Spatial analysis of shared e-scooter trips

Shared e-scooters have become a common mode of transportation in many cities around the world. E-sooters provide convenient and quick rides for short distances and can act as a connection for first/last mile trips. To date, limited studies have explored the spatial variation of e-scooter trips and there is knowledge to be gained by investigating variables associated with e-scooter trip generation. This study implemented a spatial analysis approach, Geographical Weighted Regression (GWR), to explore how factors relating to demographics, density, diversity, design, urbanism scores, distance to transit and other transportation-related variables influence e-scooter trips in Louisville, KY. More than 400,000 e-scooter trips across 159 Traffic Analysis Zones (TAZs) were included in the study. Results show TAZ-level factors including land use, age distribution, gender distribution, Walk Score and Park Score impacted the density of e-scooters trips in the TAZ. The GWR model showed improvements over a global Ordinary Least Squares (OLS) model. Local goodness of fit ranged from 0.732–0.895 across the study area. This study can help governments and e-scooter sharing companies develop policies that maximize e-scooter use, equity, and accessibility while improving the mobility of cities.     

Environmental correlates of dock-less shared bicycle trip origins and destinations

It remains unclear whether environmental conditions, including bicycle lane provision, are factors in dock-less bicycle uptake at the decision point. In conditions of generous bicycle supply and the ability to park a bicycle almost anywhere, it is important to know what local conditions might be influential in its use. The present study considered the role of 13 environmental factors in uptake and deposit rates by street segment, in a sample from a database of more than 3 m records over a ten-day period in May 2017, in Beijing, China. Street segments, defined by intersections, were coded for environmental factors using satellite and street view imagery. Uptake and especially deposit rates vary greatly by street segment and by local area. Linear regression reveals that 6 factors are highly significant in higher uptake and deposit – the presence of a dedicated bicycle pathway, street lighting, sidewalks, bicycle parking lots, POI density, and street segment length – while 3 were highly significant in lower uptake rates – interruptions in bicycle lane continuity, distance to the metro station, and elaborate environmental design. Altogether, environmental factors account for 42.4% of the variance in local bicycle trip origins and 38.7% of variance in destinations on street segments. This research contributes new understanding of the important role of local environmental factors in higher bicycle mode share in the context of a dock-less rental bicycle system.     

Spatial and temporal analysis of bike-sharing use in Cologne taking into account a public transit disruption

This research analyzes the relationship between bike-sharing and public transit using bike-sharing data collected in Cologne, Germany. The selected system is one of very few in Germany that is organized as a free-floating system, which allows the generation of more detailed data. A construction site in the light rail network causing multiple disruptions in the public transit network offered the possibility to detect changes in bike-sharing usage that occur in the corresponding period. Applying negative binomial regression, spatial and temporal usage patterns are analyzed to identify connections to the public transit network and other factors influencing the usage of bike sharing. The analysis suggests the existence of a spatial relationship between bike-sharing and public transit. Therefore, an intermodal use of both means of transport can be assumed. The short-term changes in the public transit network caused by the construction site only have minor impacts on the usage patterns. Other factors that affect the usage structures could be identified. Proximity to universities as well as the number of certain points of interest nearby, such as food outlets and shops, promote bike-sharing use. Higher temperatures are also positively correlated, while rain reduces usage. The findings of the study can be beneficial to integrate bike-sharing into urban transport systems, especially regarding public transit.     

Design speeds and acceleration characteristics of bicycle traffic for use in planning,design and appraisal

This paper reports the results of a study of a cohort of cyclists to determine their speed and acceleration characteristics relative to gradient and other influencing factors in order to supply data for planners, designers and appraisers of cycle infrastructure schemes. A cohort of everyday cyclists was supplied with a global positioning system device and a heart rate monitor and asked to collect data from their journeys in Leeds, UK.The analysis determines the cyclists’ speeds and accelerations at every point on their journey and elevation data, corroborated by mapping information, was used to determine the gradient. Two linear regression models of speed and acceleration were estimated and show that the influence of a downhill gradient on speed is less pronounced than the effect of an uphill gradient. The results indicate an eighty-fifth percentile speed on the flat of 22 kph, and for a downhill gradient of 3%, 25 kph. The power required to cycle has been estimated and shows that cyclists deliver around 150 W on the flat, but that this rises to around 250 W climbing hills. Mean acceleration on the flat is 0.231 m/s² and the average power output over the acceleration phase, which is of mean duration 26 s, is approximately 120 W. Air resistance accounts for approximately 70% of the resistive force when cycling at design speed.It is recommended that designers adopt 25 kph as a design speed for gradients less than 3%, but that consideration should be given to design speeds of up to 35 kph for steeper gradients. Free-flow speeds in this range should be used when modelling mode and route choices and in benefit appraisal.     

Data-mining,GIS and multicriteria analysis in a comprehensive method for bicycle network planning and design

In many Brazilian cities, the most common procedure for planning cycling networks is using aggregated population data in census tracts, which may not take into account the true origin and destination of trips. It may also not identify potential users of a particular mode of transport. This is particularly important considering that implementing cycling infrastructures should be based on the assumption that they are able to meet the users' needs. Therefore, the aim of this study is to develop and adopt an objective method to design and compare cycling networks based on data-mining of disaggregated origin-destination data, GIS resources, and multicriteria analysis techniques. The method follows three steps: 1) identifying potential users based on real user profiles, 2) designing proposed cycling networks and 3) a comparison between the networks proposed in this study and those developed by the municipality selected as a case study, considering real and potential users, as well as cost and benefit criteria. As a positive outcome, using disaggregated data allows for a reasonable estimate of the number of people served by the networks, a detailed analysis of their proximity to the infrastructure, as well as identifying potential users. Comparing cycling networks considering cost and benefit criteria shows that the chosen criteria were effective. It was also determined that the cycling network of the studied city poorly serves bicycle transport users, if compared to the proposed networks. These findings indicate that appropriate methods for planning cycling networks are still needed.     

Associations of built environments with spatiotemporal patterns of public bicycle use

This study examines the association of built environment attributes with spatiotemporal patterns of public bicycle use. The study observations are based on the rental records of YouBike, which is a public bicycle system (PBS) in Taipei Metropolitan Area, Taiwan, from July to December 2015. A hierarchical clustering method is applied to identify the spatiotemporal patterns of YouBike use, and multinomial logit regression is used to clarify the associations. Empirical results indicate that the spatiotemporal patterns of PBS utilization differ in weekdays and holidays and are associated with locations, land use and facilities in a city. The empirical evidence fills the knowledge gap on the factors associated with the spatiotemporal patterns of PBS use and provides system operators with a valuable basis for the integrated planning and management of PBSs and built environments.     

Spatial and temporal transferability of relationships between travel demand,trip cost and travel time

The paper draws together results from several major revealed preference (RP) and stated preference (SP) data sets, collected for large-scale disaggregate models and VTTS research, respectively, to comment on trends which appear in time and cost trading as between different time periods and different countries.     

Integrated land use and transportation interaction: a temporal GIS exploratory data analysis approach

Land use and transportation interaction is a complex, dynamic process. Many models have been used to study this interaction process during the past several decades. Empirical studies suggest that land use and transportation interaction patterns can be highly variable between geographic areas and at different spatial and temporal scales. This paper presents a temporal geographic information systems (GIS) design that offers exploratory data analysis capabilities to interactively examine land use and transportation interaction at user-specified spatial and temporal scales. A spatiotemporal interaction framework, implemented with temporal GIS databases, provides a foundation for the development of spatiotemporal analysis functions to systematically explore land use and transportation interaction.     

Mapping bicycle use and the risk of accidents for commuters who cycle to work in Belgium

This paper explores the spatial patterns of bicycle use for commuting and the risk cyclists run being injured in a road accident when commuting to work in Belgium. Exploratory data analyses suggest that the observed differences in the use of the bicycle to get to work are strongly linked to the urban hierarchy: commuters are more inclined to cycle in cities and specifically in regional towns (with 25 000 to 120 000 inhabitants). In large cities (more than 200 000 inhabitants), less commuting by bicycle takes place. The relationship between bicycle use and the risk of being seriously injured or killed in a road accident is also studied. A cluster analysis confirms that high proportions of commuter cyclists are correlated with low risks of becoming a casualty. It also shows that there are strong spatial differences (regional and between different types of towns) in bicycle use and the risk of an accident. This suggests that cycling policies should be spatially differentiated.     

Public bicycle as a feeder mode to rail transit in China: The role of gender,age, income,trip purpose,and bicycle theft experience

A marriage between public bicycle and rail transit presents new opportunities for sustainable transportation in Chinese cities. To examine determinants of public bicycle usage for rail transit access, an intercept survey of feeder mode choice among rail transit users was conducted near rail stations in Nanjing, China. Mode choice models were estimated with five feeder mode alternatives, including car, bus, walk, private bike, and public bike. By differentiating between public and private bicycle modes in the mode choice models, the study reveals the effects of personal demographics, trip characteristics, and station environments on public bicycle usage for rail transit access. Results show that female, older, and low-income rail commuters are less likely to use public bicycle to access rail transit. Rail commuters with bicycle theft experience and making school- or work-related trips are more likely to use public bicycle to access rail transit. Land use variables are largely insignificant in this study except that density shows a positive relationship with walking to rail transit. The results on demographic differences raise equity concerns when it comes to investing in public bicycle systems. Policy implications are discussed for Chinese cities to equitably boost public bicycle integration with rail transit.     

Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system: A study using big bike GPS data

As a sustainable transport mode, bicycle sharing is increasingly popular and the number of bike-sharing services has grown significantly worldwide in recent years. The locational configuration of bike-sharing stations is a basic issue and an accurate assessment of demand for service is a fundamental element in location modeling. However, demand in conventional location-based models is often treated as temporally invariant or originated from spatially fixed population centers. The neglect of the temporal and spatial dynamics in current demand representations may lead to considerable discrepancies between actual and modeled demand, which may in turn lead to solutions that are far from optimal. Bike demand distribution varies in space and time in a highly complex manner due to the complexity of urban travel. To generate better results, this study proposed a space-time demand cube framework to represent and capture the fine-grained spatiotemporal variations in bike demand using a large shared bicycle GPS dataset in the “China Optics Valley” in Wuhan, China. Then, a more spatially and temporally accurate coverage model that maximizes the space-time demand coverage and minimizes the distance between riders and bike stations is built for facilitating bike stations location optimization. The results show that the space-time demand cube framework can finely represent the spatiotemporal dynamics of user demand. Compared with conventional models, the proposed model can better cover the dynamic needs of users and yields ‘better’ configuration in meeting real-world bike riding needs.     

Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago

As ride-hailing becomes more common in cities, public agencies increasingly seek transportation network company (TNC) service data to understand (and potentially regulate) demand and service response. Despite the increase in ride-hailing or TNC demand and subsequent research into its determinants, there remains little research on shared TNC trips and the spatial distribution of trip demand across demographic and land use variables. Using Chicago as a case study, shared TNC trip data from 2019 was used to estimate the count and ratio of shared ride services, based on built environment, demographic, location, time of day, and trip details. Findings reveal that trip length, day of week designation, density of pedestrian and multi-modal infrastructure, and underlying socioeconomic characteristics of the origin zones influence the proportion and count of shared ride-hail trips. Of concern is that those using transit or active modes may be taking more ride-hailing trips, but these Chicago-region results indicate that the provision of pedestrian infrastructure and remoteness to transit stops result in fewer shared trips.     

Economic,social and cultural transformation and the role of the bicycle in Brazil

This paper reviews the current socio-cultural and political state of cycling in Brazil and the policies and activities over recent years that have aimed to reverse its marginalisation. In particular it focuses on the city of Pelotas in the southern state of Rio Grande do Sul and the significant societal and material transformations that are causing conflict and dissonance in relation to the future role of cycling on city streets. Using a combination of empirical evidence from existing literature; a focus group with members of the cycling stakeholder forum; interviews with planning officials whilst observing cycle infrastructure; interviews with participants whilst taking part in a ‘protest’ bicycle ride (bicicletada); and on street intercept interviews with cycle commuters, this paper highlights the tensions, conflicts, aspirations and imaginaries of a city grappling with significant growth and urban transformation.     

Spatial,temporal and institutional characteristics of entry strategies in inland container terminals: A comparison between Yangtze River and Rhine River

Recent decades have brought a growing commitment of investors in the (co-)funding and management of inland terminals, particularly container terminals. However, the actors involved, the forms of third-party entry and the emerging partnerships in inland terminals have only been investigated on a fragmented basis in inland port research. To complement existing inland port research on governance, management and spatial development, this paper analyses entry strategies of actors in inland container terminals on the Rhine and Yangtze in terms of their spatial, temporal and institutional characteristics. The unit of analysis in this paper is the inland container terminal, not necessarily the entire inland port (which might have more than one terminal). The entry strategies and the drivers behind these strategies are examined using a conceptual framework focused on five questions, i.e. who, where, when, why and which way. The empirical application is based on a large dataset of all container terminals on the Rhine and Yangtze. Our findings suggest clear differences between the two rivers in terms of the type of operators, the sequence of inland port development and also the major actors shaping the inland terminal landscape. Despite these differences, there is also some level of similarity, including a low presence of international players, the absence of deepsea (landlord) port authorities and observed waves of single acquisition, multiple-site acquisition, and capital entry in the terminals. Government policies, institutional frameworks and the nature of shipping network development are determinants of inland port investment and the entry strategies adopted by relevant actors. The findings contribute to a better understanding of the drivers and contextual environment guiding entry strategies in inland ports and can help policy makers and port operators in inland rivers to assess and benchmark their strategy. The paper adds to existing literature by considering spatiotemporal aspects of terminal ownership and the strategic considerations of and institutional drivers and impediments to the inland terminal strategies of the corresponding actors.     

Macro-level analysis of bicycle safety: Focusing on the characteristics of both crash location and residence

Over the last decade, bicycle ridership has been encouraged as a sustainable mode of transportation as it is economic and has less impact on the environment. Still, higher crash risk for bicyclists remains a deterrent for people to choose bicycling as their major mode of travel. As a first step in investigating bicycle safety, it is essential to identify not only the characteristics of the areas with the excessive number of bicycle crashes; but also those of the areas where crash-prone bicyclists reside. Therefore, this study aims to identify contributing factors for two subjects: (1) the number of bicycle crashes in the crash location's ZIP code and (2) the number of crash-involved bicyclists in their residence's ZIP. In order to achieve these objectives, a multivariate Bayesian Poisson lognormal CAR (conditional autoregressive) model was developed to identify the contributing factors for each subject. Regarding the model performance, the multivariate model outperformed its univariate counterpart in terms of DIC (deviance information criterion). Subsequently, hot zones for the two target zones were identified based on the modeling results. It is expected that practitioners are able to understand the contributing factors for bicycle crashes and identify hotspots from the results suggested in this study. In addition, they could implement safety countermeasures for the identified problematic locations to effectively reduce bicycle crashes.     

Motives,perceptions and experiences of electric bicycle owners and implications for health,wellbeing and mobility

The sale of electrically assisted bicycles (‘e-bikes’) is growing at a rapid rate across Europe. Whereas market data is available describing sales trends, there is limited understanding of the experience of early adopters of e-bike technology. This paper investigates the motives for e-bike purchase, rider experience and perceived impact on mobility, health and wellbeing through in-depth interviews with e-bike owners in the Netherlands and the UK.Findings revealed that the motive for purchasing e-bikes was often to allow maintenance of cycling against a backdrop of changing individual or household circumstances. E-bikes also provided new opportunities for people who would not otherwise consider conventional cycling. Perceptions of travel behaviour change revealed that e-biking was replacing conventional cycling but was also replacing journeys that would have been made by car. There was also a perception that e-biking has increased, or at least allowed participants to maintain, some form of physical activity and had benefitted personal wellbeing. Technological, social and environmental barriers to e-biking were identified. These included weight of bicycle, battery life, purchase price, social stigma and limitations of cycle infrastructure provision.Additional research is necessary to quantify actual levels of mode substitution and new journey generation among new e-bike owners and the impact of e-biking on promoting physical health and mental wellbeing.     

Investigating the effects of a shared bike for tourism use on the tourist experience and its consequences

ABSTRACT

As public bike-sharing systems have been widely set up in cities around the world, a shared bike for tourism use can enhance tourists’ experience at destinations and lead to tourists’ post-visit evaluations. Thus, this research explores the attributional effects of the value of using shared bikes (namely, instrumental value and affective value) on tourists’ emotional experience (namely, hedonics and perceived uniqueness) as well as on satisfaction and destination loyalty. We obtain a sample of 302 tourists using shared bikes as transport modes during their visits to examine the proposed relationship model. Results show that both instrumental and affective values of shared bike use positively relate to hedonics and perceived uniqueness experiences. While both hedonics and perceived uniqueness have positive effects on satisfaction, only perceived uniqueness shows a positive effect on destination loyalty. The findings of multi-group analyses indicate that the direct effects of the tourism experience on destination loyalty are significantly positive for the low-motivation group but not for the high-motivation group. Empirical implications and recommendations for future research are also discussed herein.     

A spatial analysis of demand patterns on a bicycle sharing scheme: Evidence from London

This paper investigates the spatial demand for bikesharing through the application of a series of trip generation models for the London Bicycle Sharing Scheme (LBSS). The production of trips from and the arrival of trips at scheme stations are evaluated in reference to how they connect with features of the built environment, demographics of the resident and workplace populations, and attributes of the scheme's structure. A spatial econometrics approach is taken to specify the models, with four different time windows considered throughout the day for all trips taken during 2016. The built environment features show a consistent pattern of results in the model, indicating that proximity to cycling infrastructure, rail stations, parks, university facilities, as well as the density of shops and conventional roads in the vicinity of stations is linked with trip generation rates. The presence of males and Caucasians are associated with higher station demand, aligning with other work on the introduction of new mobility solutions elsewhere, though we do find that greater distances to work tend to depress use. Trip generation is also reduced at the minority of stations located south of the River Thames, indicating that the presence of natural barriers can affect the operation of schemes. The results carry implications for scheme integration in other cities.