Non-work Trips Research Articles

Interactive Effects of Built Environment and Parking Policy on Car Use: Examining Differences Between Work and Non-Work Trips

Considerable interest has been shown in decreasing car use through planning and policy-making efforts. However, little is known about the interactive effects of built environment (BE) and parking policy on car use, and it is unclear whether and how these effects differ across trip purposes. We conducted a web-based survey in Beijing and collected data from 1036 respondents, including 517 male and 519 female respondents. This study estimates the interactive effects of BE and parking policy on car use for home-based work and non-work trips by employing multilevel logit models. The results show that BE variables at trip origins and destinations are important for shaping car use for both home-based work and non-work trips. Specifically, land use mixture (Coeff. = −0.121), bus stop density (Coeff. = −0.006), and population density (Coeff. = −0.009) at residential locations are negative factors affecting car use for work trips, whereas distance to local center (Coeff. = 0.012) and distance to the city center (Coeff. = 0.019) at residential locations are positive factors. Land use mixture (Coeff. = −0.323), bus stop density (Coeff. = −0.008), road density (Coeff. = −0.002), and population density (Coeff. = −0.007) at residential locations are negative factors of car use for non-work trips. Among BE factors at destinations, land use mixture (Coeff. = −0.319), bus stop density (Coeff. = −0.015), road density (Coeff. = −0.008), distance to the local center (Coeff. = −0.018), and population density (Coeff. = −0.012) are negative factors for car use for work trips, whereas the negative factors for non-work trips are land use mix (Coeff. = −0. 218), bus stop density (Coeff. = −0.038), road density (Coeff. = −0.003), distance to the city center (Coeff. = −0.121), and population density (Coeff. = −0.009). The effects of BE variables can be strengthened or weakened by free parking and parking convenience. Moreover, the results identify significant differences in the effects between work and non-work trips. These findings inform planners and policymakers of how to coordinate the BE and parking policies to decrease car dependence.

Telework and the day-to-day variability of travel behaviour: The specificities of Fridays

This study investigates the uniqueness of Fridays for telework in relation to commuting and non-work travel patterns. Utilizing Bayesian analysis on UK National Travel Survey data (2015–2019), it explores differences in trip frequency, distance, time, and CO2 emissions across days, particularly focusing on teleworkers versus other workers. The findings highlight Fridays as a distinct day for teleworkers, marked by a 20 % reduction in commuting and increased non-work trips, particularly during afternoons and evenings, compared to other weekdays and non-teleworkers. Key factors influencing these patterns include commuting mode, particularly private car use, and rural residency. The study concludes by considering telework’s potential in reducing travelrelated CO2 emissions and its impact on public transport and local economies, especially post-COVID-19.

Travel behaviour and the 15-min City: Access intensity, sufficiency, and non-work car use in Toronto

One of the key travel behavioural assumptions in the 15-min City concept is that if daily necessities are nearby, residents would be encouraged to use slower but more sustainable modes, such as walking, cycling and public transit to reach these destinations, thereby reducing car dependence. This research explores non-work car use associated with the 15-min City concept in the City of Toronto, Canada. We first calculate transportation accessibility, or what we refer to as access intensity, to five categories of daily necessities (food, commercial, health, recreation, and education establishments) using walking, cycling, public transit, and driving. Next, these results are analyzed using a set of minimum access criteria to particular amenities within the different destination types to determine a set of binary access or sufficiency scores. Spatial patterns of accessibilities by mode show expected pockets of high and low access. However, further analysis of non-work trip rates using travel survey data suggests that increases in 15-min accessibilities by walking, cycling, and transit are associated with decreases in the use of driving for 15-min trips. In particular, driving rates decrease as sufficient walking, cycling, and transit access improves with the largest decrease associated with sufficient walking access to all five categories of necessities. This work offers important implications for sustainable transportation and land use planning as it appears that residents do use alternative and more sustainable modes when they are associated with sufficient accessibility to all categories of destinations.

Examining the relationship between car ownership, car use, and exercise: Role of the built environment

Although owning a car allows people to access distant fitness centers and may promote exercise, car use may encourage sedentary behavior and reduce exercise. There is no empirical evidence on the relationship between car ownership, car use, and exercise, and whether improving the built environment is useful to encourage exercise by affecting car ownership and usage. Through a survey of 1049 respondents in Shanghai and subsequent path analysis, we investigate the relationship between the built environment around residences and workplaces, car ownership, car usage for work and non-work trips, and the duration of exercise weekly. While car ownership directly fosters exercise, it indirectly reduces exercise due to increased car usage for work and non-work trips, and the negative effects outweigh the positive. Moreover, the built environment around residences and workplaces affects exercise through car ownership and usage. People living in dense and downtown neighborhoods conduct more exercise because of the fewer likelihood of owning and/or using cars. More intersections and transit stops around residences and mixed land use around workplaces reduce exercise by increasing car ownership and/or car usage. We conclude that reducing car ownership and usage can promote exercise, and built environment interventions are effective in enhancing public health outcomes.

Impact of Level 4 Automated Vehicles on Mode Choice Using a Needs‐Based Approach

With the emergence of Level 4 automated vehicles, it is necessary to investigate the impact of these vehicles on mode choice. Previous studies have looked at the potential benefits and drawbacks of automated vehicles, but there has been little research done on how these vehicles will impact individuals’ travel behaviors. This paper proposes a needs‐based approach to study the impact of Level 4 automated vehicles on mode choice. The approach takes into consideration the travel needs of different individuals and their willingness to adopt new technologies. Through a stated preference survey in China, the data on travel preferences and the perceived safety levels of automated vehicles can be collected. Then, a model is built to simulate the adoption of Level 4 automated vehicles and estimate the mode split for different scenarios. The results indicated that private AV modes are preferred, and business and nonwork trips may be the targeted market for all AV modes. Overall, value of automation increases with income for private modes, with large variance. Furthermore, Pro‐AV attitude has a positive effect on value of automation, especially for self‐owned AV and AV subscription. Accordingly, the needs‐based approach demonstrates a promising method to study the impact of new technologies on travel behaviors and provides insights for policy makers to promote more sustainable transportation systems.

Exploring the endogenous effects among car dependency, work arrangement choice, and daily travel using the 2017 NHTS data

The paper presents an effort in investigating the cause-effect relationships among telecommuting, car dependency, and trip making behavior. Data from the 2017 National Household Travel Survey (NHTS) was used to develop a structural equations model (with latent constructs) to examine the endogenous effects between the decision to telework, the degree of car dependency, and the number of daily trips. Using confirmatory factor analysis, car dependency was measured by vehicle ownership, annual mileage, and car use frequency. The model provided interesting insights. Car dependency had a negative (both direct and total) impact on telework, an inference that confirms the role of car dependency as a resistant factor against alternative work arrangements and potentially any other new tech-based policies. In the opposite direction and surprisingly, telework encouraged car dependency, which might indicate that teleworkers tended to utilize the relaxed temporal-spatial constraints for non-work trips, and they were unlikely to give up private vehicle ownership simply because of their option to telecommute. Second, number of daily trips tended to increase the probability to telework, confirming the positive endogenous role of daily activity patterns on work arrangement decisions in a daily framework. Lastly, the significant negative impact of telework on daily trips was positively mediated through car dependency, leading to a smaller negative total impact on daily trips. Our study confirms that the association between telework and trip generation is quite a complex and multi-faceted relationship, leaving the argument regarding whether or not telework increases the number of daily trips as a debatable topic that calls for further exploration.

COVID-19 and Teleworking: Lessons, Current Issues and Future Directions for Transport and Land-Use Planning

Teleworking has been considered to be one of the emanating behaviors from the pandemic that may become long-lasting. Wider adoption of teleworking may fundamentally change urban mobility and spaces across cities. However, knowledge about the potential implications of teleworking on urban transport and land-use systems post-pandemic is limited. Through a comprehensive review of existing teleworking studies, this research identifies gaps in the literature, discusses major issues for exploration and suggests future research directions. It also explores ways to utilize teleworking as an effective travel demand management strategy. Analysis shows that teleworking has the potential to substantially change city landscapes and can assist in reducing traffic congestion, greenhouse gas emissions, and energy use. Priority areas for further research are identified, such as in-home activities, residential location choice, non-work trip patterns, and energy consumption decisions of teleworkers for a clearer understanding of the relationship between teleworking and urban systems. Analysis also reveals several planning and policy challenges surrounding teleworking, including digital divide, urban sprawling, and transformation of city centers, among others. To fully realize the benefits of teleworking, planners need to reconfigure community design principles to promote mixed-use, lively, and vibrant neighborhoods where people can both live and work. At the same time, governments should consider providing incentives to both organizations and employees with an aim to retain teleworking. Results of this paper will be highly beneficial to transport and land-use researchers, planners, and policy makers.

Post-pandemic travel patterns of remote tech workers

Almost half of all jobs in the San Francisco Bay Area are “remote-eligible” – more than any other metropolitan area in the United States, due to the high concentration of employees in the technology sector who were early to embrace teleworking at the start of the COVID-19 pandemic in early 2020. Any significant share of these tech workers staying remote may have profound long-term impacts on aggregate travel patterns in the region. This research seeks to predict the magnitude of these impacts and derive insights about the newly learned behaviors of tech workers, as indicative of remote-eligible workers in general.A survey of over 660 tech workers ran from November 2021 to March 2022, asking about participants’ employers and remote work policies, commute details and mode preferences, non-work trips, and interest in relocation.Respondents expected employer-driven hybrid arrangements of 2–3 days per week in the office after the pandemic, which in turn dictated the number of predicted future commuting trips and suppressed interest in relocation. Though almost half of respondents expressed interest in moving, they only planned to move a median of 20.93 miles – staying within the region but shifting away from their offices and towards less dense and more automobile-oriented suburban neighborhoods.Additionally, those moving more than ten miles from their office are likely to switch to less sustainable travel modes. On the other hand, robust observed retention of online shopping habits for groceries and food delivery may mitigate the added vehicle trips caused by rebound effects.

Study of COVID-19 impact on users' perception for transport modes choice in India

The COVID-19 pandemic has adversely affected the transportation sector, leading to a change in travel behavior. One of the most important responses of countries worldwide to slow the spread of the pandemic has been to restrict the movement of people, which has had a considerable effect on transport systems and is likely to affect the modal choices of commuters. The social and economic effects of the COVID-19 epidemic on public transportation encompass beyond service performance and health risks to social equity, financial viability, and sustainable mobility. To assess the likely nature of such a shift, this study attempts to understand mode choice based on the perception of commuters for their work and non-work trips after the lockdown phase due to COVID-19. The Multinomial Logit Model was used in this study to find the association of mode choice with health-related safety perceptions of commuters for private and public transport, and their socio-economic and travel characteristics. Mode choice for private transport was found for work trips, whereas non-motorized transport for non-work (shopping, leisure, etc.) trips up to a distance of 10 km. The model results showed that significant factors for the increase in the usage of private transport and non-motorized transport relative to public transport were physical distancing and hygiene. This study provides results for future transportation policies in the post-COVID period. The results, like emerging positive perceptions of non-motorized modes, are very useful for making better investments in the country to promote sustainable transportation and articulating solutions to address high-risk perceptions associated with public transport modes.

Who is returning to public transport for non-work trips after COVID-19? Evidence from older citizens' smart cards in the UK's second largest city region

Harnessing a unique data source – longitudinal travel smartcard data linked to passenger demographics from 2019 to 2022 – we use methods of survival analysis to model the recovery of public transport patronage among 183,891 senior citizens resident in the West Midlands metropolitan region in the United Kingdom. Comparing pre and peri-pandemic patronage, we identify pronounced social and spatial inequalities in the speed of return to public transport. We find that male, younger and non-White passengers are more likely to return to public transport as soon as movement restrictions were lifted, whereas passengers from White ethnic background and affluent areas do not return to public transport within the first year after the outbreak. Pronounced social inequalities persist into the middle of 2021, and only thence they began to attenuate as part of a wider return to public transport among passengers post retirement age. In 2022, 80% of these passengers have returned to public transport but the frequency of use has remained lower than prior to the pandemic. We discuss implications for transport policy and planning.

Travel behavior of unbanked, underbanked, and ultra-low-income transit riders in Ohio under covid-19

This research focuses on unbanked, underbanked and ultra-low-income (household income under $10,000) transit riders and their travel frequency before and during the COVID-19 pandemic. 1608 transit riders from Ohio and northern Kentucky were surveyed between October 2020 and April 2021. The study examines which demographic and socioeconomic factors are associated with being unbanked or underbanked, and whether the change in weekly trips per respondent after the onset of COVID-19 varied according to banked and income status. Logistic regression analysis revealed that the unbanked respondents are most likely to have household income less than $40,000, possess no high school degree, or live in public housing. Based on the OLS regression results, the unbanked and underbanked riders reduced their total weekly trips by about 17% and 22% respectively during COVID, compared to a 35% reduction by banked riders. All income groups in our sample reduced non-work trips to a greater extent than they did work trips. However, the responsiveness of weekly work trips within the ultra-low-income group (16%) during COVID was one of the smallest among all income groups. The analysis also revealed a significant interaction between banked status and income: unbanked riders earning between $10,000 and $30,000 cut back on work and medical trips by a significantly lower proportion, compared to banked riders in the same income categories. In line with existing research, the predicted decrease in trips during COVID compared to pre-COVID was generally smaller for the lower income groups in our sample, especially for work trips. These disparities in trip frequency after the onset of the pandemic suggest that different groups of transit users may have been impacted differently by service reductions and shutdowns.

COVID-19 and income profile: How communities in the United States responded to mobility restrictions in the pandemic's early stages.

Mobility interventions in communities play a critical role in containing a pandemic at an early stage. The real-world practice of social distancing can enlighten policymakers and help them implement more efficient and effective control measures. A lack of such research using real-world observations initiates this article. We analyzed the social distancing performance of 66,149 census tracts from 3,142 counties in the United States with a specific focus on income profile. Six daily mobility metrics, including a social distancing index, stay-at-home percentage, miles traveled per person, trip rate, work trip rate, and non-work trip rate, were produced for each census tract using the location data from over 100 million anonymous devices on a monthly basis. Each mobility metric was further tabulated by three perspectives of social distancing performance: "best performance," "effort," and "consistency." We found that for all 18 indicators, high-income communities demonstrated better social distancing performance. Such disparities between communities of different income levels are presented in detail in this article. The comparisons across scenarios also raise other concerns for low-income communities, such as employment status, working conditions, and accessibility to basic needs. This article lays out a series of facts extracted from real-world data and offers compelling perspectives for future discussions.

The daily mobility of older adults: Urban/rural differences in ten developed countries

AbstractThis paper explores the mobility patterns of older adults in ten countries, with a focus on the differences produced by urban environments in their non-work trips. Using detailed time use diaries from the Multinational Time Use Study for the last two decades, we analyze the trips associated with leisure and housework of non-working older adults. The results show that older adults in urban areas spend more time in leisure trips than similar individuals in rural areas. On the other hand, male older adults in urban areas spend less time in housework trips than do their counterparts in rural areas. However, such correlations are found to differ by country, gender, type of trip, and mode of transport, revealing complex correlations between urban forms and older adults’ daily mobility. Furthermore, factors such as the number of railway kilometers, gross domestic product growth rates, and the percentage of urban population in the country seem to be associated with differences in the behavior of older adults in their non-work daily trips.

COVID-19 impacts on non-work travel patterns: A place-based investigation using smartphone mobility data.

The COVID-19 pandemic has brought unprecedented changes to our mobility. It has not only changed our work-related travel patterns but also impacted leisure and other utilitarian activities. Non–work-related trips tend to be more seriously affected by the neighborhood/contextual factors such as socioeconomic status (SES), and destination accessibility, and COVID-19 impact on non-work trips may not be equal across different neighborhood SES. This study compares non–work-related travel patterns between the pre- and during COVID-19 pandemic in the City of El Paso, Texas. By utilizing smartphone mobility data, we captured the visitation data for major non-work destinations such as restaurants, supermarkets, drinking places, religious organizations, and parks. We used Census block groups (n = 424) within the city and divided them into low- and high-income neighborhoods based on the citywide median. Overall, the total frequency of visitations and the distances traveled to visit these non-work destinations were influenced by the COVID-19 pandemic. However, significant variations existed in their visitation patterns by the type of non-work destinations. While the overall COVID-19 effects on non-work activities were evident, its effects on the travel patterns to each destination were not equal by neighborhood SES. We also found that COVID-19 had differently influenced non-work activities between high- and low-income block groups. Our findings suggest that the COVID-19 pandemic may exacerbate neighborhood-level inequalities in non-work trips. Thus, safe and affordable transportation options together with compact and walkable community development appear imperative to support daily travel needs for various utilitarian and leisure purposes, especially in low-income neighborhoods.

The frequency use and the modal shift to ICT-based mobility services

The information and communication technology (ICT) plays an important role in improving energy consumption efficiency and reducing the emission level in the urban transport sector. ICT-based mobility services like ridesourcing provide smart tools and algorithms for matching travel demand and supply and more convenient door to door services. However, there is a concern that the convenience and competitive service fares of these new mobility modes encourage people to make more car travel or shift from more sustainable mobility modes like public transport to car travels. Therefore, it is necessary to study the frequency use and modal shift to this new mobility mode, particularly in the cities (like Cairo), where the ICT-based mobility services contain more ridesourcing of fossil fuel cars than other modes like online bikes/scooter sharing. A survey was conducted in Cairo, and logit models were developed to analyze the associations of socioeconomic, travel behavior variables with the frequency use and modal shift to ridesourcing. The results of ordinal logistic regression indicate that people who live near a metro station, with higher income, and with more non-work trips per week are more likely to be high-frequent users of ridesourcing. Moreover, women are more likely to use ridesourcing frequently than men in Cairo. The findings indicate that the most replaced mode by ridesourcing is traditional taxis (by 33 %), and the second and third shifted modes are private cars and public transport by 30% and 24 %, respectively. The results of multinomial logistic regression show that the socioeconomic parameters have significant associations with the probability of modal shift from public transport, taxis, and private cars to ridesourcing services. • Ordinal and multinominal logits were used to model the frequency use and modal shift. • Women are more likely to be high-frequent users of ridesourcing than men in Cairo. • Citizens living near metro stations, are more likely to use ridesourcing frequently. • The most replaced transport mode by ridesourcing is white taxis in Cairo. • The second and third shifted modes are private cars and public transport.

Interaction Between Information and Communication Technologies and Travel Behavior: Using Behavioral Data to Explore Correlates of the COVID-19 Pandemic

The COVID-19 pandemic has highlighted the importance of information and communication technologies (ICTs) in providing virtual engagement. Planners and engineers must determine whether cities will see reductions in travel demand, given the increasing use of ICTs. Notably, ICTs facilitate online shopping and working from home (WFH). Generally, online shopping may lead to fewer shopping trips; similarly, WFH may reduce work-related trips. However, more WFH has the potential to generate other non-work trips, including shopping trips. To find answers and explore interdependencies, this study integrates pre-pandemic behavioral data with during-pandemic travel data. In our framework, WFH and online shopping are considered together. By harnessing the pre-pandemic 2017 National Household Travel Survey data, this study jointly analyzes the relationships between shopping trips, online shopping, and WFH with a conditional mixed process model that can address unobserved endogeneity and selection bias. The results suggest that, before the pandemic, online shopping was associated with fewer in-person shopping trips while WFH was associated with more shopping trips. The role of socio-demographic, locational, and travel-related factors is also explored. The during-pandemic data and analysis capture how COVID-19 affected travel behavior. Results show that the relationships among the key variables found in the pre-pandemic data are similar but differ in magnitude from during the pandemic. WFH increased from 12% to 61% during COVID-19, admittedly an unusual situation. In the next “new normal,” planners may improve travel demand models by treating WFH explicitly as an alternative to traveling to work in the trip generation and time of day models.

Transit and Active Transportation Use for Non-Commute Travel Among Portland Transit-Oriented Development Residents

Transit-oriented development (TOD) seeks to promote non-single occupancy vehicle travel by placing dense residential and mixed-use buildings near high-capacity, high-frequency transit. Most research to date on the impact of TODs on travel behavior has focused on commute trips; however, many trips are for non-work purposes, and a sizable portion of the population does not commute to work. This study utilizes a set of surveys, conducted between 2005 and 2019 in the Portland OR region to assess factors associated with whether or not, and how often, TOD residents walk, bike, or take transit for home-based non-work trips. Findings show that about 20% of TOD residents take transit for non-work trips at least once per week, while 65% walk or bike for such trips. Attitudes and housing preferences are important factors in predicting whether and how frequently TOD residents walk, bicycle, or take transit for non-work trips. TOD residents make more non-work trips on transit when there is better transit access, and they walk and bicycle for more of these trips when street connectivity is higher. Lower access to a personal vehicle is also an important factor in non-work travel.

Impacts of disability on daily travel behaviour: A systematic review

ABSTRACT While people with disabilities have different travel patterns compared with the general traveller population, such discrepancies are ignored in mainstream travel demand modelling and planning practice. The failure to represent the diverse travel behaviour of people with disabilities leads to inaccurate forecasting and poor decision-making and exacerbates transportation disadvantages. Thus, this systematic review synthesises previous studies of travel behaviours among people with disabilities, differing from people without disabilities, in terms of trip frequency, mode choice, travel time and distance, and barriers. This review identified 115 peer-reviewed studies of the daily travel patterns of individuals across three categories of disabilities—mobility, cognitive, and sensory. Our review reveals that persons with disabilities make 10–30% fewer trips than those without disabilities, particularly non-work trips. Another significant difference is in travel mode choice—increased uses of public transit and taxi and riding with others and decreased walking and driving among those with disabilities. People with disabilities are prone to utilising slower means of transportation and travelling shorter distances. The quantitative review highlighted a limited considertation of the built environment characteristics and temporal factors as travel behavour predictors. Further, our qualitative review shows that despite a high level of adaptation, persons with disabilities encounter many barriers in the built environment to their transportation access. The environmental, social, and system barriers make specific modes unavailable to travellers with disabilities, increase travel time, and eventually decrease their trip frequency. This paper provides implications for travel demand modelling and urban and transportation planning and policy that better supports the transportation needs of persons with disabilities.

Investigating the impacts of transit-oriented development on transport-related CO2 emissions

Transit-oriented development (TOD) is considered as one of the most sustainable neighborhood planning practices, yet relatively little evidence exists on the environmental sustainability of TODs. This study examines transport-related CO 2 emissions of TODs in Dhaka, Bangladesh. Individual-level CO 2 emissions were calculated for three types of trips (home-based work, home-based school, and home-based other non-work) of 31,101 residents living in TOD and non-TOD neighborhoods. Three multi-level models were estimated, one for each trip type, to identify the effects of TODs on CO 2 emissions, controlling for spatial heterogeneity and spatial dependency of the neighborhoods and other confounding effects. Findings show that TODs have the potential to reduce CO 2 emissions for work and school trips, but not for other non-work trips in Dhaka. While the results partially verify the environmental sustainability outcome of TODs, how to design TODs to capitalize full environmental benefits remains a challenge for planners in developing countries.

Impact of COVID-19 on Perception of Commuters towards Work and Non-Work Trips in India

Impact of COVID-19 on Perception of Commuters towards Work and Non-Work Trips in India