time. Activity space is a dynamic concept; and therefore possesses a great potential in capturing temporal variations in behaviour and access opportunities. This research derives measures of the size and fullness of activity spaces for 157 individuals for weekdays, weekends, and for a week using weekly activity-travel diary data from three case study areas located in rural Northern Ireland. Four focus groups were also conducted in order to triangulate quantitative findings and to explain the differences between different socio-spatial groups. The findings of this research show that despite having a smaller sized activity space, individuals were not disadvantaged because they were able to access their required activities locally. Car-ownership was found to be an important life line in rural areas. Temporal disaggregation of the data reveals that this is true only on weekends due to a lack of public transport services. In addition, despite activity spaces being at a similar size, the fullness of activity spaces of low-income individuals was found to be significantly lower compared to their high-income counterparts. Focus group data shows that financial constraint, poor connections both between public transport services and between transport routes and opportunities forced individuals to participate in activities located along the main transport corridors.
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The majority of the world’s population now lives in cities (United Nations, 2008) resulting in an urban densification requiring people to live in closer proximity and share urban infrastructure such as streets, public transport, and parks within cities. However, “physical closeness does not mean social closeness” (Wellman, 2001, p. 234). Whereas it is a common practice to greet and chat with people you cross paths with in smaller villages, urban life is mainly anonymous and does not automatically come with a sense of community per se. Wellman (2001, p. 228) defines community “as networks of interpersonal ties that provide sociability, support, information, a sense of belonging and social identity.” While on the move or during leisure time, urban dwellers use their interactive information communication technology (ICT) devices to connect to their spatially distributed community while in an anonymous space. Putnam (1995) argues that available technology privatises and individualises the leisure time of urban dwellers. Furthermore, ICT is sometimes used to build a “cocoon” while in public to avoid direct contact with collocated people (Mainwaring et al., 2005; Bassoli et al., 2007; Crawford, 2008). Instead of using ICT devices to seclude oneself from the surrounding urban environment and the collocated people within, such devices could also be utilised to engage urban dwellers more with the urban environment and the urban dwellers within. Urban sociologists found that “what attracts people most, it would appear, is other people” (Whyte, 1980, p. 19) and “people and human activity are the greatest object of attention and interest” (Gehl, 1987, p. 31). On the other hand, sociologist Erving Goffman describes the concept of civil inattention, acknowledging strangers’ presence while in public but not interacting with them (Goffman, 1966). With this in mind, it appears that there is a contradiction between how people are using ICT in urban public places and for what reasons and how people use public urban places and how they behave and react to other collocated people. On the other hand there is an opportunity to employ ICT to create and influence experiences of people collocated in public urban places. The widespread use of location aware mobile devices equipped with Internet access is creating networked localities, a digital layer of geo-coded information on top of the physical world (Gordon & de Souza e Silva, 2011). Foursquare.com is an example of a location based 118 Mobile Multimedia – User and Technology Perspectives social network (LBSN) that enables urban dwellers to virtually check-in into places at which they are physically present in an urban space. Users compete over ‘mayorships’ of places with Foursquare friends as well as strangers and can share recommendations about the space. The research field of Urban Informatics is interested in these kinds of digital urban multimedia augmentations and how such augmentations, mediated through technology, can create or influence the UX of public urban places. “Urban informatics is the study, design, and practice of urban experiences across different urban contexts that are created by new opportunities of real-time, ubiquitous technology and the augmentation that mediates the physical and digital layers of people networks and urban infrastructures” (Foth et al., 2011, p. 4). One possibility to augment the urban space is to enable citizens to digitally interact with spaces and urban dwellers collocated in the past, present, and future. “Adding digital layer to the existing physical and social layers could facilitate new forms of interaction that reshape urban life” (Kjeldskov & Paay, 2006, p. 60). This methodological chapter investigates how the design of UX through such digital placebased mobile multimedia augmentations can be guided and evaluated. First, we describe three different applications that aim to create and influence the urban UX through mobile mediated interactions. Based on a review of literature, we describe how our integrated framework for designing and evaluating urban informatics experiences has been constructed. We conclude the chapter with a reflective discussion on the proposed framework.
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Deterministic transit capacity analysis applies to planning, design and operational management of urban transit systems. The Transit Capacity and Quality of Service Manual (1) and Vuchic (2, 3) enable transit performance to be quantified and assessed using transit capacity and productive capacity. This paper further defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures the transit task performed over distance. Passenger transmission (p-km/h) captures the passenger task delivered by service at speed. Transit productiveness (p-km/h) captures transit work performed over time. These measures are useful to operators in understanding their services’ or systems’ capabilities and passenger quality of service. This paper accounts for variability in utilized demand by passengers along a line and high passenger load conditions where passenger pass-up delay occurs. A hypothetical case study of an individual bus service’s operation demonstrates the usefulness of passenger transmission in comparing existing and growth scenarios. A hypothetical case study of a bus line’s operation during a peak hour window demonstrates the theory’s usefulness in examining the contribution of individual services to line productive performance. Scenarios may be assessed using this theory to benchmark or compare lines and segments, conditions, or consider improvements.
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Despite of a significant contribution of transport sector in the global economy and society, it is one of the largest sources of global energy consumption, green house gas emissions and environmental pollutions. A complete look onto the whole life cycle environmental inventory of this sector will be helpful to generate a holistic understanding of contributory factors causing emissions. Previous studies were mainly based on segmental views which mostly compare environmental impacts of different modes of transport, but very few consider impacts other than the operational phase. Ignoring the impacts of non-operational phases, e.g., manufacture, construction, maintenance, may not accurately reflect total contributions on emissions. Moreover an integrated study for all motorized modes of road transport is also needed to achieve a holistic estimation. The objective of this study is to develop a component based life cycle inventory model which considers impacts of both operational and non-operational phases of the whole life as well as different transport modes. In particular, the whole life cycle of road transport has been segmented into vehicle, infrastructure, fuel and operational components and inventories have been conducted on each component. The inventory model has been demonstrated using the road transport of Singapore. Results show that total life cycle green house gas emissions from the road transport sector of Singapore is 7.8 million tons per year, among which operational phase and non-operational phases contribute about 55% and about 45%, respectively. Total amount of criteria air pollutants are 46, 8.5, 33.6, 13.6 and 2.6 thousand tons per year for CO, SO2, NOx, VOC and PM10, respectively. From the findings, it can be deduced that stringent government policies on emission control measures have a significant impact on reducing environmental pollutions. In combating global warming and environmental pollutions the promotion of public transport over private modes is an effective sustainable policy.
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Transit oriented developments (TODs) are master planned communities constructed to reduce the dependence on the private car and promote the modes of transport such as public transport, walking and cycling, which are presumed by many transport professionals to be more sustainable. This paper tests this assumption that TOD is a more sustainable form of development than traditional development, with respect to travel demand, by conducting travel surveys for a case study TOD and comparing the travel characteristics of TOD residents with the travel characteristics of residents of Brisbane, Australia who live in non TOD suburbs. The results of a household comparison showed that the Kelvin Grove Urban Village (KGUV) households had slightly smaller household size, lower vehicle and bicycle ownership compared to Brisbane Statistical Division (BSD), Brisbane’s inner north and inner south suburbs. The comparison of average trip characteristics showed that on an average KGUV residents undertook fewer trips on the given travel day (2.6 trips/person) compared to BSD (3.1 trips/person), Brisbane Inner North Suburbs (BINS) (3.6 trips/person) and Brisbane Inner South Suburbs (BISS) (3.5 trips/person) residents. The mode share comparison indicated that KGUV residents used more public transport and made more walk-only trips in comparison to BSD, BINS and BISS residents. Overall, 72.4 percent of KGUV residents used a sustainable mode of transport for their travel on a typical weekday. On the other hand, only 17.4 percent, 22.2 percent and 24.4 percent residents of BSD, BINS and BISS used sustainable modes of transport for this travel. The results of trip length comparison showed that overall KGUV residents have smaller average trip lengths as compared to its counterparts. KGUV & BINS residents used car for travelling farther and used public transport for accessing destinations located closer to their homes. On the contrary, BSD and BISS residents exhibited an opposite trend. These results support the transportation claims of many transport professionals that TODs are more transport efficient and therefore more sustainable in this respect.
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Besides responding to challenges of rapid urbanization and growing traffic congestion, the development of smart transport systems has attracted much attention in recent times. Many promising initiatives have emerged over the years. Despite these initiatives, there is still a lack of understanding about an appropriate definition of smart transport system. As such, it is challenging to identify the appropriate indicators of ‘smartness’. This paper proposes a comprehensive and practical framework to benchmark cities according to the smartness in their transportation systems. The proposed methodology was illustrated using a set of data collected from 26 cities across the world through web search and contacting relevant transport authorities and agencies. Results showed that London, Seattle and Sydney were among the world’s top smart transport cities. In particular, Seattle and Paris ranked high in smart private transport services while London and Singapore scored high on public transport services. London also appeared to be the smartest in terms of emergency transport services. The key value of the proposed innovative framework lies in a comparative analysis among cities, facilitating city-to-city learning.
Resumo:
The global financial crisis (GFC) in 2008 rocked local, regional, and state economies throughout the world. Several intermediate outcomes of the GFC have been well documented in the literature including loss of jobs and reduced income. Relatively little research has, however, examined the impacts of the GFC on individual level travel behaviour change. To address this shortcoming, HABITAT panel data were employed to estimate a multinomial logit model to examine mode switching behaviour between 2007 (pre-GFC) and 2009 (post-GFC) of a baby boomers cohort in Brisbane, Australia—a city within a developed country that has been on many metrics the least affected by the GFC. In addition, a Poisson regression model was estimated to model the number of trips made by individuals in 2007, 2008, and 2009. The South East Queensland Travel Survey datasets were used to develop this model. Four linear regression models were estimated to assess the effects of the GFC on time allocated to travel during a day: one for each of the three travel modes including public transport, active transport, less environmentally friendly transport; and an overall travel time model irrespective of mode. The results reveal that individuals were more likely to switch to public transport who lost their job or whose income reduced between 2007 and 2009. Individuals also made significantly fewer trips in 2008 and 2009 compared to 2007. Individuals spent significantly less time using less environmentally friendly transport but more time using public transport in 2009. Baby boomers switched to more environmentally friendly travel modes during the GFC.
Resumo:
Background Understanding how different socioeconomic indicators are associated with transport modes provide insight into which interventions might contribute to reducing socioeconomic inequalities in health. The purpose of this study was to examine associations between neighbourhood-level socioeconomic disadvantage, individual-level socioeconomic position (SEP) and usual transport mode. Methods This investigation included 11,036 residents from 200 neighbourhoods in Brisbane, Australia. Respondents self-reported their usual transport mode (car or motorbike, public transport, walking or cycling). Indicators for individual-level SEP were education, occupation, and household income; and neighbourhood disadvantage was measured using a census-derived index. Data were analysed using multilevel multinomial logistic regression. High SEP respondents and residents of the most advantaged neighbourhoods who used a private motor vehicle as their usual form of transport was the reference category. Results Compared with driving a motor vehicle, the odds of using public transport were higher for white collar employees (OR1.68, 95%CrI 1.41-2.01), members of lower income households (OR 1.71 95%CrI 1.25-2.30), and residents of more disadvantaged neighbourhoods (OR 1.93, 95%CrI 1.46-2.54); and lower for respondents with a certificate-level education (OR 0.60, 95%CrI 0.49-0.74) and blue collar workers (OR 0.63, 95%CrI 0.50-0.81). The odds of walking for transport were higher for the least educated (OR 1.58, 95%CrI 1.18-2.11), those not in the labour force (OR 1.94, 95%CrI 1.38-2.72), members of lower income households (OR 2.10, 95%CrI 1.23-3.64), and residents of more disadvantaged neighbourhoods (OR 2.73, 95%CrI 1.46-5.24). The odds of cycling were lower among less educated groups (OR 0.31, 95% CrI 0.19-0.48). Conclusion The relationships between socioeconomic characteristics and transport modes are complex, and provide challenges for those attempting to encourage active forms of transportation. Further work is required exploring the individual- and neighbourhood-level mechanisms behind transport mode choice, and what factors might influence individuals from different socioeconomic backgrounds to change to more active transport modes.
Resumo:
There is a long tradition of social inquiry concerned with locational patterns and place-based explanations of crime in which urban/rural differences have been regarded as of cardinal importance. The geographical and socio-spatial aspects of punishment have on the other hand been widely neglected. One reason for this is that cities have been treated as the site of the major crime problems, presenting a contrast with what are commonly assumed (often without careful empirical research) to be the naturally cohesive character of rural communities. Thus punishment, like crime, is not a significant or distinctive issue in rural communities, requiring the attention of criminologists. But just as there are significant and distinctive dimensions to rural crime, the practice of punishment in rural contexts raises important questions worthy of attention. These questions relate to (1) the demand for punishment (i.e. the penal sensibilities to be found in rural communities); (2) the supply of punishment according to principles of legal equality (notably the question of the effective availability in rural courts of the full range of penalties administered by urban courts, in particular alternatives to incarceration); and (3) the differential impact of the same penalties when imposed in different geographical settings (e.g. imprisonment may involve distant removal from an offender’s community in addition to segregation from it; license disqualification is a great deal more consequential in settings where public transport is unavailable). The chapter examines these questions by reference to available knowledge concerning patterns of punishment in rural Australia. This will be set against the background of an analysis of the differential social organisation of penality in rural and urban settings. The generally more attenuated nature of the social state and social provision in rural contexts can, depending upon the profile of particular communities (and in particular their degree of social homogeneity), produce very different penal consequences: more heavy reliance on the penal state on the one hand, or greater recourse to informal social controls on the other.
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This paper focuses on urban road pricing as a demand management policy that is often regarded as radical and generally unacceptable. Road pricing often gets delayed or abandoned due to low acceptability. This may be due to the fact that complex interactions and drivers of change affect road transport management and require cooperation within implementation networks. The implementation network is a group of people (referred to as partners and actors) who co-ordinate the introduction of policy tools. The drivers of change include any internal or external influences that have an effect on the time, place, or ‘shape’ of the policy measures being introduced. Demand management measures that focus on 'sustainable transport' usually address a limited set of objectives and are often implemented alone i.e. are not necessarily combined with other policy measures. When combined with other measures, it is not always clear whether the multiple interactions between policy tools and implementation networks have been sufficiently considered. Examples of ongoing implementation of policy package in the UK are the support of road pricing initiatives combined with public transport improvements by the Transport Innovation Fund. The objectives of the paper are twofold. First, we present a review of the UK urban road pricing situation. Second, we contrast the emerging issues against six key implementation factors. The analysis of three existing UK road pricing examples - London, Edinburgh and Durham – shows the importance of combining policy tools. Furthermore, through the above examples and theoretical arguments, we emphasise the additional need of creating and maintaining strong networks when implementing policy packages.
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Much of the interest in promoting sustainable development in planning for the city-region focuses on the apparently inexorable rise in the demand for car travel and the contribution that certain urban forms and land-use relationships can make to reducing energy consumption. Within this context, policy prescription has increasingly favoured a compact city approach with increasing urban residential densities to address the physical separation of daily activities and the resultant dependency on the private car. This paper aims to outline and evaluate recent efforts to integrate land use and transport policy in the Belfast Metropolitan Area in Northern Ireland. Although considerable progress has been made, this paper underlines the extent of existing car dependency in the metropolitan area and prevailing negative attitudes to public transport, and argues that although there is a rhetorical support for the principles of sustainability and the practice of land-use/transportation integration, this is combined with a selective reluctance to embrace local changes in residential environment or in lifestyle preferences which might facilitate such principles.
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Environmental concerns relating to gaseous emissions from transport have led to growth in the use of compressed natural gas vehicles worldwide with an estimated 13 million Natural Gas Vehicles (NGVs) currently in operation. Across Europe, many countries are replacing traditional diesel oil in captive fleets such as buses used for public transport and heavy and light goods vehicles used for freight and logistics with CNG vehicles. Initially this was to reduce localised air pollution in urban environments. However, with the need to reduce greenhouse gas emissions CNG is seen as a cleaner more energy efficient and environmental friendly alternative. This paper briefly examines the growth of NGVs in Europe and worldwide. Then a case study on CNG the introduction in Spain and Italy is presented. As part of the case study, policy interventions are examined. Finally, a statistical analysis of private and public refuelling stations in both countries is also provided. CNG can also be mixed with biogas. This study and the role of CNG is relevant because of the existing European Union Directive 2009/28/EC target, requiring that 10% of transport energy come from renewable sources, not alone biofuels such as biogas. CNG offers another alternative transport fuel.
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In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.
Resumo:
Demand for intelligent surveillance in public transport systems is growing due to the increased threats of terrorist attack, vandalism and litigation. The aim of intelligent surveillance is in-time reaction to information received from various monitoring devices, especially CCTV systems. However, video analytic algorithms can only provide static assertions, whilst in reality, many related events happen in sequence and hence should be modeled sequentially. Moreover, analytic algorithms are error-prone, hence how to correct the sequential analytic results based on new evidence (external information or later sensing discovery) becomes an interesting issue. In this paper, we introduce a high-level sequential observation modeling framework which can support revision and update on new evidence. This framework adapts the situation calculus to deal with uncertainty from analytic results. The output of the framework can serve as a foundation for event composition. We demonstrate the significance and usefulness of our framework with a case study of a bus surveillance project.