Technical article reproduced with permission from Transportation Professional - the magazine of the Chartered Institution of Highways & Transportation
www.ciht.org.uk/en/knowledge/publications/transportation-professional/index.cfm
Next Generation Intelligent Transportation: Solutions for Smart CitiesUGPTI
This March 1 seminar presentation provided an overview of key technology trends that are steadily transforming our transportation system. Bridgelall provided a sample of research needs that exposed the complexities and interdependencies between transportation supply, transportation demand, performance measures, and policy making.
The End of Transport Behaviour ModellingAndrew Nash
Presentation on how social media could impact transportation behaviour modelling. Prepared for COST Action TU1305: Social Networks and Travel Behaviour. Presented 15 October 2015, Technion, Haifa.
Transport for Cairo is an ambitious project that seeks to map all formal and informal transportation in Cairo digitally, and release all data openly.
This Presentation is outdated as of April 2016.
Next Generation Intelligent Transportation: Solutions for Smart CitiesUGPTI
This March 1 seminar presentation provided an overview of key technology trends that are steadily transforming our transportation system. Bridgelall provided a sample of research needs that exposed the complexities and interdependencies between transportation supply, transportation demand, performance measures, and policy making.
The End of Transport Behaviour ModellingAndrew Nash
Presentation on how social media could impact transportation behaviour modelling. Prepared for COST Action TU1305: Social Networks and Travel Behaviour. Presented 15 October 2015, Technion, Haifa.
Transport for Cairo is an ambitious project that seeks to map all formal and informal transportation in Cairo digitally, and release all data openly.
This Presentation is outdated as of April 2016.
Big data: uncovering new mobility patterns and redefining planning practicesMickael Pero
Using representations and data that are digital, we can create images about what happens where and when in cities, including mobility patterns that remained unaccounted until now. If properly analysed, big data for mobility can radically improve the socioeconomic and environmental analysis of public and sustainable transport. This session will discuss how big data is affecting mobility in terms of new travel behaviour and transport planning. At the user level, the relations between social networks, social media usage and travel behaviour in EU countries will be discussed. Scientific insight on the social media usage of millennial students in EU countries to understand their impact on social activities and mobility in urban areas will be presented. At the planer level, responses to changes in mobility patterns or unaccounted needs given by the analysis of public transport smart data will be presented. Advances on an integrated accessibility index will be discussed as a way for policy makers to improve current transport planning practices. Yet, big data in transport is not immune from some problems, especially those relating to statistical validity, bias and incorrectly imputed causality. This point will be discussed alongside liability, since Big data is gathered and manipulated by many different stakeholders. The proposed panel discussion therefore aims to provide to the audience a clear understanding on ways in which big data affects travel behaviour and transport planning, while accounting for data quality and pan European standardisation aspects.
Questions?
Join the conversation at @dovuapi or DM arwen@dovu.io.
Summary
Moving from A-B is slowly being revolutionised through data. Car-sharing and ride-hailing are just the beginning. Thousands of connected devices are currently monitoring data points, and although stand-alone analysis can be useful, true innovation occurs when these data sets are combined to transform into something new.
In the near future, IoT data explosion and the API revolution will collide to change city planning, urban movement and the role of the car in the 21st century.
- First off, we set out to understand what big data means in the context of transportation, answering questions such as what is it, where is it coming from, and what can you do with it.
- Next, we'll zoom out and apply these learning to transport innovation in a wider context, considering how it will influence concepts such as urban movement, social mobility, and quality of life.
- Finally, we'll discuss the relationship between open data and innovation.
Networked Society City Index 2013 Case Studies Ericsson
http://www.ericsson.com/thinkingahead/networked_society/city-life
Case studies from the 2013 Networked Society City Index which features 31 major world cities and measures their ICT maturity as well as the economic, social and environmental dimensions, called the “triple bottom line” effects.
Projectes inLab en l'àrea de les comunicacions mòbilsinLabFIB
Presentació dels projectes de l'inLab en l'àrea d'aplicacions mòbils, exposada per Jaume Figueras el dia 21 de març de 2013 a l'acte organitzat pel Centre d’Innovació i Tecnologia (CIT UPC) de presentació d'alguns exemples de les capacitats tecnològiques de la UPC en l’àrea de les comunicacions mòbils.
Short presentation about the role of AMS in solving Amsterdam mobility issues and setting the mobility agenda. Linking science and practise using Amsterdam as a Living Lab.
EDF2014: Talk of Vassileios Tsetsos, Chief Technical Officer, Mobics Ltd: Pre...European Data Forum
Selected Talk of Vassileios Tsetsos, Chief Technical Officer, Mobics Ltd at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Predicting parking occupancy in a sensor-enabled smart city
EDF2014: Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany: ...European Data Forum
Industry Keynote Talk by Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Probe Data Analytics and Processing for Traffic Information, Traffic Planning and Traffic Management.
Presented at the ICCVE 3-7 Nov 2014, Vienna, Austria
P1 Plenary session:
Which technologies will pave the way to automated vehicles? Which industry sector is expected to take a leading role?
Vision-based real-time vehicle detection and vehicle speed measurement using ...JANAK TRIVEDI
In recent trends, digital information to the industrial integration for the intelligent transportation system (ITS)
field is gaining importance for the researcher, academia, and industrial persons. Visual information helps to
manage traffic systems in the industrial forum to build smart cities in developed countries. This paper presents
vision-based real-time vehicle detection and Vehicle Speed Measurement (VSM) using morphology operation and
binary logical process for an unplanned traffic scenario using image processing techniques. Vehicle detection and
VSM help to reduce the number of accidents and improve road network efficiency. The bounding box size for
vehicle detection is flexible according to vehicles’ sizes on the road. We test this system with different colors and
dimensions for a selected Region of Interest (ROI). The ROI sets using the two-line approach. Here, we compare
the proposed system with the inter-frame difference method and the blob analysis method with recall, precision,
and F1 performance parameters.
Cities in Motion: Mapping Singapore’s Night-time Economy through Taxi DataAkshay Regulagedda
We studied taxi-data from 2016 to 2021 shared by Singapore’s Land Transport Authority, and generate a tool that could showcase how availability of taxis has changed in various districts before and after the Covid lockdown measures.
Big Data and Transport Understanding and assessing optionsLudovic Privat
The International Transport Forum at the OECD is an intergovernmental organisation with 54 member
countries. It acts as a think tank for transport policy and organises the Annual Summit of transport
ministers. ITF is the only global body that covers all transport modes.
ITF works for transport policies that improve peoples’ lives. Our mission is to foster a deeper understanding
of the role of transport in economic growth, environmental sustainability and social inclusion and to raise
the public profile of transport policy.
ITF organises global dialogue for better transport. We act as a platform for discussion and pre-negotiation
of policy issues across all transport modes. We analyse trends, share knowledge and promote exchange
among transport decision makers and civil society.
RhinoStreet -- A Crowdsourcing platform for Road Toll monitoringKofi Kafui Kornu
RhinoStreet is an alternative to help citizens mostly to have an idea of how much revenue is being made by the road tolls in the country, and juxtapose that with the figures the government presents. Armed with such information, citizens can push to have better, maintained roads and invariably also help prevent road accidents and other related occurrences.The platform would be web-based and allow contributors to share pictures of toll tickets they have bought, or enter amounts spent on toll tickets,while specifying the toll booth they bought it from. These entries would then be aggregated and analysed on a monthly basis considering monies generated at the individual toll booths, to have a sense of how much is being generated by the country's road tolls and mapped to the government's data to ensure accountability, and also ensure that roads in the country are repaired, improved, and maintained, as the open data got is a tool to drive policy-formation. This is believed to also create a data-driven culture which would enhance evidence-based decision-making and policy formation.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using location awareness applications installed in mobile devices, data related to user mobility were collected by using crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to overcome the problem. By using this, the best transportation method can be predicted as the results of the research. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper
way to predict the traffic and recommend the best route considering the time factor and the people’s
satisfaction on various transportation methods. Therefore, in this research using location awareness
applications installed in mobile devices, data related to user mobility were collected by using
crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to
overcome the problem. By using this, the best transportation method can be predicted as the results of the
research. Therefore, people can choose what will be the best time slots & transportation methods when
planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
Big data: uncovering new mobility patterns and redefining planning practicesMickael Pero
Using representations and data that are digital, we can create images about what happens where and when in cities, including mobility patterns that remained unaccounted until now. If properly analysed, big data for mobility can radically improve the socioeconomic and environmental analysis of public and sustainable transport. This session will discuss how big data is affecting mobility in terms of new travel behaviour and transport planning. At the user level, the relations between social networks, social media usage and travel behaviour in EU countries will be discussed. Scientific insight on the social media usage of millennial students in EU countries to understand their impact on social activities and mobility in urban areas will be presented. At the planer level, responses to changes in mobility patterns or unaccounted needs given by the analysis of public transport smart data will be presented. Advances on an integrated accessibility index will be discussed as a way for policy makers to improve current transport planning practices. Yet, big data in transport is not immune from some problems, especially those relating to statistical validity, bias and incorrectly imputed causality. This point will be discussed alongside liability, since Big data is gathered and manipulated by many different stakeholders. The proposed panel discussion therefore aims to provide to the audience a clear understanding on ways in which big data affects travel behaviour and transport planning, while accounting for data quality and pan European standardisation aspects.
Questions?
Join the conversation at @dovuapi or DM arwen@dovu.io.
Summary
Moving from A-B is slowly being revolutionised through data. Car-sharing and ride-hailing are just the beginning. Thousands of connected devices are currently monitoring data points, and although stand-alone analysis can be useful, true innovation occurs when these data sets are combined to transform into something new.
In the near future, IoT data explosion and the API revolution will collide to change city planning, urban movement and the role of the car in the 21st century.
- First off, we set out to understand what big data means in the context of transportation, answering questions such as what is it, where is it coming from, and what can you do with it.
- Next, we'll zoom out and apply these learning to transport innovation in a wider context, considering how it will influence concepts such as urban movement, social mobility, and quality of life.
- Finally, we'll discuss the relationship between open data and innovation.
Networked Society City Index 2013 Case Studies Ericsson
http://www.ericsson.com/thinkingahead/networked_society/city-life
Case studies from the 2013 Networked Society City Index which features 31 major world cities and measures their ICT maturity as well as the economic, social and environmental dimensions, called the “triple bottom line” effects.
Projectes inLab en l'àrea de les comunicacions mòbilsinLabFIB
Presentació dels projectes de l'inLab en l'àrea d'aplicacions mòbils, exposada per Jaume Figueras el dia 21 de març de 2013 a l'acte organitzat pel Centre d’Innovació i Tecnologia (CIT UPC) de presentació d'alguns exemples de les capacitats tecnològiques de la UPC en l’àrea de les comunicacions mòbils.
Short presentation about the role of AMS in solving Amsterdam mobility issues and setting the mobility agenda. Linking science and practise using Amsterdam as a Living Lab.
EDF2014: Talk of Vassileios Tsetsos, Chief Technical Officer, Mobics Ltd: Pre...European Data Forum
Selected Talk of Vassileios Tsetsos, Chief Technical Officer, Mobics Ltd at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Predicting parking occupancy in a sensor-enabled smart city
EDF2014: Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany: ...European Data Forum
Industry Keynote Talk by Ralf-Peter Schaefer, Head of Traffic Product Unit, TomTom, Germany at the European Data Forum 2014, 20 March 2014 in Athens, Greece: Probe Data Analytics and Processing for Traffic Information, Traffic Planning and Traffic Management.
Presented at the ICCVE 3-7 Nov 2014, Vienna, Austria
P1 Plenary session:
Which technologies will pave the way to automated vehicles? Which industry sector is expected to take a leading role?
Vision-based real-time vehicle detection and vehicle speed measurement using ...JANAK TRIVEDI
In recent trends, digital information to the industrial integration for the intelligent transportation system (ITS)
field is gaining importance for the researcher, academia, and industrial persons. Visual information helps to
manage traffic systems in the industrial forum to build smart cities in developed countries. This paper presents
vision-based real-time vehicle detection and Vehicle Speed Measurement (VSM) using morphology operation and
binary logical process for an unplanned traffic scenario using image processing techniques. Vehicle detection and
VSM help to reduce the number of accidents and improve road network efficiency. The bounding box size for
vehicle detection is flexible according to vehicles’ sizes on the road. We test this system with different colors and
dimensions for a selected Region of Interest (ROI). The ROI sets using the two-line approach. Here, we compare
the proposed system with the inter-frame difference method and the blob analysis method with recall, precision,
and F1 performance parameters.
Cities in Motion: Mapping Singapore’s Night-time Economy through Taxi DataAkshay Regulagedda
We studied taxi-data from 2016 to 2021 shared by Singapore’s Land Transport Authority, and generate a tool that could showcase how availability of taxis has changed in various districts before and after the Covid lockdown measures.
Big Data and Transport Understanding and assessing optionsLudovic Privat
The International Transport Forum at the OECD is an intergovernmental organisation with 54 member
countries. It acts as a think tank for transport policy and organises the Annual Summit of transport
ministers. ITF is the only global body that covers all transport modes.
ITF works for transport policies that improve peoples’ lives. Our mission is to foster a deeper understanding
of the role of transport in economic growth, environmental sustainability and social inclusion and to raise
the public profile of transport policy.
ITF organises global dialogue for better transport. We act as a platform for discussion and pre-negotiation
of policy issues across all transport modes. We analyse trends, share knowledge and promote exchange
among transport decision makers and civil society.
RhinoStreet -- A Crowdsourcing platform for Road Toll monitoringKofi Kafui Kornu
RhinoStreet is an alternative to help citizens mostly to have an idea of how much revenue is being made by the road tolls in the country, and juxtapose that with the figures the government presents. Armed with such information, citizens can push to have better, maintained roads and invariably also help prevent road accidents and other related occurrences.The platform would be web-based and allow contributors to share pictures of toll tickets they have bought, or enter amounts spent on toll tickets,while specifying the toll booth they bought it from. These entries would then be aggregated and analysed on a monthly basis considering monies generated at the individual toll booths, to have a sense of how much is being generated by the country's road tolls and mapped to the government's data to ensure accountability, and also ensure that roads in the country are repaired, improved, and maintained, as the open data got is a tool to drive policy-formation. This is believed to also create a data-driven culture which would enhance evidence-based decision-making and policy formation.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using location awareness applications installed in mobile devices, data related to user mobility were collected by using crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to overcome the problem. By using this, the best transportation method can be predicted as the results of the research. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper
way to predict the traffic and recommend the best route considering the time factor and the people’s
satisfaction on various transportation methods. Therefore, in this research using location awareness
applications installed in mobile devices, data related to user mobility were collected by using
crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to
overcome the problem. By using this, the best transportation method can be predicted as the results of the
research. Therefore, people can choose what will be the best time slots & transportation methods when
planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
The increasing need for traffic detection system has become a vital area in both developing and developed
countries. However, it is more important to get the accurate and valuable data to give the better result
about traffic condition. For this reason, this paper proposes an approach of tracking traffic data as cheap
as possible in terms of communication, computation and energy efficient ways by using mobile phone
network. This system gives the information of which vehicles are running on which location and how much
speed for the Traffic Detection System. The GPS sensor of mobile device will be mainly utilized to guess a
user’s transportation mode, then it integrates cloud environment to enhance the limitation of mobile device,
such as storage, energy and computing power. This system includes three main components: Client
Interface, Server process and Cloud Storage. Some tasks are carried out on the Client. Therefore, it greatly
reduces the bottleneck situation on Server side in efficient way. Most of tasks are executed on the Server
and history data are stored on the Cloud Storage. Moreover, the paper mainly uses the distance based
clustering algorithm in grouping mobile devices on the same bus to get the accurate data.
Techniques for Smart Traffic Control: An In-depth ReviewEditor IJCATR
Inadequate space and funds for the construction of new roads and the steady increase in number of vehicles has prompted
scholars to investigate other solutions to traffic congestion. One area gaining interest is the use of smart traffic control systems (STCS)
to make traffic routing decisions. These systems use real time data and try to mimic human reasoning thus prove promising in vehicle
traffic control and management. This paper is a review on the motivations behind the emergence of STCS and the different types of
these systems in use today for road traffic management. They include – fuzzy expert systems (FES), artificial neural networks (ANN)
and wireless sensor networks (WSN). We give an in depth study on the design, benefits and limitations of each technique. The paper
cites and analyses a number of successfully tested and implemented STCS. From these reviews we are able to derive comparisons of
the STCS discussed in this paper. For instance, for a learning or adaptive system, ANN is the best approach; for a system that just
routes traffic based on real time data and does not need to derive any data patterns afterwards, then FES is the best approach; for a
cheaper alternative to the FES, then WSN is the least costly approach. All prove effective in traffic control and management with
respect to the context in which each of them is used.
Quantified Self movement allows to collect a lot of
personal data which can be used to nurture the model
of the users. Evenly, when aggregated, these personal
data become a picture of the people of a space in a City
Model. This model can be fed also by data coming from
crowdsensing. The resulting City Model can be used to
provide personalized services to citizen, and to increase
people awareness about their behaviour that can help
in promoting collective behavioural change. The paper
Data science courses in Germany 3.pptx12samaylearnco
In today's congested cities, urban transportation is a serious issue. The main causes of the traffic bottlenecks that hinder our daily journeys are overcrowding, emissions, and incompetence. However, data science is a promising new light on the horizon. However, amidst this chaos, a quiet revolution is underway – one fueled by data science. Explore how aspiring professionals can embark on this journey through data science courses in the country. Unlocking Productivity with Data-Driven Understanding
All throughout APAC the landscape is changing and presenting a need for smart mobility. Read more in detail to learn how businesses can seize opportunities with the right IT strategy and the right partnership.
A presentation by Neil Frost (Chief Executive Officer: iSAHA), at the Transport Forum SIG: "Cost Effective Public Transport Management Systems" on 12 May 2016 hosted by University of Johannesburg. The theme of the presentation was: "Big Data and Public Transport."
Tips For Implementing Smart City TechnologyAlan Oviatt
The concept of smart cities was premised on integrating information, communications and Internet of Things (IoT) technologies like sensors and cameras in a secure fashion to manage a city's assets. One goal was more effective and cost-efficient management of city infrastructures and property, but equally important was responsiveness to emerging infrastructure events to help cities and their occupants. By Alan Oviatt
Smart Cities - Smart(er) cities with geolocative technologiesSmart Cities Project
This guide is for managers at Local Authorities and city management, seeking new ways to deliver local services, and/or to give citizens a greater opportunity to interact with services, from reporting problems to finding the most appropriate information.
Public Transportation transformation for “The New Norm”Vinod Bijlani
Innovation goals in Public Transportation have transformed radically in the wake of Covid-19. In this write-up, I will be focusing primarily on artificial intelligence (AI) and internet-of-things (IoT) developments for rail transit systems, or trains, which form the transportation backbone of nearly every major city around the world.
Review Paper on Intelligent Traffic Control system using Computer Vision for ...JANAK TRIVEDI
In today scenario city will try to modify in the form of smart city with better facilities in terms of education, social-economic life,
better transportation availability, noise free – Eco-friendly environment availability, and ICT- Information and communication technology
enabler for development in the city. In this paper, we are reviewing different work already done or draft by some research in the field of traffic
control system – for better monitoring, tracking and managing using a computer vision system. Nowadays, most of the city installed with
C.C.T.V. – camera for monitoring the traffic related activity.
A SHORT SURVEY ON CONSTRUCTING AN IOTBASED INTELLIGENT ROAD SYSTEMijcsit
Road construction is a crucial component of modern infrastructure since it greatly facilitates travel between various areas.Sustainability, Progress, and Transformation refer to the upgrading of roads employing communication, lighting, and control transmission mechanisms that may promote sustainability, road progress, and a better driving experience for users.Smart roads that are connected to the Internet of Things (IoT) devices make it possible to drive more efficiently, sustainably, and safely.For this reason, the range of smart road technology like actuators, sensors, and solar power along with software infrastructures like Artificial Intelligence and big data are now made standard in all new roads. This article provides a framework for patients to employ speech-to-text chatbots to conduct treatment. Using chat-box technology, we have implemented cognitive therapy as a solution.
Road construction is a crucial component of modern infrastructure since it greatly facilitates travel
between various areas.Sustainability, Progress, and Transformation refer to the upgrading of roads
employing communication, lighting, and control transmission mechanisms that may promote sustainability,
road progress, and a better driving experience for users.Smart roads that are connected to the Internet of
Things (IoT) devices make it possible to drive more efficiently, sustainably, and safely.For this reason, the
range of smart road technology like actuators, sensors, and solar power along with software
infrastructures like Artificial Intelligence and big data are now made standard in all new roads. This
article provides a framework for patients to employ speech-to-text chatbots to conduct treatment. Using
chat-box technology, we have implemented cognitive therapy as a solution.
Road construction is a crucial component of modern infrastructure since it greatly facilitates travel
between various areas.Sustainability, Progress, and Transformation refer to the upgrading of roads
employing communication, lighting, and control transmission mechanisms that may promote sustainability,
road progress, and a better driving experience for users.Smart roads that are connected to the Internet of
Things (IoT) devices make it possible to drive more efficiently, sustainably, and safely.For this reason, the
range of smart road technology like actuators, sensors, and solar power along with software
infrastructures like Artificial Intelligence and big data are now made standard in all new roads. This
article provides a framework for patients to employ speech-to-text chatbots to conduct treatment. Using
chat-box technology, we have implemented cognitive therapy as a solution
Similar to Big data helps pedestrian planning take a big step forward (20)
www.nhtnetwork.org/cqc-efficiency-network/home
The CQC Efficiency Network is a collaborative venture between ITS researcher Dr Phill Wheat and leading
performance and benchmarking company measure2improve (m2wi). Dr Wheat has used funding from the EPSRC
Impact Acceleration Account (IAA) to refine the tools to support m2i in developing the fast growing network. The IAA is an institutional award funded by EPSRC to help speed up the contribution that engineering and physical science research make towards new innovation, successful businesses and
the economic returns that benefit UK plc.
Posters summarizing dissertation research projects - presented by MSc students at the Institute for Transport Studies (ITS), University of Leeds, April 2017. http://bit.ly/2re35Cs
www.its.leeds.ac.uk/courses/masters/dissertation
Cutting-edge transport research showcased to Secretary of State during the event to officially re- open the Institute building www.leeds.ac.uk/news/article/4011/cutting-edge_transport_research_showcased_to_secretary_of_state
DR STEPHEN HALL, PROFESSOR SIMON SHEPHERD, DR ZIA WADUD; UNIVERSITY OF LEEDS, IN COLLABORATION WITH FUTURE CITIES CATAPULT
Also see https://theconversation.com/five-reasons-why-you-might-be-driving-electric-sooner-than-you-think-71896
Presentation Fiona Crawford - winner of the Smeed prize for best student paper at the UTSG Conference 2017
www.its.leeds.ac.uk/people/f.crawford
www.utsg.net/web/index.php?page=annual-conference
Efforts to reduce the emissions from car travel have so far been hampered by a lack of specific information on car ownership and use. The Motoring and vehicle Ownership Trends in the UK (MOT) project seeks to address this by bringing together new sources of data to give a spatially and disaggregated diagnosis of car ownership and use in Great Britain and the associated energy demand and emissions.
Data from annual car M.O.T tests, made available by the Department for Transport, will be used as a platform upon which to develop and undertake a set of inter-linked modelling and analysis tasks using multiple sources of vehicle-specific and area-based data. Through this the project will develop the capability to understand spatial and temporal differences in car ownership and use, the determinants of those differences, and how levels may change over time and in response to various policy measures. The relationship between fuel use and emissions, and the demographic, economic, infrastructural and socio-cultural factors influencing these will also be tested.
Consequently, the MOT project has the potential to transform the way in which energy and emissions related to car use are quantified, understood and monitored to help refine future research and policy agendas and to inform transport and energy infrastructure planning.
www.its.leeds.ac.uk/research/featured-projects/mot
The University's Annual Review covering the 2015-16 academic year. This new publication gives an overview of some of the most important initiatives and activities that the University has undertaken recently and a sense of the scale of the ambition for the future.
www.its.leeds.ac.uk/people/c.calastri
Social networks, i.e. the circles of people we are socially connected to, have been recognised to play a role in shaping our travel and activity behaviour. This not only has to do with socialisation being the purpose of travel, but also with enabling mobility and other activities through the so-called social capital. Another theme in the literature connecting social environment and travel behaviour is social influence, i.e. the investigation of how travel behaviour can be affected by observation or comparison with other people. Research about the impact of social influence on travel choices is still at its infancy. In this talk, I will give an overview of how choice modelling can be used to investigate the relationships between social networks, travel and activities. I will touch upon work that I have done so far, in particular I will describe my applications of the Multiple Discrete-Continuous Extreme Value (MDCEV) model to frequency of social interactions as well as to allocation of time to different activities, taking the social dimension into account. In these studies, I make use of social network and travel data collected in places as diverse as Switzerland and Chile. I will also discuss ongoing work making use of longitudinal life-course data to model the impact of family of origin and the “mobility environment” people grew up in on travel decision of adults. Finally, I will outline future plans about modelling behavioural changes due to social influence using the smartphone app travel data that are being collected in Leeds within the “Choices and consumption: modelling long and short term decisions in a changing world” (“DECISIONS”) project.
Shigeki Oxawa is Associate Professor at the Department of Integrated Informatics, Daido University and part-time Lecturer in Transport Economics at Hosei University. He is a transport economist with a strong interest in transport policy. He is currently an academic visitor at Leeds University (April 2016-March 2017) working in the area of intermodal transport (with a focus on rail freight transport) and in turn track access charges.
Abstract: In the national railway revolution in Japan, the passenger division was divided into 6 companies by regions. They operate trains and own/manage the rail track (vertical integration system). On the other hand, vertical separation was introduced into freight companies, therefore, freight companies have to access rail track owned/managed by passenger companies. The Japanese regulator regards track access transactions between passenger companies and freight companies as private business.
In the vertical separation system, freight companies cannot get access to the slots required and efficient allocation of rail track cannot be achieved. The vertical separation is a very significant issue in railway policy and freight transport policy in Japan. In the presentation, causes and possible solutions to the issue will be shown.
Shigeki is Associate Professor at the Department of Integrated Informatics, Daido University and part-time Lecturer in Transport Economics at Hosei University. He is a transport economist with a strong interest in transport policy. He is currently an academic visitor at Leeds University (April 2016-March 2017) working in the area of intermodal transport (with a focus on rail freight transport) and in turn track access charges. He has 20 years of experience in research and teaching.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
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Big data helps pedestrian planning take a big step forward
1. Technical Paper Transportation Professional April 201526
Introduction
Recent advances in crowd modelling
systems mean decision makers are
placing a greater importance on such
techniques at complex locations
including stations, stadia, shopping
centres and schools.
Capturing data in these places is
difficult as people interact with the space
and each other in very complex ways.
As the range of crowd models and level
of detail required increases, gaps are
being exposed in the industry´s current
knowledge that need to be urgently
addressed. So much so that accurate data
collection is one of the biggest limitations
that crowd specialists face today.
Limitations with data collection
Data capture has been hampered to
date by the availability of practical and
affordable methods of data collation.
Surveys or field observations are often
impractical at complex locations where a
large amount of information about route
choice, flows, speed, spatial distribution
patterns and behaviours are required.
A lack of large scale real world data on
pedestrian movements and behaviours
is impeding how new models are
developed.
Feasibility of mobile phone data
Excitement is being generated by the
relatively recent ability to record data
using GPS units and mobile phone
about everyday activities, from financial
transactions to movement patterns.
This vast amount of data – ‘big data’ –
is being studied by public and private
organisations around the world in an
effort to understand facets of everyday
life in greater detail.
One of the benefits of big data for
transport planners is the ability to track
movements of vehicles and people
on a scale never before imagined. The
potential to use information generated
by mobile phones and other devices
across large populations and geographic
areas offers the prospect for pedestrian
modellers to understand city wide
movements at a level of detail and
accuracy never before achieved.
In the UK work has been carried out
by consultants and authorities using
telecoms data to ascertain what that
can tell us about people movement,
regardless of transport mode. Initial
findings suggest there may be some
valuable data that can be of use for
vehicle based studies.
However it appears that this type of
data capture is very difficult to use at the
required level of spatial resolution for
pedestrian movements.
Some telecom companies are
developing software that use anonymised
and aggregated mobile network data to
understand crowd patterns. However this
software is unlikely to be able to track
patterns such as route choice, group
behaviour and speed.
For the moment mobile phone data
generated from existing networks is
not able to directly inform detailed
analysis and understanding of pedestrian
movements. This would require the
development of technology – such as the
5G mobile network – to allow tracking
of mobile phone devices in much more
detail and with greater accuracy.
Alternative technologies
Other methods to obtain pedestrian
information include scanners that track
Bluetooth or WiFi traces from mobile
phones. Chicago has developed a project
using 50 sensors placed around the
city to collect real time data relating to
environment, infrastructure and activity.
They are attached to street lights and use
sensors to collect pedestrian flows within
a 30m range. However sample sizes are
still small, around 10-15%.
A recent exciting development
that claims to capture nearly 100% of
pedestrian movements and track phones
to within 1m uses locating sensors that
pick up signals from all phones regardless
of network, signal strength or connection.
This idea is currently being used in
Liverpool to collect real time data of
pedestrian and vehicle movement in
Using technology to track the movement of people through busy urban spaces can be a great help for
transport planners, say Pablo Alvarez and Andy Leeson.
Big data helps pedestrian
planning take a big step forward
By 2050 over 70% of the world’s population is predicted to live in cities, putting increased strain on
urban infrastructure and transport systems
AntoonKuper(Flickr)
2. Technical PaperTransportation Professional April 2015 27
order to enhance the urban transport
network.
Alternatives to mobile phone data
include using smartcards like Oyster in
London or the CEPAS card in Singapore to
track people when using public transport.
However outputs are of limited use for
tracking pedestrian movements other
than to establish general daily or weekly
commuting patterns.
This method can also be used to inform
transport users’ decisions about public
transport services, taking into account
strategic information about route choice,
journey times, in-vehicle time or number
of transfers.
Using CCTV for big data collection
Video cameras can also be used to record
and understand detailed pedestrian
movements. They can track size, shape,
clothing texture and colour or type of
movement rather than facial recognition
to preserve anonymity.
Collecting data in this manner is
perhaps not ‘big data’ as defined by
many. But if the technology was applied
to a network of existing cameras, such
as CCTV, there would be potential for
citywide movements to be captured and
understood more clearly than ever before.
Researchers from the University of
Washington are developing a project
using cameras mounted in cars to take a
video of the scene, then identify and track
people and overlay them into a virtual
3D map on a GPS screen. This could
help pick out people crossing in busy
intersections to improve safety.
If the different cars using this
technology uploaded the data to the
‘cloud’, it could be used to see real
time flow dynamics of city streets on a
platform like Google Earth.
Swiss experience
Video technology was also used by Swiss
Federal Railways to track hundreds of
thousands of pedestrians at Lausanne
train station over a prolonged period of
time to determine how pedestrian flow
was distributed along different platforms.
Using around 100 sensors located
throughout the station trajectories were
created for each pedestrian.
Anonymised data were used to
inform the planning process for future
transport infrastructure developments by
providing an understanding of behaviour,
interaction with other pedestrians, flow
dynamics and use of space.
Concerns over invasion of privacy
should be considered but the benefits of
this technology could enable accurate
origin destination matrices to be
developed and seasonal fluctuations
to be understood. Additional benefits
include the ability to determine
differences associated with changing
weather, as well as behavioural traits such
as group behaviour, dwell times, walking
speeds and route choices.
London has about 500,000 CCTV
cameras, so there is the potential for
this technology to be expanded at scale.
However one of the biggest limitations to
using the existing CCTV network for this
Pablo Alvarez
has a Masters in
Civil Engineering
and a Masters in
Transport Planning &
Engineering from the
Institute for Transport
Studies, Leeds. Based within AECOM’s
transport planning team he has worked
on several major pedestrian planning
projects including the Glasgow 2014
Commonwealth Games, FIFA World Cup
Qatar 2022 and Riyadh Metro.
Andy Leeson is a
principal consultant at
AECOM and a project
manager overseeing
crowd modelling
projects. Andy has
worked in transport
planning for over 10 years and has
specialised in pedestrian modelling for
the last seven. He has worked on the
Glasgow Commonwealth Games, Qatar
2022 World Cup and on over 100 rail
station assessments.
purpose is the placement of each camera.
The location of a camera may not be
effective for pedestrian flow analysis, or
the coverage of the CCTV network could
be poor with large gaps between cameras.
Classic cameras may also only be efficient
in daylight. Limitations can be overcome
by adding thermal sensors.
Conclusion
It is an exciting time for the crowd
modelling sector. The need to understand
and predict pedestrian volumes,
movements and behaviours for cities,
‘mega events’ and emergency planning
will continue to increase in prominence
in order to design more efficient and safer
cities for pedestrians.
Big data stands out as the next
necessary step for pedestrian planners.
It is vital that the industry recognises
the opportunities that are emerging
through technology and engage with
those involved to ensure that it can
effectively and efficiently shape future
developments.
Acknowledgement
This paper has been reviewed by
CIHT’s Sustainable Transport, Network
Management & Operations and Urban
Design panels.
Video cameras were used to track pedestrians
at Lausanne station to investigate what can be
done to manage daily flows, set to increase from
50,000 to 100,000 by 2030. Source: VisioSafe