Vol 20 No 4 (2020)
2020-10-01
Vol 20 No 4 (2020)
2020-10-01
Articles
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Nowadays, mobility modelling at individual level is receiving significant attention. Moreover, the technological advances in the field of travel behaviour analysis have supported and promoted the modelling paradigm shift to disaggregate methods such as agent/activity-based modelling Nonetheless, such approaches usually require significant amounts of detailed and fine-grained data which are not always easily accessible. The methodology presented in this paper aims to generate individual home-based trip-chains (i.e. tours) utilising aggregated sources of information, primarily, typical Origin-Destination matrices (ODs) and secondarily travel surveys. A suitable framework able to optimally identify ‘hidden’ tours in typical ODs is proposed and evaluated through its application on a set of multi-period OD matrices, covering an urban area of realistic size. This novel methodological framework synthesises the individual tours by combining and elevating advanced graph theory and integer programming concepts. The performance of the proposed methodology proves particularly encouraging since high estimation accuracy (greater than 85%) was achieved even for the most challenging examined test-case. The presented results provide positive evidence that information regarding travel behaviour on an individual level can be produced based on aggregated data sources such as OD matrices. This element is particularly valuable towards the analysis of mobility at the person-level, especially within the framework of agent-based modelling.
Nowadays, mobility modelling at individual level is receiving significant attention. Moreover, the technological advances in the field of travel behaviour analysis have supported and promoted the modelling paradigm shift to disaggregate methods such as agent/activity-based modelling Nonetheless, such approaches usually require significant amounts of detailed and fine-grained data which are not always easily accessible. The methodology presented in this paper aims to generate individual home-based trip-chains (i.e. tours) utilising aggregated sources of information, primarily, typical Origin-Destination matrices (ODs) and secondarily travel surveys. A suitable framework able to optimally identify ‘hidden’ tours in typical ODs is proposed and evaluated through its application on a set of multi-period OD matrices, covering an urban area of realistic size. This novel methodological framework synthesises the individual tours by combining and elevating advanced graph theory and...
Nowadays, mobility modelling at individual level is receiving significant attention. Moreover, the technological advances in the field of travel behaviour analysis have supported and promoted the modelling paradigm shift to disaggregate methods such as agent/activity-based modelling...
Haris Ballis, Loukas Dimitriou1-21 -
This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset provided by the German Automobile Club ADAC covering the Tyrolean road network in 2016. From this dataset, trajectories along the A12 motorway were extracted for congestion analysis. These data are characterized by high GPS time interval, low number of trajectories, and are not representative for total traffic due to overrepresentation of trucks. The influence of these quality parameters on congestion identification is explored by analyzing the parameter distribution among different congestion types. In addition, we validate the results by comparing them with congestion incidents obtained from the stationary detector data (SDD) and examining the impact of quality parameters on the validation results. We find that the given data set does not allow short-term congestion patterns to be identified due to quality flaws. Especially the low number of trajectories proved problematic, whereas the influence of other parameters was less distinct. Despite these flaws, for large-scale congestion incidents, floating car data provide outcomes similar to those derived from stationary detectors.
This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset provided by the German Automobile Club ADAC covering the Tyrolean road network in 2016. From this dataset, trajectories along the A12 motorway were extracted for congestion analysis. These data are characterized by high GPS time interval, low number of trajectories, and are not representative for total traffic due to overrepresentation of trucks. The influence of these quality parameters on congestion identification is explored by analyzing the parameter distribution among different congestion types. In addition, we validate the results by comparing them with congestion incidents obtained from the stationary detector data (SDD) and examining the impact of quality parameters on the validation...
This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset...
Wolfgang Blumthaler, Bartosz Bursa, Markus Mailer22-37 -
Due to the dilemma of bike-sharing concerning its benefits and drawbacks, and its unclear future, we focused on a mixed-methods approach to analyze this public discussion through posts or “tweets” from the social media channel Twitter. We collected around 12,000 tweets in English around the world related to bike-sharing for a period of about six months. We considered two approaches, including topic clustering and sentiment analysis in tweets including: a) bike-sharing related terms and b) “future” and bike-sharing related terms. Strongly positive tweets promote bike-sharing and its benefits such as being convenient, well-performing, and sustainable. Additionally, there is a tendency to write that public, electric, and dockless are better, together with scooters. In contrast, the complaints on bike-sharing focused on inequity, rentals and safety issues, critique on authorities and laws, and poor performance especially of dockless Asian bike-sharing start-ups with low-quality bikes. Around 50% of the tweets that included the terms “future” and “bike–sharing” stated that bike-sharing is going to be part of the future of mobility as an electric dockless version together with other shared modes. The hesitant statements towards bike-sharing being part of the future referred mainly to the systems with poor bikes’ quality. Politicians and stakeholders can use this information to enhance bike-sharing or consider the implementation of certain types of bike-sharing in their cities. To the best of the authors’ knowledge, this study would be one of the first that analysis the public discussion on social media about a transportation system and its future using a mixed-methods approach. Future studies should aim at identifying and comparing the public opinion of different emerging transportation technologies.
Due to the dilemma of bike-sharing concerning its benefits and drawbacks, and its unclear future, we focused on a mixed-methods approach to analyze this public discussion through posts or “tweets” from the social media channel Twitter. We collected around 12,000 tweets in English around the world related to bike-sharing for a period of about six months. We considered two approaches, including topic clustering and sentiment analysis in tweets including: a) bike-sharing related terms and b) “future” and bike-sharing related terms. Strongly positive tweets promote bike-sharing and its benefits such as being convenient, well-performing, and sustainable. Additionally, there is a tendency to write that public, electric, and dockless are better, together with scooters. In contrast, the complaints on bike-sharing focused on inequity, rentals and safety issues, critique on authorities and laws, and poor performance especially of dockless Asian bike-sharing start-ups with...
Due to the dilemma of bike-sharing concerning its benefits and drawbacks, and its unclear future, we focused on a mixed-methods approach to analyze this public discussion through posts or “tweets” from the social media channel Twitter. We collected around 12,000 tweets in English...
David Duran-Rodas, Dominic Villeneuve, Gebhard Wulfhorst38-58 -
The first/last mile is a long known deterrent to public transportation use, yet difficult to solve with fixed route transit. Many transit agencies are exploring partnerships with ridesourcing companies to offer subsidized feeder services. Ridership, however, has been surprisingly low. We explore two conceptual explanations. First, ridesourcing fares are found to exceed travel time savings for all distances below 1 mile and annual household incomes below USD 30,000 (i.e., the majority of US bus-using households). Subsidies are thus necessary, yet common schemes (flat fees, flat value or percentage discounts) are inequitable as they particularly benefit high-income households (thus miss their main target group). Second, the disutility of the additional transfer (‘transfer penalty’) and wait times exceed travel time savings assuming modest values for all distances below 0.45 miles. Subsidized ridesourcing for the first/last mile is thus not the panacea often portrayed, particularly not for short first/last miles. Where first/last miles are longer, investments in first/last mile services only might miss their purpose as the private car often remains the faster, more convenient and cheaper option. A much more holistic set of policy changes is hence required. Where transit agencies decide to proceed with first/last mile subsidies, they are advised to integrate them into existing fares (offering first/last mile rides for free) as this is the most equitable approach.
The first/last mile is a long known deterrent to public transportation use, yet difficult to solve with fixed route transit. Many transit agencies are exploring partnerships with ridesourcing companies to offer subsidized feeder services. Ridership, however, has been surprisingly low. We explore two conceptual explanations. First, ridesourcing fares are found to exceed travel time savings for all distances below 1 mile and annual household incomes below USD 30,000 (i.e., the majority of US bus-using households). Subsidies are thus necessary, yet common schemes (flat fees, flat value or percentage discounts) are inequitable as they particularly benefit high-income households (thus miss their main target group). Second, the disutility of the additional transfer (‘transfer penalty’) and wait times exceed travel time savings assuming modest values for all distances below 0.45 miles. Subsidized ridesourcing for the first/last mile is thus not the panacea often portrayed,...
The first/last mile is a long known deterrent to public transportation use, yet difficult to solve with fixed route transit. Many transit agencies are exploring partnerships with ridesourcing companies to offer subsidized feeder services. Ridership, however, has been surprisingly low. We...
Daniel J. Reck, Kay W. Axhausen59-77 -
The numbers of electric vehicles (EV) will increase as many countries perceive EVs as a solution to reduce the emissions of transportation and therefore incentivize their adoption. However, the deployment of public charging infrastructure is lagging behind that of EVs, which represents a potential barrier to their wide-scale adoption. The objective of this paper is to develop a comprehensive overview of potential EV charging solutions to be deployed in urban areas. Using a micro-Delphi approach, experts from transport, energy and urban planning were consulted and identified 15 realistic options for charging electric vehicles in urban environments by 2035. The solutions range from purely technical to more service oriented. Most of these solutions already exist today, although some remain at a very early stage of deployment. The five most likely options were on-street public charging points, charging at work, fast-charging stations, using building domestic plugs and semi-fast charging in public areas. When combined with the typical mobility and residential profiles, our results show that EV drivers will most likely rely on a mix of solutions, when they have no home chargers. As such, no breakthrough or major shift is expected in charging infrastructures, rather a scale-up of existing solutions. Our analysis concludes that urban charging options will be numerous and no single solution is expected to dominate as users with different EV user profiles will charge at different times and locations.
The numbers of electric vehicles (EV) will increase as many countries perceive EVs as a solution to reduce the emissions of transportation and therefore incentivize their adoption. However, the deployment of public charging infrastructure is lagging behind that of EVs, which represents a potential barrier to their wide-scale adoption. The objective of this paper is to develop a comprehensive overview of potential EV charging solutions to be deployed in urban areas. Using a micro-Delphi approach, experts from transport, energy and urban planning were consulted and identified 15 realistic options for charging electric vehicles in urban environments by 2035. The solutions range from purely technical to more service oriented. Most of these solutions already exist today, although some remain at a very early stage of deployment. The five most likely options were on-street public charging points, charging at work, fast-charging stations, using building domestic plugs and semi-fast...
The numbers of electric vehicles (EV) will increase as many countries perceive EVs as a solution to reduce the emissions of transportation and therefore incentivize their adoption. However, the deployment of public charging infrastructure is lagging behind that of EVs, which represents a...
Dominic Villeneuve, Yann Füllemann, Guillaume Drevon, Vincent Moreau, François Vuille, Vincent Kaufmann78-102 -
Serious games as research instruments – Do’s and don’ts from a cross-case-analysis in transportation
Serious games as research instruments are seen as a special type of participatory modelling, allowing a researcher to observe the behaviour and decisions taken by players. Yet, games have their own dynamics and come with certain challenges when used as a research instrument. This article reports on specific challenges in using games as research instruments in the domain of transportation. Therefore, three digital games from the transportation sub-systems freight transport, airport management and public transport are presented. The cases are analysed according to the challenges faced during the phases of requirements analysis, design, implementation, usage as research instrument, and evaluation. Based on this cross-case analysis of the research games, Do’s and Don’ts as well as practical recommendations are derived to support researchers and practitioners in applying serious games as research instruments in transportation. The new ReDIRE-framework to analyse serious games for research purposes is presented for this aim. Design guidelines resulting from our contribution can be helpful for game designers and researchers alike.
Serious games as research instruments are seen as a special type of participatory modelling, allowing a researcher to observe the behaviour and decisions taken by players. Yet, games have their own dynamics and come with certain challenges when used as a research instrument. This article reports on specific challenges in using games as research instruments in the domain of transportation. Therefore, three digital games from the transportation sub-systems freight transport, airport management and public transport are presented. The cases are analysed according to the challenges faced during the phases of requirements analysis, design, implementation, usage as research instrument, and evaluation. Based on this cross-case analysis of the research games, Do’s and Don’ts as well as practical recommendations are derived to support researchers and practitioners in applying serious games as research instruments in transportation. The new ReDIRE-framework to analyse serious games for...
Serious games as research instruments are seen as a special type of participatory modelling, allowing a researcher to observe the behaviour and decisions taken by players. Yet, games have their own dynamics and come with certain challenges when used as a research instrument. This article...
Maria Freese103-126 -
Cycling is an important pillar of the global endeavor to have a more sustainable transportation system. Many papers have studied how trip and person characteristics affect selecting the bike as a transport mode but unlike other researchers, we model the probability of cycling using a binary item response model where the choice is modelled as a trade-off between the individuals' tendency to cycle and the threshold related to each cycling situation.
We distinguish between frequent and occasional cyclists. The results show that occasional cyclists are more affected by adverse weather situations, darkness, and uphill slopes. Contrary to the previous studies, a separate bike path turned out a stronger motivator for the group of frequent cyclists.
The model fit can substantially be improved by accounting for attribute non-attendance. The results show that weather and wind speed have the highest probability to be taken into account, and the bike path had the lowest probability of being considered by the respondents.
Employing the attribute non-attendance model made it possible to make accurate and trustworthy conclusions about the attributes by focusing on the people who take into account the attributes. More specifically, it was found that the presence of a separate bike path and a 100% asphalt route can increase the average probability of taking the bike by up to 55 and 40 percentage points, respectively.
Cycling is an important pillar of the global endeavor to have a more sustainable transportation system. Many papers have studied how trip and person characteristics affect selecting the bike as a transport mode but unlike other researchers, we model the probability of cycling using a binary item response model where the choice is modelled as a trade-off between the individuals' tendency to cycle and the threshold related to each cycling situation.
We distinguish between frequent and occasional cyclists. The results show that occasional cyclists are more affected by adverse weather situations, darkness, and uphill slopes. Contrary to the previous studies, a separate bike path turned out a stronger motivator for the group of frequent cyclists.
The model fit can substantially be improved by accounting for attribute non-attendance. The results show that weather and wind speed have the highest probability to be taken into account, and the bike path had the lowest...
Cycling is an important pillar of the global endeavor to have a more sustainable transportation system. Many papers have studied how trip and person characteristics affect selecting the bike as a transport mode but unlike other researchers, we model the probability of cycling using a binary...
Abolghassem Jandari, Michel Meulders, Saskia Desplenter, Martina Vandebroek127-151 -
This article presents an agent-based travel demand model, where agents react to transport supply across all mobility choices. Long-term choices include mobility tool ownership and work locations. Daily travel patterns are simulated at the individual level by sequentially combining activity frequency, activity durations and destinations as well as a rule-based time-of-day scheduling. A key to success in this novel approach is balancing individual preferences of travelers with system constraints. The model incorporates two types of constraints: 1) capacity constraints of the transport infrastructure. 2) natural time and space constraints during the execution of individual 24-hour day plans. Model results are validated against empirical observations of travel demand in Switzerland. The article concludes with a perspective for further research and development in the field of applied agent-based modeling.
This article presents an agent-based travel demand model, where agents react to transport supply across all mobility choices. Long-term choices include mobility tool ownership and work locations. Daily travel patterns are simulated at the individual level by sequentially combining activity frequency, activity durations and destinations as well as a rule-based time-of-day scheduling. A key to success in this novel approach is balancing individual preferences of travelers with system constraints. The model incorporates two types of constraints: 1) capacity constraints of the transport infrastructure. 2) natural time and space constraints during the execution of individual 24-hour day plans. Model results are validated against empirical observations of travel demand in Switzerland. The article concludes with a perspective for further research and development in the field of applied agent-based modeling.
This article presents an agent-based travel demand model, where agents react to transport supply across all mobility choices. Long-term choices include mobility tool ownership and work locations. Daily travel patterns are simulated at the individual level by sequentially combining activity...
Wolfgang Scherr, Patrick Manser, Chetan Joshi, Nathalie Frischknecht, Denis Métrailler152-172