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Citizen reports and social media images that capture the aftermath of natural disasters contain important information for emergency responders. Currently, these data sources are not fully integrated into existing systems or require labour-intensive user input, which can be challenging in critical situations. In this paper, we apply computer vision services to publicly available imagery to derive meaningful information, extract objects and create text descriptions. This research builds on our previous work and enhances available hazard maps with (near) real-time weather and traffic information. Through this geospatial-based workflow, we aim to reduce climate hazard reporting friction and support operational response to incidents.

Collectively the UK investment in transport decarbonisation is greater than £27B from government for incentivising zero-emission vehicles as part of an urgent response to decarbonise the transport sector. The investments made must facilitate a transition to a long-term solution. The success relies on coordinating and testing the evolution of both the energy and transport systems, this avoids the risk of unforeseen consequences in both systems and therefore de-risks investment Here, we present a semiquantitative energy and transport system analysis for UK road freight focusing on two primary investment areas for nation-wide decarbonisation, namely electrification and hydrogen propulsion. Our study assembles and assesses the potential roadblocks of these energy systems into a concise record and considers the infrastructure in relation to all other components within the energy system. It highlights that for system-wide success and resilience, a hydrogen system must overcome hydrogen production and distribution barriers, whereas an electric system needs to optimise storage solutions and charging facilities. Without cohesive, co-evolving energy networks, the planning and operational modelling of transport decarbonisation may fall short of meaningful real-world results. A developed understanding of the dependencies between the energy and transport systems is a necessary step in the development of meaningful operational transport models that could de-risk investment in both the energy and transport systems.

The population of older drivers is increasing in size. However, age-related functional decline potentially reduce their safe driving ability and thereby their wellbeing may decline. Fortunately, the forthcoming highly automated vehicles (HAVs) may have the potential to enhance the mobility of older drivers. HAVs would introduce a revolutionary human-machine interaction in which drivers can be completely disengaged from driving, and their control would be required occasionally. In order to inform the design of an age-friendly human-machine interaction in HAVs, several semi-structured interviews were conducted with 24 older drivers (mean = 71.50 years, SD = 5.93 years; 12 female, 12 male) to explore their opinions of and requirements towards HAV after they had hands-on experience with a HAV on a driving simulator. Results showed that older drivers were positive towards HAVs and welcomed the hands-on experience with HAVs. In addition, they wanted to retain physical and potential control over the HAVs, and would like to perform a range of non-driving related tasks in HAVs. Meanwhile, they required an information system and a monitoring system to support their interactions with HAVs. Moreover, they required the takeover request of HAVs to be adjustable, explanatory and hierarchical, and they would like the driving styles of HAVs to be imitative and corrective. Above all, this research provides recommendations to inform the design of age-friendly human-machine interactions in HAVs and highlights the importance of considering the older drivers’ requirements when designing and developing automated vehicles.

The last few years have seen the emergence of many new technologies that can potentially have major impacts on Intelligent Transportation Systems (ITS). One of these technologies is a micro-electromechanical device called smartdust. A smartdust device (or a mote) is typically composed of a processing unit, some memory, and a radio chip, which allows it to communicate wirelessly with other motes within range. These motes can also be augmented with additional sensors – such as those for detecting light, temperature and acceleration – hence enhancing their features and making their application areas virtually limitless.\ud As the smartdust concept is still relatively new, and very little is known about its application in transport domain, conducting research in this area may prove to be very valuable. It is generally perceived that smartdust will become the low-cost, ubiquitous sensor of the future, especially once its size shrinks dramatically to merit its name.\ud Our involvement in several transport-related EU and UK funded projects (ASTRA, 2005; ASK-IT, 2007; EMMA, 2007; Foot-LITE, 2007; MESSAGE, 2007; TRACKSS, 2007) provides us with an opportunity to carry out experiments and to develop demonstrations of smartdust applications in transport systems. We also have a chance to investigate how smartdust can be used in collaboration with other (more traditional) transport sensors for developing better Co-operative Transport Systems (CTS).\ud This paper outlines our experience in these projects and provides an illustration on the important role that the smartdust technology can play in future ITS. We also present encouraging results obtained from our experiments in investigating the feasibility of utilising smartdust in real ITS applications.