1,721,176 research outputs found
Automating bus stop dwell times measurements using London’s iBus: exploiting the data from vehicle location systems
No full textAutomatic Vehicle Location (AVL) systems for buses have been deployed successfully in many cities to improve service operations and provide real-time passenger information. Increasingly these systems are being used to develop further applications, and this paper provides one example using London’s iBus, where events captured historically by vehicles operating on-street in real-time are used to derive automated bus stop dwell time measurements, which are comparable to the observations made on-board vehicles, and the values obtained previously through manual surveys. The method involves running complex algorithms to process large volumes of events log records taken from the small on-board computers of iBus-enabled vehicles, and using these to calculate the Speed Zero durations or stationary times of buses within the stop zone. This method may have similar application in other cities, and has the potential to replace relatively expensive manually surveys, and provide improved dwell time measurements for use in bus priority, for service scheduling, journey time planning and in public transport modelling
Transforming towards people-friendly cities and encouraging active mobility – lessons from the EU Horizon 2020 Metamorphosis Project
No full textUsing the iBus System to provide improved public transport information and applications for London
No full textiBus is Transport for London (TfL)’s innovative GPS-enhanced Automated Vehicle Location System for improving bus fleet management and giving buses priority at traffic signals. Since 2007, the System has been rolled out to the contracted fleet of 8,000+ buses across London, leading to improvements in bus regularity and punctuality, and a reduction in average waiting times. The System also delivers real time “next stop” signage and voice announcements for on board passengers, and is now being integrated with the (“Countdown”) passenger information system at bus stops, to provide improved real-time predictions of vehicle arrivals. The System’s implementation also provides an opportunity to derive other improved public transport information and applications, including profiles of typical journey and bus stop dwell times for management and operational reporting. Dwell times, for example, form an important component in overall bus journey times, and their variability can impact significantly on the effectiveness of systems such as SCOOT to provide bus priority, as well as on overall service performances. The ability to derive typical dwell times therefore helps TfL to optimise the effectiveness of SCOOT (and associated vehicles detectors) in providing bus priority, and their values have potentially wider use in public transport operations, traffic management and simulation modelling. For example, they could provide an improved understanding of the expected delay of vehicles bus stops (and the knock-on impact on other traffic), and help predict more effectively the expected journey times for buses (and other vehicles) in London
Automating bus stop dwell time measurements for London buses using iBus
No full textiBus is Transport for London (TfL)’s GPS-enhanced Automatic Vehicle Location System, which has been rolled out to the entire contracted fleet of over 8,500 buses across London, and resulted in efficiencies in fleet management, improvements in bus waiting times, and provided improved real-time information for passengers. The System resides on board each vehicle, as well as in operators’ bus garages and at the main TfL Control Centre, and records a number of on-street events relating to for example buses’ entry and exit into stop zones, when their doors opened and closed, and their location and speed in real-time. This information, which is collected in the ‘log’ files of every vehicle, provided an opportunity to develop further uses for the System, including an alternative method for measuring bus stop dwell times. Historically, dwell times in London have been obtained using manual road-side surveys, which are relatively expensive, and therefore occur infrequently. However, dwell times and their variability are important to bus operations, network planning and traffic management, and they can affect the ability of urban traffic control systems such as SCOOT to provide buses with priority at traffic signals, which reduces their effectiveness. An alternative method for measuring dwell times using iBus therefore offers many benefits for TfL, provided a process could be determined and largely automated, as the dwell values are not recorded directly by the System, which is relatively complex. A knowledge base of the bus log files therefore had to be developed, and was tested to allow different algorithms, flow charts and programs to be produced for deriving dwell times, based on a sequence of different vehicle speed, stop zone and door events. An experiment was also conducted to validate the dwell times obtained through this method against video data obtained of vehicles stopping on street, which showed a close match between when the vehicle speeds are zero and roadside dwell, although another method, using the duration between when doors opened and closed, provided a close approximation, particularly when an offset value is accounted for. The dwell times obtained through the ‘speed zero’ method in the experiment were then analysed, and this showed wide variations between different bus stops and routes, which are consistent with previous surveys in London, and suggests that generalised values of dwell are inadequate for most applications. The analysis also showed that the dwell time variation by time-of-day is more complex than a traditional morning and afternoon peak, which may reflect changes in ticketing, vehicle modernisation, and the demand made by different types of bus passengers in recent years
Does gender make a difference to performing in-vehicle tasks?
No full textThis study describes the gender differences in driving and visual behaviour observed under a high mental workload. The impacts of performing a set of in-vehicle auditory tasks on the behaviour of 34 drivers were studied in an on-road experiment using an instrumented vehicle. The results show that female participants tended to drive more attentively in baseline driving than males, but they were also more affected by the higher workload. The latter effect was identified by an increase in steering wheel adjustments and a slightly lower auditory task performance. Females adopted a more conservative coping strategy to compensate for the higher workload, as identified by increased headways and more stable lateral control. By contrast, male drivers did not appear to be affected in the same way, but their eye movements revealed significant gaze concentration and less mirror-checking. This suggests that male drivers may be less aware of the impact of mental distractions on their driving performance and visual behaviour, and adopt a simplification strategy to cope with the extra workload. These gender differences in behaviours and coping strategies can be explained only through a combination of traditional measurements and drivers' eye movements, which provide a supplementary measure for understanding driving behaviour. Increased understandings of such gender differences may have significant implications for the design and safe operation of future in-vehicle technologie
The impact of smarter choices of the use of active travel and public transport
No full textThis paper examines the impact of the Local Sustainable Transport Fund (LSTF) and the Better Bus Area Fund (BBAF), with a particular focus on South Hampshire. In particular, it examines the impact on the extent of active travel (walking and cycling) and public transport usage. In so doing, the nudge hypothesis is critically examined. This hypothesis suggests that small changes in choice architecture can lead to large changes in behaviour. In the local transport context, this has meant an emphasis on improvements to information (such as real time information) and marketing (including personalised journey planning). This has often (but not always) coincided with physical improvements including the provision of interchanges, bus priority and cycleways. Before and after surveys are analysed to determine the impact on active travel and public transport. Results are compared with secondary data on road traffic, public transport and active travel usage. The extent of countervailing trends, such as changes in income levels and petrol prices, will be examined
Big data, small changes: evaluating the impact of the local sustainable transport fund on travel behaviour and awareness
No full textA common question asked in current travel behaviour research is whether investment in sustainable travel leads to significant changes in travel behaviour and awareness? In this large-scale study, we looked at the preliminary impact of UK Central Government funding to encourage sustainable modes of transport as implemented by three regional transport authorities and local councils through the Local Sustainable Transport Fund (LSTF). The evaluation method was predominantly quantitative, the main component being a longitudinal postal cohort survey. The survey was conducted in five treatment areas that werethe subject of local LSTF-funded transport interventions, which included physicalinfrastructure upgrades as well as softer measures: a town in Leicestershire; two districts in South Hampshire, and two districts of Greater Manchester. In addition, in each of the three regions, surveys were undertaken in control (or comparison) areas that had not received such interventions. The survey tool comprised a self-completion questionnaire covering respondents’ awareness and usage of various land-based transport modes, including a seven-day travel diary. The initial survey was conducted in December 2013/Spring 2014 (withthe after survey a year later - to follow), and the results compared against identical surveys in the three similar demographic control areas in the three regions. Over 64,000 questionnaires were distributed, which gave rise to a response rate of over 13%, from which nearly 6,800 completed or partially completed records were obtained and analysed. An age-weighting wasapplied to the travel diary data, to account for the variation in the sample versus the demography of the local populations, and the results analysed according to five different travel purposes, using guidance from the UK’s Department for Transport, the project sponsor. The data from this 2013/14 survey suggests there are already small effects arising from the LSTF interventions, particularly from public transport interchange improvements, bus priority measures, demand responsive transport and improved cycling infrastructure. The level of awareness for these schemes is higher in the treatment areas than the control areas, and this is reflected in the travel diary data, which suggests respondents from the treatment areas tend to travel shorter distances per round trip on average, with a significant greater proportion being conducted by bus, and less as car driver. This study also shows the potential of collecting large datasets across different sources for travel behaviour analysis; however further research, including comparisons with cordon counts and results from the follow-on survey, need to be conducted before more substantive conclusions can be drawn
School streets case studies from Southampton - how using temporary street closures and trial interventions can help to gain support for permanent changes to improve our school environments
No full textStreets around our schools are dominated by cars at the start and end of the school day. In Southampton (UK), this has led to high levels of air pollution, unsafe environments for children and parents, and unpleasant conditions for walking, cycling and other social activities. Southampton City Council (SCC), with the support of its major partners, the University of Southampton, Sustrans, and Balfour Beatty, have worked in partnership with local pupils, teachers and residents to transform these unpleasant environments through a combination of street closures, other infrastructure measures, and behavioural change projects. These approaches place the needs and preferences of the local community, and in particular children and young people, at the heart of identifying what steps need to be taken to create safer, cleaner, and more pleasant school environments, which encourage more families to walk, cycle or scoot to school. In our paper, three case studies that explore a range of measures will be presented (see below). These range from one-day street closures, 6-week trials using temporary street furniture, through to ongoing (semi-permanent) physical traffic restrictions. Using these examples, we will describe the lessons learned from adopting each approach, the impact they have had on levels of active travel and changes in driver behaviour at the school gates, and the wider outcomes on the local community and environment, as well as recommendations for other councils and authorities considering this approach
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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