1,721,073 research outputs found
Using human interaction to improve transport models
No full textThis presentation highlighted that while computers are good at detailed repetative tasks, humans are much better at 'seeing' the bigger picture. To enable the best models therefore takes a combination of human intelligence and electronic persistence
Perceptions of personal impact: why air quality concerns often do not lead to behavioural change
No full textWhen virtual networks meet physical networks: perils of data mining for real-time transport information
No full textReal time monitoring of the state of a transport system has been a worldwide research topic since long before the current era of social-media and big-data began to arrive. The breadth of overlapping data sources and depth of information now available (both deliberately and accidentally) about our everyday travel behaviour however creates a range of new technical and ethical challenges. This talk therefore seeks to explore some of the perils of data mining for real time transport information, including the difficulties of identifying physical locations from textual descriptions in social media; the misinterpretation of automated tracking data; and the awkward question of should we worry about our location being constantly known
Urban intersection management strategies for Autonomous/Connected/Conventional Vehicle fleet mixtures
No full textConnected Vehicles and Autonomous Vehicles (CAVs) provide various sources of vehicular related information to intersection infrastructure by integrating on-board sensors processing, wireless communication and other Vehicle-to-Infrastructure (V2I) technologies. Thus connected vehicle technologies can potentially remedy data collection limitations of existing urban intersection managements, enhancing the performances of intersection controls such as reducing vehicle delay, reducing vehicle number of stops and improving energy efficiency. This paper reviews optimization-based signal controls for different penetrations of connected vehicles and conventional vehicles environments, autonomous intersection management specific to completely 100% AVs road states, as well as signal-trajectory joint control for different adoptions of conventional vehicles, CVs and AVs mixture environments. Real time data processing, signal timing optimizations, vehicle trajectory motion planning and evaluation frameworks are summarized to highlight the advantages and limitations of respective intersection control paradigms. It is important to recognize that realistic scenarios in comparative assessments for proposed methods need to be achieved in future works. The effectiveness of different approaches is challenging to be compared without complete evaluation frameworks, and sensitivity analysis and hypothesis tests involving variety penetration rates and flow demands should be performed in order to test the stability of methods in different scenarios
Are privacy fears associated with Intelligent Transport Systems justified?
No full textThe creation of wide-area, real-time monitoring systems for the road network has the potential to achieve a step change in both our understanding of the evolution of congestion and forecasting/information to minimise its economic consequences. While such comprehensive monitoring systems will provide unprecedented levels of information about the network as a whole, however, they also potentially provide substantial information about individual vehicles and individual travellers. There are therefore concerns within the general public that the potential privacy invasions resulting from this increased monitoring will create a ‘Big Brother’ or panopticon state. This paper examines whether these fears are justified. While it is shown that people’s views on privacy are very heterogeneous (varying from completely unconcerned, to concerned to the point of paranoia), drawing on research conducted into both general privacy and the privacy concerns associated with ecommerce, it is identified that the most appropriate definition of a privacy impact is where the increased monitoring associated with intelligent transport systems (ITS) restricts the perceived freedom of travel that an individual currently experiences.This paper therefore considers how the privacy concerns associated with ITS fall into six distinct areas: the volume and type of data collected; errors in the data collected; unauthorised secondary uses of the data collected; inappropriate use of the data collected; a lack of awareness about what the data will be used for; and a lack of control over who can gain access to the data. By identifying the relative importance of these concerns and their applicability to ITS monitoring, this paper considers whether there is evidence that privacy concerns actually impact people’s behaviour or, through contrasts with the potential benefits of increased monitoring, whether there exists a level at which individuals are willing to trade their personal data for an individual, (or potentially even a societal), benefit. <br/
Privacy decision-making in the travel panopticon
No full textIntelligent Transport Systems (ITS) have the potential to increase road-network capacities, reduce congestion and pollution, create shorter and more predictable journey times and significantly improve road-user safety. However, these technologies will also have the ability to track a citizen’s every move, extracting information about their daily lives. It has been argued that privacy invasions caused by ITS will have a damaging effect on society, creating a ‘Big Brother’ or panopticon state.For these fears to be fulfilled, it needs to be the case that citizens are not only concerned about the privacy impacts of ITS, but that the ITS will actually cause citizens to change their travel behaviour. This paper explores the privacy decision making process individuals will use to determine whether the implementation of future ITS will cause them to change their travel behaviour. The results of a Europe-wide survey have shown that when faced with a decision about whether to disclose personal information or not, future ITS users will be more influenced by irrational factors than rational ones. In addition, users will be more influenced by their perceptions of the risks associated with disclosing personal information (data sensitivity, trust in the data holder and trust in the transfer method) than the reward on offer.<br/
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