Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) to Transportation Equity framework. We found that dockless e-bikesharing trips were longer in distance and duration than docked trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with 0.8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The destination choice model results suggest that JUMP users traveled to lower-density destinations, and GoBike users were largely traveling to dense employment areas. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing systems in areas of the city where high-job density and bike facility availability converge with older resident populations.     

Understanding the diffusion of public bikesharing systems: evidence from Europe and North America

Since the mid-2000s, public bikesharing (also known as “bike hire”) has developed and spread into a new form of mobility in cities across the globe. This paper presents an analysis of the recent increase in the number of public bikesharing systems. Bikesharing is the shared use of a bicycle fleet, which is accessible to the public and serves as a form of public transportation. The initial system designs were pioneered in Europe and, after a series of technological innovations, appear to have matured into a system experiencing widespread adoption. There are also signs that the policy of public bikesharing systems is transferable and is being adopted in other contexts outside Europe. In public policy, the technologies that are transferred can be policies, technologies, ideals or systems. This paper seeks to describe the nature of these systems, how they have spread in time and space, how they have matured in different contexts, and why they have been adopted.Researchers provide an analysis from Europe and North America. The analysis draws on published data sources, a survey of 19 systems, and interviews with 12 decision-makers in Europe and 14 decision-makers in North America. The data are examined through the lens of diffusion theory, which allows for comparison of the adoption process in different contexts. A mixture of quantitative and qualitative analyses is used to explore the reasons for adoption decisions in different cities. The paper concludes that Europe is still in a major adoption process with new systems emerging and growth in some existing systems, although some geographic areas have adopted alternative solutions. Private sector operators have also been important entrepreneurs in a European context, which has accelerated the uptake of these systems. In North America, the adoption process is at an earlier stage and is gaining momentum, but signs also suggest the growing importance of entrepreneurs in North America with respect to technology and business models. There is evidence to suggest that the policy adoption processes have been inspired by successful systems in Paris, Lyon, Montreal, and Washington, DC, for instance, and that diffusion theory could be useful in understanding public bikesharing policy adoption in a global context.     

Is traffic congestion overrated? Examining the highly variable effects of congestion on travel and accessibility

Congestion is universally unpopular, but is it always a problem? Are some places more “congestion-adapted” than others? Using data for Los Angeles, we examine whether the geographies of congestion and accessibility are distinct by mapping and describing them across neighborhoods. We then estimate a series of regression models of trip-making to test the net effects of traffic delays on behavior. We find that there are places where people make many trips and engage in many activities despite lots of congestion, which tend to be more central, built-up areas that host many short trips; in other places, high congestion and low activity coincide. Why the variance? While congestion can constrain mobility and reduce accessibility, traffic is also associated with agglomerations of activity and is thus a byproduct of proximity-based accessibility. Whether agglomeration and congestion have net positive or negative impacts on activity participation thus varies substantially over space. Controlling for factors such as income and working at home, we find that the effects of congestion on access depend on whether congestion-adaptive travel choices (such as walking and making shorter trips to nearby destinations) are viable. Because “congestion-adapted” places tend to host more trip-making, planners may be justified in creating more such places in order to increase accessibility, even if doing so makes absolute levels of congestion worse in the process.     

Carer-employees’ travel behaviour: Assisted-transport in time and space

Assisted-transport demand is a daily caregiving task that affects carer-employee’s activity-travel behaviour; however, little is known about such behaviour and the types of constraints that impact carer-employee health. Combining the principles of Hägerstrand’s time geography and Mckie et al.’s caringscape terrain, this research develops a mixed-methods framework to classify the travel behaviour of carer-employees based on their travel experience and the space-time fixity of their weekly schedules. The mixed-methods framework consists of sentiment analysis and k-means clustering, both which are used to analyze 25 randomly selected participants within the Greater Toronto-Hamilton Area (GTAH). Participants were asked to reflect on their recorded one-week trips in a trip summary questionnaire. Sentiment analysis was used to thematically describe carer-employees’ travel behavior, whereas, k-means clustering generated travel behaviour profiles. “Time”, “pressure”, “parents”, “run”, and “long” were several thematic keywords describing the carer-employees’ travel behaviour. K-means clustering identified three relative types of carer-employees’ travel behaviours: 1) flexible, 2) between flexible and fixed, and; 3) fixed. These results provide critical information for the establishment of custom transport programs, such as maximum monthly telecommuting allotment; such programs are useful for employers to use in order to alleviate assisted-transport demand on their employees.     

Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic

The COVID-19 pandemic has led to a globally unprecedented change in human mobility. Leveraging two-year bike-sharing trips from the largest bike-sharing program in Chicago, this study examines the spatiotemporal evolution of bike-sharing usage across the pandemic and compares it with other modes of transport. A set of generalized additive (mixed) models are fitted to identify relationships and delineate nonlinear temporal interactions between station-level daily bike-sharing usage and various independent variables including socio-demographics, land use, transportation features, station characteristics, and COVID-19 infections. Results show: 1) the proportion of commuting trips is substantially lower during the pandemic; 2) the trend of bike-sharing usage follows an “increase-decrease-rebound” pattern; 3) bike-sharing presents as a more resilient option compared with transit, driving, and walking; 4) regions with more white, Asian, and fewer African-American residents are found to become less dependent on bike-sharing; 5) open space and residential areas exhibit less decrease and earlier start-to-recover time; 6) stations near the city center, with more docks, or located in high-income areas go from more increase before the pandemic to more decrease during the pandemic. Findings provide a timely understanding of bike-sharing usage changes and offer suggestions on how different stakeholders should respond to this unprecedented crisis.     

Bike-share rebalancing strategies,patterns, and purpose

We provide a first spatio-temporal exploration of bicycle sharing system (BSS) rebalancing patterns from data extracted for individual stations at a fine temporal scale and operator interviews. Analyzing rebalancing operations for nine BSS, we describe implications for operators, municipalities, and future optimization work. We find that stations adjacent to transit hubs receive disproportionate amounts of rebalancing relative to trips and that rebalancing is more often responding to morning and afternoon demand exceeding station dock capacities rather than longer term accumulations of bicycles. More importantly, we observe some operator’ rebalancing behaviors constrained between opposing goals of maximizing trips, profits, and service level agreements. Many BSS have no explicitly defined purpose, but existing rebalancing strategies can support or clash with the purpose or suggested benefits of a BSS.     

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.     

Can freeway traffic volume information facilitate urban accessibility assessment?: Case study of the city of St. Louis

In urban contexts, accessibility measures are often utilized to represent the interactions among land use, transport and people’s trips to services and other facilities. Accessibility is generally evaluated using conventional traffic measures such as travel time and distance, but traffic volume, which is a product of the travel trips induced by people’s needs, may also be positively related to accessibility. This study tests the hypothesis “can freeway traffic volume information facilitate urban accessibility assessment?” Traffic volume based accessibility models are proposed to investigate this relationship and test the hypothesis. The results indicate that the answer to this question is a qualified “yes”, as there is a statistically significant relationship between traffic volume differences and accessibility. The coefficients of the models can potentially be used as a reference to guide the urban planning process. The limitations of the proposed models can be addressed by deploying Intelligent Transportation Systems (ITS) traffic sensors on ramps and arterial roadways.     

Mobility in different generations of older persons: The development of daily travel in different cohorts in Denmark,Norway and Sweden

In the Scandinavian countries Denmark, Norway and Sweden, the proportion of older people in the total population is expected to reach about 25% in 2060. The ageing of the population has a variety of social implications. One aspect of population ageing that has relatively little attention in the Scandinavian countries is the question of everyday mobility. The purpose of this paper is to get a better understanding of the activity and travel patterns of different groups of older people, examine how travel- and activity patterns are developing during the life course, study the changes over time and how the “new” generations of older people behave compared to the older ones. The method used is cohort analysis of National Travel Surveys from the three countries in a 20 years perspective. Results show a significant period effect in car ownership and use among older people in Denmark, Norway and Sweden with a clear increase during the past 20 years. This is especially true for women. The increase in the number of driver’s licence-holders and car availability is reflected in travel mode choice among older people: both men and women maintain their car-use habits at old age. Another clear finding is that older people today travel more than the comparable age groups 20–25 years ago: everyday trip rates are higher and activities outside home are more common. While commuting and work-related trips decline after retirement, shopping and leisure trips do not start to decline before high age. From the cohort analysis we see that leisure and shopping trips are maintained in the period after retirement, and the car is important to reach shopping malls, health service, leisure activities, visit relatives and other social company.     

Inequalities in the London bicycle sharing system revisited: impacts of extending the scheme to poorer areas but then doubling prices

Cycling confers transport, health and environmental benefits, and bicycle sharing systems are an increasingly popular means of promoting urban cycling. Following the launch of the London bicycle sharing system (LBSS) in 2010, women and residents of deprived areas were under-represented among initial users. This paper examines how the profile of users has changed across the scheme’s first 3 years, using total-population registration and usage data. We find that women still make fewer than 20% of all ‘registered-use’ LBSS trips, although evidence from elsewhere suggests that the introduction of ‘casual’ use has encouraged a higher overall female share of trips. The proportion of trips by registered users from ‘highly-deprived areas’ (in the top tenth nationally for income deprivation) rose from 6% to 12%. This was due not only to the 2012 LBSS extension to some of London’s poorest areas, but also to a steadily increasing share of trips by residents of highly-deprived areas in the original LBSS zone. Indirect evidence suggests, however, that the twofold increase in LBSS prices in January 2013 has disproportionately discouraged casual-use trips among residents of poorer areas. We conclude that residents in deprived areas can and do use bicycle sharing systems if these are built in their local areas, and may do so progressively more over time, but only if the schemes remain affordable relative to other modes.     

The effect of travel cost on frequencies of shopping and recreational trips in Sweden

This article focus on how the cost of travel affects travel behavior. A trip frequency model for recreational and shopping trips is suggested and used to investigate this. The data that is used comes from a Swedish travel habit survey where the respondents’ trip frequencies of both types of trips on a certain day are recorded. This is likely to introduce a correlation structure, which is incorporated in the model. Special attention is paid to the effect of travel cost on trip frequencies for different regions and income groups. As a measure of the sensitivity of cost changes, elasticity of demand is calculated. The precision of the elasticities are evaluated with simulated p-values.     

Do satisfying walking and cycling trips result in more future trips with active travel modes? An exploratory study

Previous studies have indicated that travel satisfaction - the experienced emotions during, and cognitive evaluation of, a trip - can be affected by travel mode choice and other trip characteristics. However, as satisfactory trips might improve a person's attitude towards the used mode, persons may be more likely to use that same mode for future trips of the same kind. Hence, a cyclical process between travel mode choice and travel satisfaction might occur. In this paper we begin to analyse this process—using a structural equation modelling approach on cross-sectional data—for people who engage in walking and cycling for leisure trips in the Belgian city of Ghent. The focus on walking and cycling reflects recent studies indicating that active travel is often associated with the highest levels of travel satisfaction. Results of this exploratory analysis offer tentative support for the idea of a cyclical process: the evaluation of walking and cycling trips positively affects the respondents' attitude towards the respective mode, which in turn has a positive effect on choosing that mode.     

Does urban living influence baby boomers’ travel behavior?

We compare the travel behavior of urban versus suburban baby boomers in the Boston metropolitan area. Using propensity score matching to attempt to control for self-selection and data from two surveys implemented in 2008 and 2010, we find that the urban boomers tend to be less automobile-dependent than suburban baby boomers. Urban baby boomers also make more recreational non-motorized transport (NMT), social, utilitarian, and transit commute trips. Most of these differences seem to be primarily a result of the urban setting, not the particular preferences of boomers living in urban settings. We find very small self-selection effects on automobile commuting, recreational NMT, and utilitarian trips: 1–7% of observed influence. We also find some evidence that baby boomers’ preference for social activities tends to be mismatched to their environments – suburban boomers want more social opportunities than their settings enable. For public transport, we find a relatively large self-selection effect, 43% of observed influence, suggesting a transit-oriented boomer market segment exists.     

Home-end and activity-end preferences for access to and egress from train stations in the Copenhagen region

Increasing public transport use with the aim of improving the sustainability of cities should focus not only on enhancing level and quality of the service offered, but also on understanding determinants of the choice of access and egress modes to and from the railway network. This study analyzes the difference in preferences at the home-end and activity-end for travelers who have chosen train as their main travel mode while investigating the effect of policy variables such as car parking availability, bicycle parking availability and type, and bicycle on train possibility. Specifically, this study analyzes the choices between five transport modes (i.e., “walk,” “bicycle,” “car driver,” “car passenger,” “bus”) for 2921 home-end and 3658 activity-end trips. Joint mixed logit models are specified and estimated to account for heteroscedasticity and correlation across alternative modes as well as taste heterogeneity across travelers. Model estimates and pseudo-elasticities uncover the importance of travel time and underline how the improvement of walkability, bikeability, and bus service would contribute significantly to the increase in the probability of choosing sustainable modes to and from train stations. Moreover, model results emphasize the role of bicycle parking in terms of the sheer number of spaces to be increased as well as covered places to be offered at the activity end, de facto giving the possibility to leave a bicycle at that end during the night. Lastly, model results show that it is a matter of not only time and trip characteristics, but also traveler characteristics, occupation, and purpose.     

Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel

Traffic-related carbon dioxide (CO₂) emissions have become a major problem in cities. Especially, the CO₂ emissions induced by taxis account for a high proportion in total CO₂ emissions. The availability of taxi trajectory data presents new opportunities for addressing CO₂ emissions induced by taxis. Few previous studies have analyzed the impact of human trips on CO₂ emissions. This paper investigates trip-related CO₂ emission patterns based on individuals' travel behavior using taxi trajectory data. First, we propose a trip purpose inference method that takes into account the spatiotemporal attractiveness of POIs to divide human trips into different types. Further, we reveal the spatiotemporal patterns of CO₂ emissions from various types of trips, including temporal regularity and periodicity as well as spatial distribution of “black areas”. Finally, comparative analysis of CO₂ emissions for different kinds of trips based on trip behavior is conducted using three variables, namely trip distance, trip duration and trip speed. This study is helpful for us to understand how to make travel and cities more sustainable through modifying people's trip behaviors or taxi trips.     

Travel time use and its impact on high-speed-railway passengers' travel satisfaction in the e-society

The availability of wireless networks and the pervasive use of mobile ICT devices have allowed passengers to conduct various e-activities during journeys. These various e-activities, in turn, may change people's conventional perception of travel time from being “wasteful” and “unproductive,” to “desirable” and giving rise to satisfaction. Journeys on high-speed railway (HSR) is particularly relevant for transport researchers to probe into this question because of its characteristics of being medium to long-distance (typically taking half-an-hour or more), seat availability, and a smooth ride. Using a questionnaire survey on passengers along the Shanghai-Nanjing HSR route, this study aims to examine the nature of ICT device use and in-vehicle e-activities conducted by HSR passengers and the influence on their travel satisfaction with their on-board journey experience. Our results reveal a high percentage of ICT device use and a wide variety of e-activities such as e-working, e-communication, and e-reading for leisure on HSR trains. In addition, the higher use of ICT device was associated with an increase of passengers' travel satisfaction. Furthermore, we found a positive effect of work-related e-activities on travel satisfaction for business/work trips, while a positive effect of entertainment-related e-activities for non-business/work trips. Given that HSR is potentially a more sustainable transport mode, some possible policy implications are proposed to encourage people to use HSR, as opposed to driving or flying, for medium to long-distance intercity journeys.     

Proactive vehicle routing with inferred demand to solve the bikesharing rebalancing problem

Bikesharing suffers from the effects of fluctuating demand that leads to system inefficiencies. We propose a framework to solve the dynamic bikesharing repositioning problem based on four core models: a demand forecasting model, a station inventory model, a redistribution needs model, and a vehicle-routing model. The approach is proactive instead of reactive, as bike repositioning occurs before inefficiencies are observed. The framework is tested using data from the Hubway Bikesharing system. Simulation results indicate that system performance improvements of 7% are achieved reducing the number of empty and full events by 57% and 76%, respectively, during PM peaks.     

Effects of upgrading to cycle highways - An analysis of demand induction,use patterns and satisfaction before and after

ObjectiveThe objective of the present study is to investigate the effects of improvements made to two large, interconnected bicycle infrastructure in the western suburbs of Copenhagen, Denmark, on bicycle volumes and mode share, and cyclists' behaviour, perceptions, and experiences.MethodsEffects are assessed by analysing data from automatic counting stations during 35 months to measure the changes in bicycle volumes on the investigated routes. Furthermore, a questionnaire survey repeated three times – before, and one and two years after opening the improved routes - is used. Findings are supported by a control survey at a nearby facility, which was not influenced by the infrastructure improvements.ResultsThe investments related to the two investigated cases of infrastructure improvements resulted in a significant increase in the volume of bicyclist two years after the improvements. On one of the routes, the “Albertslund Route”, on weekdays during the rush hour in daylight, an increase from 126 to 203 bicyclists/h was recorded, whereas an increase from 24 to 32 bicyclists/h was recorded at “Vestvolden” for the same period. Most of the increase could be attributed to relocation of bicyclists from other routes. Induced cycling trips – trips that were not previously made by bicycle - were estimated to account for only 4–5% of the bicyclists two years after improvements. Bicyclists using the improved route express an increase in satisfaction with the quality of the facilities, which is significantly higher than at the control site.ConclusionData from the counting stations provides useful information if measured over a long period. This is necessary to correct for factors such as climate effects and temporal variation. Investments in cycle infrastructure in the investigated case led to a higher number of bicyclists who were mainly relocated from other routes. A minor increase in the modal share of cyclists was observed two years after the infrastructure improvements. Furthermore, the investments resulted in a higher degree of satisfaction among active bicyclists. If measured over a longer period, this could lead to a higher modal share due to a potential social advertising effect.     

Active ageing in developing countries? – trip generation and tour complexity of older people in Metro Manila

There is by now quite a substantial body of literature discussing the impact of an ageing population in developed countries on travel needs and required changes to transport policy. As many newly developed and developing countries are following demographic trends of “first world” countries, but offset by some decades, the problem is, however, not limited to the industrialised nations. The focus of this paper is on Metro Manila and analyses travel patterns by those aged 60 or over. Trip frequency and tour complexity are analysed with ordered probit regression, separating the effects of socio-demographic characteristics as well as land-use patterns. The results are compared to observations made for cities in developed countries, in particular London as an example for a city in a first world country. We show that there is a more pronounced decrease in total trips made with increasing age in Manila. However, analysing for specific trip purposes we find, similarly to trends in developed countries, that the number of recreational trips is fairly constant in all age groups. Recreational activities also seem to take more time per day than average for younger old, possibly indicating the advent of similar active ageing trends as in industrialised nations. The paper concludes by discussing some implications given future economic trends and advocates that better datasets from developing and newly developed countries are required for urban planning in developing countries.     

Commuting patterns in the metropolitan region of Rio de Janeiro. What differences between formal and informal jobs?

Limiting commuting trips in major cities is important from the environmental, social and economic standpoints. In order to design policies that aim to change commuting practices it is, however, necessary to have acquired a good understanding of the trips in question and their determinants. However, these trips have been subjected to very little study in the cities of developing countries. This paper is concerned with the Rio de Janeiro Metropolitan Area (RJMA), and sets out to test the influence of “classical” socioeconomic and spatial variables on the distance and duration of the commuting trips of the region's inhabitants, especially those with the lowest incomes. The main original feature of this research is that it includes jobs in the informal sector. The results show that, all other things being equal, commuting distances and times are shorter for the informal sector, and people walk more from their homes to their place of work because jobs in the informal sector are more dispersed than jobs in the formal sectors. The notable exception is personal and household services for which employees (who are mainly women) live a long way from the city center where wealthy families (and their jobs) are concentrated.