Jittering: A computationally efficient method for generating realistic route networks from origin-destination data

Origin-destination (OD) data is a vital source of information on travel patterns but its utility is limited by reliance on zone centroids. This paper presents a reproducible and open two-stage ‘jittering’ approach to tackling this problem, which (1) uses random points to represent unique start and end points (sampling), and (2) splits OD pairs representing many trips into many ‘sub-OD’ pairs. We find that route networks generated from jittered OD data are more diffuse and potentially realistic based on an example from Edinburgh. Further work is needed to validate the approach and to find optimal parameters for sampling and disaggregation.

Pola Pergerakan Orang di Masa Pandemi dengan Pendekatan Eksploratif di Wilayah Kepulauan Bangka Belitung

COVID-19 has spread around the world and has given a huge impact on people's lives. One of the changes in the COVID-19 condition is the travel pattern of people. Travel patterns can be explained in terms of the flow of vehicles, passengers, and people's mobility from the origin and destination zones within a certain area and period. On the other hand, it is known that travel patterns are an essential factor in solving transportation problems. The change of travel pattern data is needed for transportation planners and policymakers in providing safe transportation during the pandemic. In addition, data on travel patterns also play an important role in determining travel restrictions in an area to reduce the spread of COVID-19. This study tries to analyze travel patterns during the COVID-19 pandemic through an exploratory approach by taking a case study in the Bangka Belitung Province. The results of this study show that the mobility was dominated by intra-island trips during the pandemic, both within Bangka Island and Belitung Island. Furthermore, during the COVID-19 pandemic, the majority of people made changes to their routine's mobility. More than 50% of people did not return to their original travel patterns even though the pandemic conditions had entered the New Normal period. The most influential factor which makes people change their mobility is to take precautions from COVID-19.

Identifikasi Pengunjung Pada Pantai Panrita Lopi, Kecamatan Muara Badak

Panrita Lopi Beach is one of the natural tourist destinations that needs to be surveyed by visitors in order to identify and determine strategies for developing tourist attractions and also marketing in Kutai Kartanegara Regency. This study aims to analyze the characteristics of tourists and travel patterns of tourists who visit and to determine the perception of the level of tourist satisfaction with infrastructure products, public facilities and tourism facilities in this tourist destination. The main variables used in segmenting comprise: Geographic Segmentation, Demographic Segmentation, Psychographic Segmentation, and Behavior-based Segmentation. This research is a type of survey research with a qualitative descriptive approach. I carried out data collection from primary data sources and secondary data sources. The sample used in this study is a non-probability sampling technique by accidental sampling, namely a sampling technique based on chance, anyone who coincidentally meets a researcher can be used as a sample, if it is deemed that the person who was met is suitable as a data source. Data that has been collected from research results related to typology (characteristics, travel patterns) and visitor perceptions can be analyzed descriptively qualitatively. The analyzed data comes from surveys through questionnaires that have been given to visitors, including data on visitor profiles, visitor travel patterns, and visitor perceptions about this Panrita Lopi beach.

Analysis of Changes in Intercity Highway Traffic Travel Patterns under the Impact of COVID-19

The unprecedented COVID-19 pandemic impacts negatively on the security and development of human society. Comparison and analysis of intercity highway travel patterns before and during the COVID-19 pandemic can bring vital insights for the prevention and control of the pandemic. Empirical studies are conducted using cellular network-based datasets associated with two groups of city pairs in China heavily affected by COVID-19. Spatial matching, full-sample extrapolation, and trajectory feature analysis are adopted to attain travel volumes of intercity highways during four different periods. The reliability of origin-destination (OD) matrices calculated based on the cellular network-based dataset is demonstrated by comparing with the fluctuation trend of traffic count data. The empirical studies show that the OD flows associated with passenger cars on intercity highways in China decreased significantly during COVID-19. With the effective implementation of the pandemic prevention control policy and the orderly promotion of the recovery to work and production, the volumes of intercity highway OD flows returned to the pre-pandemic level in mid-April 2020. Besides, the peak of passenger car trips decreases and the time span for truck trips gets longer owing to implemented control measures in dealing with COVID-19. The results can be applied to the calculation of OD flows between most adjacent cities and analyze the intercity highway traffic travel patterns changes, which provide insightful implications for making intercity travel safety prevention and control policies under epidemic conditions.

Identification of Metro-Bikeshare Transfer Trip Chains by Matching Docked Bikeshare and Metro Smartcards

Metro-bikeshare integration, an important way of improving the efficiency of public transportation, has grown rapidly during the last decades in many countries. However, most previous analysis of metro-bikeshare transfer trips were based on limited sample size and the number of recognized metro-bikeshare trips were not sufficient. The primary objective of this study is to derive a method to recognize metro-bikeshare transfer trips. The two data sources are provided by Nanjing Metro Company and Nanjing Public Bicycle Company over the same period from 9–29 March 2016. The identifying method includes three steps: (1) Matching Card Pairs (2) Filtering Card Pairs and (3) Identifying Card Pairs. The case study indicates that the Support Vector Classification (SVC) performs best with a high prediction accuracy of 95.9% using seamless smartcards. The identifying method is then used to recognize the transfer trips from other types of cards, resulting in 17,022 valid metro-bikeshare transfer trips made by 2948 travelers. Finally, travel patterns extracted from the two groups of identified transfer trips are analyzed comparatively. The method proposed presents new opportunities for analyzing metro-bikeshare transfer trip characteristics.

Exploring the Role of Norms and Habit in Explaining Pro-Environmental Behavior Intentions in Situations of Use Robots and AI Agents as Providers in Tourism Sector

In a pandemic situation, with climate change around the world, studies analyzing changes in travel patterns are welcome. This study combines three theories to propose a model on pro-environmental behavior intentions, namely, the theory of planned behavior, value–belief–norm theory and habit theory. This study aims to examine the role of social norms, personal norms and habit strength to explain pro-environmental behavior intentions. The authors collected 316 usable questionnaires from tourists in the well-known touristic Belem location in Lisbon. Personal norms were revealed to have the strongest association with pro-environmental behavior intentions, followed by habit strength. The study also identified different broad challenges to encouraging sustainable behaviors and use these to develop novel theoretical propositions and directions for future research. Finally, the authors outlined how practitioners aiming to encourage sustainable consumer behaviors can use this framework to achieve better results.

Exploring Women’s Experience of Gender-Based Violence and Other Threats to Safety on Public Transport in Bangladesh

Equal access to safe transport is increasingly conceptualised as a fundamental right for women, with demonstrated impact on health outcomes, social and economic mobility, and societal participation. This study analysed qualitative and quantitative data to examine travel patterns and experiences among 200 women (aged between 18-64 years) using paid transport for work or educational purposes in Bangladesh. Results showed that the women faced multiple threats to their safety, including gender-based violence, harassment and crime, and traffic and non-traffic injury and that the use of paid transport was associated with high levels of anxiety and fear. Despite these circumstances, the women were captive travellers, forced to make transport choices based on price, availability, and ease of travel rather than safety. Unable to choose safe transports, the women attempted to mitigate risks by changing their travel pattern and behaviour, and by restricted their travel frequency. These findings are discussed within the context of women’s rights and mobility justice.

Travel Patterns of Women Giving Birth in the Southern District Health Board

<p>The objective of this mixed method piece of descriptive research is to analyse travel patterns of New Zealand women relating to their selected place of birth, focusing on residents of the Southern District Health Board. It also explores the motivations of a sample of women in this area regarding their birth place choices. Data extracted from Southern District Health Board 2013 electronic records, were analysed using geographic information system software. Spatial modelling was also conducted using this dataset. The second part of the study involved a questionnaire issued to women in Southern District Health Board maternity facilities during a three month period in 2014. In the analysis of 2013 data that women appeared to be by-passing smaller primary maternity units in preference for larger complex care facilities. Spatial modelling examined some possible geographic reasons for this and improved service placement was also modelled based on 2013 demand. Survey results were congruent with other similar research, in that the main reasons for women choosing birth place were a combination of seeking out a safe place whilst remaining as close to home as possible. These priorities caused a tension of distance for rural women. There was no significant statistical variance in the responses between demographic groups. Women are prioritising safety when they choose their birth place. In a large sparsely-populated District Health Board like Southern, this results in some women making long journeys to their chosen birth place as they select complex care facilities over closer primary maternity units or home.</p>