Commuter Travel Research Articles

COVID-19, commuter territories and the e-bike boom.

The appearance and integration of e‐bikes in public space is a source of much debate worldwide. This paper offers insights to these debates by reflecting on how Deleuze and Guattari's concept of assemblage as territory helps us to understand the uptake of e‐bike commuter cycling during the Covid‐19 pandemic through empirical material from a study conducted in Sydney, Australia. Here we conceptualise commuter journeys in terms of processes of deterritorialisation and reterritorialisation; experienced through the affective territories generated by e‐bikes. The disclosure of commuter cycling sensations generated by the pandemic disruptions to commuter routines provided an important lens through which to understand the uptake of e‐bikes. The paper concludes by showing the utility of the concept of territory as a means of theorising changes to everyday mobility practices.

Analyzing COVID-19's impact on the travel mobility of various social groups in China's Greater Bay Area via mobile phone big data.

The COVID-19 outbreak has significantly impacted people’s mobility in terms of travel, which is directly related to regional economic vitality and individuals’ well-being. This study conducted research on the COVID-19 epidemic’s impact on travel mobility in China’s Greater Bay Area, utilizing mobile phone big data. The overall influence of COVID-19 was measured by investigating the impact between different income and migration groups in three core cities: Shenzhen, Guangzhou, and Foshan. Individuals’ weekly activity space area and travel frequency were calculated, and the average values between the different cities and various social groups were compared. The results showed that travel mobility declined during the epidemic’s peak, followed by a recovery based on the overall trend. The start and end of strict law enforcement had a significant impact on the initial decline and subsequent recovery of travel mobility in the core cities. COVID-19 had a larger impact on core cities than peripheral areas, and on non-commute travel frequency, compared to commute travel frequency. Compared to advantaged groups, socially disadvantaged groups experienced a steeper decline in travel mobility during the epidemic’s peak, but a more significant recovery afterwards. These findings indicate that discretionary activities have not yet recovered and remain below the pre-epidemic level, and that disadvantaged social groups had limited access to superior precautionary measures for avoiding infection. Based on the findings, we provide several policy suggestions regarding the recovery of travel mobility.

The impact of traffic demand management policy mix on commuter travel choices

The experience of traffic demand management policy in many cities shows that a single policy instrument has limited effect and may have side effects on other contemporaneous policies; therefore, formulating a policy mix is a more effective way to solve urban traffic problems. However, the bulk of previous literature has focused on the impact of single policy instruments, neglecting the growing interest in understanding the role played by the different combinations of policy instruments. Therefore, using a 6*3 matrix typology, this paper provides an empirical impact analysis of selected policy mixes in inducing sustainable travel behavior and reducing private car use. This study also designs orthogonal experiments and adopts stated preference questionnaires to analyze the main effects and full combined effects of packages of policy instruments through multinomial logit models. The results show that the effect of a policy mix is often not better than that of a single policy and demonstrate the need for careful systemic design. A balanced-designed policy mix can facilitate public transportation and help reduce traffic gridlock using a balanced combination of push, pull and systemic TDM policy instruments.

Simulating the impact of privately owned automated vehicles within the region Test Bed Lower Saxony, Germany

Automated and connected vehicles are assumed to have a major impact on road safety, traffic flow, energy consumption, greenhouse gas emissions, as well as on future mobility. This paper aims to analyze, the impact of privately owned automated vehicles on travel behavior in the region covering the Test Bed Lower Saxony in Germany. The main focus is laid on the evaluation of long-distance trips in the entire study area as well as on commuter journeys to and from the city of Brunswick. An agent-based demand model in conjunction with a traffic flow model was used to simulate four scenarios with different penetration rates of fully automated vehicles. The results show a major shift in the mode share, an increasing of the daily mileage, and reduced travel time of the motorized individual transport, as well as minor changes in travel distance and total traffic volume.

Habit Dependence in Car Ownership and Commuter Travel Mode Choice: Evidence from a Longitudinal Survey in China

Habit Dependence in Car Ownership and Commuter Travel Mode Choice: Evidence from a Longitudinal Survey in China

Public transport travel mode chain and its implications for commute satisfaction: Take Xi'an as an example

The continuous expansion of urban population and space scale, the continuous increase of daily average traffic trips and per capita travel distance, and the increasingly frequent urban economic activities have formed diversified travel demands. Based on the survey data, this study combs the commuter travel mode chain of Xi'an with public transport as the main body, and explores the satisfaction of current commuter bus passengers. First of all, the impact factors of each link of the public transport travel mode chain are sorted out. Based on the three levels of reachability, accessibility and connectivity, this paper proposes an evaluation index system of urban public transport commuting service, including convenience, safety, comfort, reliability and other specific indicators. Secondly, the commuting satisfaction evaluation scale is constructed to evaluate the subjective experience of travellers in the travel process. The results show that there is a gap between the expectation of commuters and the perception of public transport service attributes. Among them, "convenience" and "comfort" of public transport are the most important service quality attributes related to the satisfaction of commuters, and residents are the least satisfied with the convenience of transit, and public transport lines fail to meet the commuting needs of some residents. When transport operators provide services that meet passengers' expectations, passenger satisfaction and PBT utilization rate will be improved, service quality of public transport mode chain will be improved, sustainable transport will be promoted, and energy consumption and emissions will be reduced.

What Counts as Commute Travel? Identification and Resolution of Key Issues around Measuring Complex Commutes in the National Household Travel Survey

We use travel diary data from the 2017 National Household Travel Survey (NHTS) Georgia subsample to address critical issues associated with analyzing complex work journeys. To define the work journey, we discuss the importance of defining commute anchors by both purpose and location. We then compare two alternate measures for determining what portion of each journey should be counted as commute distance: the last leg of the journey (the NHTS default), and a modeled counterfactual simple commute to estimate the distance that would have been traveled had no stops been made. The average complex commute distance obtained using the counterfactual method was 63% higher than the estimate based on using the last leg alone. Using the last-leg method may understate Georgia’s annual commute distance by 2.6 billion miles (10% of the total, including both simple and complex commutes). We argue that the last-leg method is not an accurate gauge of work travel, particularly among populations such as women, who are more likely to trip chain on their commutes.

Identifying the Service Areas and Travel Demand of the Commuter Customized Bus Based on Mobile Phone Signaling Data

In recent years, customized bus (CB), as a complementary form of urban public transport, can reduce residents’ travel costs, alleviate urban traffic congestion, reduce vehicle exhaust emissions, and contribute to the sustainable development of society. At present, customized bus travel demand information collection method is passive. There exist disadvantages such as the amount of information obtained is less, the access method is relatively single, and more potential travel demands cannot be met. This study aims to combine mobile phone signaling data, point of interest (POI) data, and secondary property price data to propose a method for identifying the service areas of commuter CB and travel demand. Firstly, mobile phone signaling data is preprocessed to identify the commuter’s location of employment and residence. Based on this, the time-space potential model for commuter CB is proposed. Secondly, objective factors affecting commuters’ choice to take commuter CB are used as model input variables. Logistic regression models are applied to estimate the probability of the grids being used as commuter CB service areas and the probability of the existence of potential travel demand in the grids and, further, to dig into the time-space distribution characteristics of people with potential demand for CB travel and analyze the distribution of high hotspot service areas. Finally, the analysis is carried out with practical cases and three lines are used as examples. The results show that the operating companies are profitable without government subsidies, which confirms the effectiveness of the method proposed in this paper in practical applications.

Bike Shares and Commute Travel Modes in Chinese Cities: A Socio-Ecological Study

Bike Shares and Commute Travel Modes in Chinese Cities: A Socio-Ecological Study

Health, environmental and distributional impacts of cycling uptake: The model underlying the Propensity to Cycle tool for England and Wales

IntroductionThe Propensity to Cycle Tool (PCT) is a widely used free, open source and publicly available tool for modelling cycling uptake and corresponding health and carbon impacts in England and Wales. In this paper we present the methods for our new individual-level modelling representing all commuters in England and Wales. MethodsScenario commuter cycling potential in the PCT is modelled as a function of route distance and hilliness between home and work. Our new individual-level approach has allowed us to create an additional “Near Market” scenario where age, gender, ethnicity, car ownership and area level deprivation also affect an individual's likelihood of switching to cycling. For this and other scenarios, we calculate the carbon benefits of cycling uptake based on the trip distance and previous mode, while health benefits are additionally affected by hilliness and baseline average mortality risk. This allows the estimation of how health and carbon benefits differ by demographic group as well as by scenario. ResultsWhile cycle commuting in England and Wales is demographically skewed towards men and white people, women and people from ethnic minorities have greater cycling potential based on route distance and hilliness. Benefits from cycling uptake are distributed differently again. For example, while increasing female cycling mode share is good for equity, each additional female cyclist generates a smaller average health and carbon benefit than a male cyclist. This is based on women's lower baseline mortality risk, shorter commute travel distances, and lower propensity to commute by car than men. ConclusionWe have demonstrated a new approach to modelling that allows for more sophisticated and nuanced assessment of cycling uptake and subsequent benefits, under different scenarios. Health and carbon are increasingly incorporated into appraisal of active travel schemes, valuing important outcomes. However, especially with better representation of demographic factors, this can act as a barrier to equity goals.

Comparing immigrant commute travel adaptation across and within racial/ethnic groups

This research investigates differences in the adaptation process of immigrant commute distance and commute mode across and within three racial/ethnic groups—white, Hispanic, and Asian—in the United States to explore policies that facilitate immigrant travel in an efficient and sustainable way. A two-step analysis is conducted: the first step uses all US-born as the reference group, and the second step uses US-born of the same race/ethnicity as the reference. The second step overcomes a potential problem in existing research on immigrant travel adaptation: When all US-born are used as the reference group, the statistics mainly reflect the travel behavior of US-born white people, masking intrinsic travel differences among US-born racial/ethnic groups. Based on multi-level regression analysis of the 2017 National Household Travel Survey (NHTS) data, our results support existing findings of initial difference but eventual convergence of immigrant commute behavior with US-born, while highlighting white immigrants' persistence and Hispanic immigrants' low propensity in using non-automobile modes. Comparison results based on the two reference groups suggest that segmented assimilation due to racial/ethnic group membership is limited. Still, nuanced findings denote distinctive spatial mechanisms that affect immigrant and US-born Asians and highlight the short time window after immigrants' arrival in the U.S. during which policies might contribute to a continuation of their sustainable travel patterns.

E-bike user groups and substitution effects: evidence from longitudinal travel data in the Netherlands

In recent years, the e-bike has become increasingly popular in many European countries. With higher speeds and less effort needed, the e-bike is a promising mode of transport to many, and it is considered a good alternative for certain car trips by policy-makers and planners. A major limitation of many studies that investigate such substitution effects of the e-bike, is their reliance on cross-sectional data which do not allow an assessment of within-person travel mode changes. As a consequence, there is currently no consensus about the e-bike’s potential to replace car trips. Furthermore, there has been little research focusing on heterogeneity among e-bike users. In this respect, it is likely that different groups exist that use the e-bike for different reasons (e.g. leisure vs commute travel), something which will also influence possible substitution patterns. This paper contributes to the literature in two ways: (1) it presents a statistical analysis to assess the extent to which e-bike trips are substituting trips by other travel modes based on longitudinal data; (2) it reveals different user groups among the e-bike population. A Random Intercept Cross-Lagged Panel Model is estimated using five waves of data from the Netherlands Mobility Panel. Furthermore, a Latent Class Analysis is performed using data from the Dutch national travel survey. Results show that, when using longitudinal data, the substitution effects between e-bike and the competing travel modes of car and public transport are not as significant as reported in earlier research. In general, e-bike trips only significantly reduce conventional bicycle trips in the Netherlands, which can be regarded an unwanted effect from a policy-viewpoint. For commuting, the e-bike also substitutes car trips. Furthermore, results show that there are five different user groups with their own distinct behaviour patterns and socio-demographic characteristics. They also show that groups that use the e-bike primarily for commuting or education are growing at a much higher rate than groups that mainly use the e-bike for leisure and shopping purposes.

Estimates of the Carbon Impacts of Commute Travel Restrictions due to COVID-19 in the UK

This paper explores the carbon impacts of the reductions in commute travel which resulted from restrictions placed on the general population in the UK. The article uses anonymised and aggregated mobile data for the period February 2020 to June 2020 to understand how commute trips changed spatially. This has been linked to journey length and emissions data to produce estimates of the consequent reductions in CO2 (an average range of 17-60%). At a local level, the key factors that contributed to substantial CO2 reductions were high car ownership, paired with the prevalence of specific industrial employment types that could readily transition from a desk-based work to virtual working.

Inferring the Purposes of using Ride-Hailing Services through Data Fusion of Trip Trajectories, Secondary Travel Surveys, and Land Use Data

This paper presents a data fusion methodology for inferring trip purposes from GPS trajectories of ride-hailing services in Toronto. The methodology has a discrete choice model at its core that predicts the most probable purpose distributions using only basic trip-related information such as approximate pick-up and drop-off locations, trip start times, and land use characteristics around the origins and destinations. The choice model is estimated using revealed trip purpose data from a small-sample travel survey augmented by land use information from an enhanced point of interest database and the census. The methodology is applied to the trajectories of commercial ride-hailing trips made in Toronto between September 2016 and September 2018. For the core choice model, multinomial, nested, and mixed multinomial logit models are compared. Validation of the inferred trip purposes using the trip purpose proportions from another independent survey (not used in choice model estimation) reveal that the multinomial logit model can infer ride-hailing trip purpose distribution with reasonable accuracy. The inferred purpose distribution explains the nature of ride-hailing trips and provides important context of travel demand generated by the services. The results indicate that although ride-hailing services are mostly used for discretionary activities, they also play important roles in daily commuter travel. A quarter of the total weekday ride-hailing trips were made for work- and school-related activities. With increasing ridership, these services may start influencing conventional travel modes and thereby adversely affect the level of traffic congestion and transit ridership in the city.

Changing mobility patterns in the Netherlands during COVID-19 outbreak

ABSTRACT The COVID-19 outbreak and associated measures taken had an enormous impact on society as well as a disruptive, but not necessarily negative, impact on mobility. The Ministry of Infrastructure and Water Management received the most recent insights from the Dutch Mobility Panel (DMP) on a weekly basis. These insights were used to monitor the travel behaviour and to analyse changes in the behaviour of different groups and usage of modes of transport during COVID-19. The analysis shows an enormous decrease in travel at the beginning of the implementation of the so-called ‘intelligent’ lockdown and gradual increase again towards comparable levels as before this ‘intelligent lockdown, although the distribution over time, motives and used modes has changed. It becomes clear that not everyone needs to travel during peak hours and commuter travel is also not the main reason for the increase in car usage. Furthermore, cycling has shown to be an alternative option for travellers and public transport is hardly used anymore. If it is possible to sustain the lower level of car usage and integrate public transport as an important alternative for travel again, the COVID-19 impact on mobility could have a substantial remaining positive impact on mobility.

Exploring satisfaction with travel time profiles towards understanding intrinsic utilities of travel time

Although commuting is often viewed as a burden, transportation research has recently investigated satisfaction with commuting or commute travel times, with a goal to understand intrinsic utilities of travel time: when and for whom travel is productive or beneficial, beyond reaching a destination. However, few studies have examined perceived satisfaction with a range of travel times, and those that have only report aggregate trends. Thus, there is a need to illuminate and explain heterogeneity in travel time satisfaction profiles. By exploring individual-level responses to questions about satisfaction with hypothetical commute travel times among 588 commuters in Portland, Oregon, this study makes three contributions. First, through clustering, we identify eight different satisfaction with travel time profiles. Only one (the smallest group) has the same non-monotonic shape found in past research. Others are distinguished by different tolerable commute times: when (compared to an average/threshold commute time of 30 min) satisfaction levels drop. On this basis, we further categorize profiles into three groups: Monotonic low-tolerance (ML), Monotonic high-tolerance (MH), and Non-monotonic (NM) commuters. Second, through multinomial and ordered logit models, we determine factors associated with having a specific satisfaction profile or tolerable commute time. Significant differences are found for commute travel times (actual or ideal), mode choice (cycling), measures of intrinsic utility (satisfaction with actual commute times and the teleportation test), and a few personal characteristics (self-employment). Third, through visual comparisons, we find within-person consistency in responses to all of these questions about the intrinsic utility of travel time, supporting their use in past and future research.

Pooled versus private ride-hailing: A joint revealed and stated preference analysis recognizing psycho-social factors

Pooled mobility services hold substantial promise as a means to provide better accessibility to those who may find it difficult to drive themselves, while also promoting sustainable transportation efforts. In this paper, we develop a joint revealed preference-stated preference model for the choice between pooled versus private ride-hailing that (a) accommodates a suite of individual-level socio-demographics, individual-level psycho-social attributes, built environment variables, and trip-level variables, and (b) explicitly recognizes the importance of considering familiarity with pooled ride-hailing (RH) as an integral element of the pooled RH choice process. The primary source of data for the analysis is drawn from a 2019 survey of Austin, Texas residents. Our results underscore the value of using psycho-social latent constructs in the adoption of current and emerging mobility services, both in terms of improved prediction fit as well as in terms of designing proactive strategies to promote pooled RH service adoption. Women, older adults, and non-Hispanic/non-Latino Whites have a low propensity to choose the pooled RH mode, while employed individuals, highly educated individuals, and those living in high density urban areas have a high propensity. Overall, the average VTT estimate is $27.80 per hour for commute travel, $19.40 per hour for shopping travel, and $10.70 per hour for leisure travel, while the willingness to pool (that is, the willingness to pay to not pool a ride or WTS) averages about 62 cents for commute travel, $1.70 for shopping travel and $1.32 for leisure travel. These estimates can be used by TNCs and cities to consider new integrated pooled RH-fixed transit service designs, position traffic congestion alleviation strategies and new mobility services, and customize information campaigns to promote pooled RH mode use.

ПОРІВНЯННЯ СПОЖИВЧОЇ ЦІННОСТІ ПОЇЗДОК ПРИВАТНИМ АВТОМОБІЛЕМ І ТРАНСПОРТОМ ЗАГАЛЬНОГО КОРИСТУВАННЯ У ПРИМІСЬКОМУ СПОЛУЧЕННІ

The consumer's decision on the choice of a way to move in space, but directly in this article on the choice of the type private or suburban public transport, is based on the person's expectation of the consumer value of the trip, which will have a certain size and content. Consumer value for suburban transportation – as a result of the interaction of the passenger with the carrier. The elements of the consumer value for suburban passenger transportation by public transport are shown in general. With the help of previous research in this area, as well as the author's own experience, the elements and content of the consumer value, commuter travel by public transport and private car, are further formed and revealed. The elements of consumer value consist of the preferences and sacrifices of the passenger. The article aims to use more modern and universal approaches to shaping the consumer value content and components of commuter travel. This set-up should be based on a sequence of modern scientific and practical approaches to the core of SC services. Methods of synthesis and analysis, induction and deduction, and generalization are used in the study (to determine the content of public transport and suburban transport by private vehicle and the elements of consumer value). A positive result of the interaction between passenger and carrier is the guarantee of more active use of public transport services by the consumer. In addition to increasing the consumer value of such services, it will encourage consumers to abandon the use of private transport for the public benefit. A well-thought-out policy on the tariff plan, improving the comfort and quality of services provided by public transport helps to attract the maximum number of passengers who use public transport and also attaches great importance to the economic effect of the consumer value of suburban travel by public transport. The results of the study can be applied in favor of reducing the use of a large number of private transports, which will enable the formulation and implementation of policies to protect the environment and the environmental situation.

Study on commuter travel of urban workers——Analysis of coordination between ground bus and rail transit in Beijing

At present, with the advancement of China’s urbanization construction process, China’s urbanization rate has gradually increased in recent years, and the population in the suburbs and surrounding towns and rural areas continue to pour into large cities, which inevitably leads to a series of social problems in the process of China’s urban economic development. In the process of population gathering in large cities, traffic problems have a great impact on urban workers. With the increase of urban population and the rising stock of private cars, the efficiency of ground transportation continues to decline; the population aggregation in big cities, the poor travel experience of public transport system in the morning and evening rush hours on weekdays, and the long commuting time and distance of workers restrict the long-term development of large cities in China to a certain extent. This paper studies the coordination between ground public transport and rail transit in Beijing with reference to the coordination of the development of ground public transport and rail transit. Finally, based on these problems, this paper puts forward some suggestions for the long-term coordinated development of public transport in Beijing.

The application of travel demand management initiatives within a university setting

A biennial transport survey at the University of Aberdeen was analysed over a ten-year period to better understand the influence of travel demand management (TDM) initiatives on the commuting habits of staff and students. Campus-based TDM initiatives such as a free inter-campus shuttle bus, charged parking permits and cycle infrastructure was introduced to encourage sustainable travel and to move away from single occupancy car journeys. To consider the impacts of TDM initiatives on staff and student travel choice, an index representing low emissions travel was created using estimated carbon intensity of travel options. Survey data was assessed across age categories, year, commuter travel distance, gender and status (staff or student) to enable discussion of how TDM implementations may have influenced clean travel choice across the survey periods.Outcomes indicated that TDM initiatives did not in themselves influence a substantial shift to clean transport options. A low carbon travel choice index was developed and median comparisons indicated that students travelled on average more by lower emissions transport methods, predominantly walking or cycling, than staff and showed greater variation across the full range of travel options. Staff exhibited significantly lower median index values. This is thought to be related to socio-economic factors between the groups combining with housing opportunities and residential choices over time.While TDM initiatives should be encouraged at institutions such as universities and hospitals, single institutions are unlikely to see a substantial transition to sustainable travel if wider societal infrastructure is not in place to enable people to be habituated to choosing sustainable options. Findings suggest that regional coordination is required for TDM to be societally accepted and successful.