Activity-travel Behavior Research Articles

The efficacy of an integrated intervention to encourage low-carbon travel behaviour

The importance of pro-environmental behaviour has increasingly attracted academics’ attention. However, limited research has taken place to investigate the efficacy of different interventions on encouraging pro-environmental behaviour. The effects of an integrated intervention on changing people’s actual travel behaviour also remain largely unfilled. Therefore, this empirical research aims to fill this research by examining the efficacy of an integrated intervention and its durability to encourage pro-environmental behaviour. SPSS programme was used to analyse the collected data: a primary online survey dataset and a secondary longitudinal dataset. The efficacy of the intervention was assessed using Kruskal-Wallis test and Wilcoxon Signed Ranks test was used to investigate the durability of its effectiveness.

Zoom in the attitude-behaviour gap: low carbon travel behaviour

The concept of pro-environmental behaviour in low carbon consumption has increasingly attracted academics’ attention in the last two decades. There has been a growing interest in exploring the association between people’s travel attitude and behaviour. This study has critically reviewed, compared, and discussed some of the key theories around these research topics. However, based on the findings of the literature review, there is a dearth of research examining the association between people’s travel attitude and their actual behaviour. Therefore, this study seeks to fill the gap by examining the causal linkage between people’s attitude towards a specific travel mode and their actual travel behaviour.

Assessing Two-way and One-way Carsharing: an Agent-Based Simulation Approach

Carsharing companies can customize their service by adopting different pricing schemes and offers with the aim of increasing fleet use and profits. Different business models have been developed such as round-trip and one-way. It is clear that, even though many aspects of the business model and operations are the same, the different way in which these services are supplied leads to a diverse response from the users. In this work, we analyze how a fixed pricing scheme affects the behavior of the members of two different carsharing systems: two-way and one-way, explicitly considering their different income distributions to analyze social equity aspects. The dynamic pricing policy is simulated in MATSim, an agent-based simulator able to generate realistic mode choices based on individual activity-travel behavior. Scenarios with a synthetic population of carsharing members for the city of Berlin are analyzed. We aim to provide an experimental analysis that addresses the different behavior of different demand sectors, categorized by income, in function of the supply distributed on the territory. Simulation results show that the two services are not in competition between each other: the two-way service is used as a substitute for private cars while the one-way system is preferred from agents who choose to use multiple types of modes during the day. The response from the different income classes tends to be similar for both services since all the users within the same purchase power have the same degree of acceptance for both systems.

Spatial conditions for car dependency in mid-sized European city regions

ABSTRACT We analysed the spatial conditions for Car Dependency (CD) in three European cities and their suburbs, to investigate the following research question: What are the potential travel mode alternatives to the car, and how do they relate to actual travel behaviour? We defined CD as the lack of alternative transport modes to the car for reaching daily destinations. We selected three mid-sized city regions with different planning traditions and travel behaviour: Eindhoven, Southampton and Aachen. The results demonstrate that the differences in CD in the three cities are not substantial. The suburbs show a substantially higher CD than the city proper; however, when considering the e-bicycle as an alternative transport mode, this difference decreases. Daily amenities are largely within walking distance, in cities as well as in suburbs. For the daily commute there seems to be great potential for the (e)-bicycle as most employees, living both in the cities and their suburbs, currently live within 15 km of their jobs. Overall, our research shows that the differences in the actual modal split in the three cities cannot be explained by differences in the spatial conditions for CD.

Major investment in active travel in Outer London: Impacts on travel behaviour, physical activity, and health

IntroductionThis paper analyses three years’ data from the People and Places longitudinal study. The study examines the travel behaviour impacts of major investments in active travel infrastructure in three Outer London boroughs (the ‘mini- Hollands programme’). MethodsThe People and Places survey, conducted annually in May-June, treats the mini-Holland interventions as a ‘natural experiment’. Participants in other Outer London boroughs form a control group. The survey had over 3,000 respondents at baseline (May-June 2016). Three follow-up waves each had over 1400 repeat respondents. A difference-in-differences analysis was used to compare changes in active travel uptake in intervention and control groups. Further analysis examines likelihood of meeting targets for past-week active travel and all physical activity. Finally, the article conducts a health economic benefit assessment based on uptake of active travel at Wave 3. ResultsAt all waves, living close to mini-Holland interventions (‘high-dose’ areas) was consistently associated with increased duration of past-week active travel, compared with the control group (44.0 extra minutes in Wave 2, 41.0 in Wave 1, and 41.5 in Wave 3). Changes in active travel behaviour were stronger in the high-dose area than in the low-dose area. Most of the increase was in walking. People living in high-dose areas were 13% more likely at Wave 3 to achieve 140 minutes active travel than people in control areas. People living in high- or low-dose areas in mini-Holland boroughs were more likely to be physically active for 5 days in the past week. The 20- year health economic benefit in high-dose areas from three years’ of interventions (costing £80 million) is £724 million. ConclusionAmbitious interventions can yield substantial health economic benefits from changes in active travel. This includes early uptake of walking as well as cycling. Most of the increase was in walking but the ratio varied by year.

Do accessibility and clustering affect active travel behavior in Salt Lake City?

While researchers recognize the relationship between general accessibility and active travel, it is rare to study the impact of accessibility to multi-use paths by non-motorized modes. Furthermore, auto-culture-derived issues in the U.S. imply the importance of promoting walking and cycling culture through understanding the clustering effect. Using 2012 Utah Travel Survey, this study is one of the rare that considers all typical categories of explanatory variables at two levels. First, a spatial probit model is estimated to identify whether and why people in Salt Lake City walked or cycled; second, for people who walked or cycled, a spatial autoregressive model is estimated to explore travel time by walking or cycling. The results not only reveal how accessibility to multi-use paths and attitudes influence active travel together but also report opposite spatial autocorrelations at two levels. These findings will help decision-makers efficiently decide strategical planning components to promote active transportation.

A Study on Impact of Sustainable Transportation Systems Indian Cities Using For EDAS Methods

India is undergoing economic change. Cities now have better quality of life, and they are now crucial hubs for human existence. The increase in urbanization of Indian cities was facilitated by this influx of people. Prosperity and changing lifestyles brought about by a booming economy made reliance on private vehicles essential. The total demand for travel has accelerated along with population expansion and increased car ownership, but the supply side has lagged behind demand and there are numerous external variables associated to transportation, such as accidents, congestion, pollution, inequality, etc. Promoting and promoting sustainability is important in the contemporary urban transportation environment, sustainable transportation policies. These policies' principal goal is to change people's travel habits, or, in other words, to alter the travel environment. However, many of these rules' ramifications are unclear or complicated. As a result, it is critical that decision-makers are informed of the effects of such policies before adopting and putting them into practice. Models of travel demand can be used in this situation to forecast future travel demand under various policy scenarios. In order to analyze sustainable transportation strategies, this study analyses the possibilities of travel demand models already in use in India. The study discovered that the trip-based, four-step aggregate method used in India as the standard model system was nsufficient for studying sustainable transportation policy. An analysis of an alternative strategy known as activity-based travel demand modeling revealed that it could manage such policies better than traditional models and was useful in selecting the best combination of policies for particular circumstances. Since India has not yet created an operational activity-based travel demand modeling system, the study concludes by proposing a conceptual framework for an integrated activity-based demand model based on the needs identified within the review's framework. In accordance with people's current activity-travel behavior, it can be utilized to create modified and verified applications for existing travel demand models. The final result is done by using the EDAS method. Delhi is highest Value and Agra is lowest value.

Modelling the effects of COVID-19 on travel mode choice behaviour in India

The COVID-19 pandemic has resulted in unprecedented changes in the activity patterns and travel behaviour around the world. Some of these behavioural changes are in response to restrictive measures imposed by the Government (e.g. full or partial lock-downs), while others are driven by perceptions of own safety and/or commitment to slow down the spread (e.g. during the preceding and following period of a lock-down). Travel behaviour amidst the stricter of these measures is quite straightforward to predict as people have very limited choices, but it is more challenging to predict the behavioural changes in the absence of restrictive measures. The limited research so far has demonstrated that different socio-demographic groups of different countries have changed travel behaviour in response to COVID-19 in different ways. However, no studies to date have either (a) investigated the changes in travel behaviour in the context of the Global South, or (b) modelled the relationship between changes in transport mode usage and traveller characteristics in order to quantify the associated heterogeneity. In this paper, we address these two gaps by developing mathematical models to quantify the effect of the socio-demographic characteristics of the travellers on the mode-specific trip frequencies before (January 2020) and during the early stages of COVID-19 spread in India (March 2020). Primary data collected from 498 respondents participating in online surveys have been used to estimate multiple discrete choice extreme value (MDCEV) models in this regard. Results indicate – a) significant inertia to continue using the pre-COVID modes, and b) high propensity to shift to virtual (e.g. work from home, online shopping, etc.) and private modes (e.g. car, motorcycle) from shared ones (e.g. bus and ride-share options). The extent of inertia varies with the trip purpose (commute and discretionary) and trip lengths. The results also demonstrate significant heterogeneity based on age, income, and working status of the respondents. The findings will be directly useful for planners and policy-makers in India as well as some other countries of the Global South in better predicting the mode-specific demand levels and subsequently, making better investment and operational decisions during similar disruptions.

Integrated Impact Assessment of Active Travel: Expanding the Scope of the Health Economic Assessment Tool (HEAT) for Walking and Cycling.

The World Health Organization’s Health Economic Assessment Tool (HEAT) for walking and cycling is a user-friendly web-based tool to assess the health impacts of active travel. HEAT, developed over 10 years ago, has been used by researchers, planners and policymakers alike in appraisals of walking and cycling policies at both national and more local scales. HEAT has undergone regular upgrades adopting the latest scientific evidence. This article presents the most recent upgrades of the tool. The health impacts of walking and/or cycling in a specified population are quantified in terms of premature deaths avoided (or caused). In addition to the calculation of benefits derived from physical activity, HEAT was recently expanded to include assessments of the burden associated with air pollution exposure and crash risks while walking or cycling. Further, the impacts on carbon emissions from mode shifts to active travel modes can now be assessed. The monetization of impacts using Value of Statistical Life and Social Costs of Carbon now uses country-specific values. As active travel inherently results in often substantial health benefits as well as not always negligible risks, assessments of active travel behavior or policies are incomplete without considering health implications. The recent developments of HEAT make it easier than ever to obtain ballpark estimates of health impacts and carbon emissions related to walking and cycling.

Exploration of Statewide Fragmentation of Activity and Travel and a Taxonomy of Daily Time Use Patterns using Sequence Analysis in California

Sequence analysis is used in this paper to measure fragmentation in activity participation and travel. Fragmentation here is defined as the sequencing of many short and long activities and trips that happen in a personal daily schedule. Studying sequences of daily episodes (each activity at a place and each trip) is preferable over other techniques of studying activity–travel behavior because sequences include the entire trajectory of a person’s activity during a day while jointly considering the number of activities and trips, their ordering, and their durations. We first identify places visited and duration at each place on a minute-by-minute basis, then we derive representative daily behavior patterns using hierarchical clustering. Our study shows there are at least nine distinct daily patterns with different sequencing of activities and travel as well as travel time ratios and modal split. These patterns include typical commute to work or school, staying at home all day, or traveling extensively. As expected, day of the week plays a major role in the type of daily activity–travel patterns. Travel time ratios are also examined for each daily pattern and we find differences in the role played within each pattern between central city, suburban, exurban, and rural dwellers. In a comparison of couples, we find systematically higher fragmentation in households that have children and their parents are employed, with women showing higher fragmentation in the activity–travel patterns.

Short- and Long-Term Impacts of Workplace Relocation: A Survey and Experience from the University of Luxembourg Relocation

Workplace relocation can have a significant impact on commuting trips as well as on the location and number of activities scheduled within the home-work tour. This often exogenous, non-voluntary event affects the entire activity-travel behavior of the employees. As response, employees can adopt several short- and long-term adaptation strategies to cope with such change, the most obvious being commuting mode shifting, acquire new mobility resources (e.g., buying a car) or changing residential location. As workplace relocation can be consequence of national policies aimed at decongesting the city centers or to favor the development of new business areas, undesired macroscopic changes in modal shares and in land developments may be observed. While a decrease in the commuting time after a workplace relocation is, in some cases, observed, an increase in car use for the commuting trip may be observed as well. This paper aims at providing an in-depth understanding of the effect of workplace relocation on travel behavior by reviewing and selecting the relevant scientific literature on the topic, which has in the last years gained popularity. The findings and observations summarized by the literature review are then complemented with the specific example of the relocation of the University of Luxembourg employees. Finally, we indicate potential directions for research, which are currently underexplored.

Effects of built environment on activity participation under different space-time constraints: A case study of Guangzhou, China

Conventional facility planning seeks to provide service facilities to meet population demand in an aggregate manner. However, recent studies reveal that the provision of facilities in residential neighborhoods does not necessarily mean easy service access for certain groups. This issue is approached through the lens of space–time constraints in this study, which asserts that because people with different socioeconomic attributes experience different space–time constraints, the effects of the same built environment on actual access can considerably vary. Based on the activity-diary data from 493 respondents in Guangzhou, China, this study conducts a quasi-experiment facilitated by the propensity score matching approach. Residents in low-density suburban areas and those in high-density central city areas are considered as the control and treatment groups, respectively. By comparing the activity-travel behavior between these two groups, this work presents an analysis of the effects of service density improvement on residents’ actual service access. Moreover, the differences of such effects are examined through separate quasi-experiments for residents with the largest, medium and smallest space–time constraints. Residents who originally experience the smallest space–time constraints could further benefit from the enhancement of service density, whereas those who originally suffer from the largest and medium space–time constraints could not. These findings imply that conventional facility planning may not provide equitable outcomes. Therefore, facility planning and management should address and integrate residents’ unequal experiences of space–time constraints into time-sensitive policies (e.g., flextime policies).

Clusters of Adolescent Physical Activity Tracker Patterns and Their Associations With Physical Activity Behaviors in Finland and Ireland: Cross-Sectional Study.

BackgroundPhysical activity trackers (PATs) such as apps and wearable devices (eg, sports watches, heart rate monitors) are increasingly being used by young adolescents. Despite the potential of PATs to help monitor and improve moderate-to-vigorous physical activity (MVPA) behaviors, there is a lack of research that confirms an association between PAT ownership or use and physical activity behaviors at the population level.ObjectiveThe purpose of this study was to examine the ownership and use of PATs in youth and their associations with physical activity behaviors, including daily MVPA, sports club membership, and active travel, in 2 nationally representative samples of young adolescent males and females in Finland and Ireland.MethodsComparable data were gathered in the 2018 Finnish School-aged Physical Activity (F-SPA 2018, n=3311) and the 2018 Irish Children’s Sport Participation and Physical Activity (CSPPA 2018, n=4797) studies. A cluster analysis was performed to obtain the patterns of PAT ownership and usage by adolescents (age, 11-15 years). Four similar clusters were identified across Finnish and Irish adolescents: (1) no PATs, (2) PAT owners, (3) app users, and (4) wearable device users. Adjusted binary logistic regression analyses were used to evaluate how PAT clusters were associated with physical activity behaviors, including daily MVPA, membership of sports clubs, and active travel, after stratification by gender.ResultsThe proportion of app ownership among Finnish adolescents (2038/3311, 61.6%) was almost double that of their Irish counterparts (1738/4797, 36.2%). Despite these differences, the clustering patterns of PATs were similar between the 2 countries. App users were more likely to take part in daily MVPA (males, odds ratio [OR] 1.27, 95% CI 1.04-1.55; females, OR 1.49, 95% CI 1.20-1.85) and be members of sports clubs (males, OR 1.37, 95% CI 1.15-1.62; females, OR 1.25, 95% CI 1.07-1.50) compared to the no PATs cluster, after adjusting for country, age, family affluence, and disabilities. These associations, after the same adjustments, were even stronger for wearable device users to participate in daily MVPA (males, OR 1.83, 95% CI 1.49-2.23; females, OR 2.25, 95% CI 1.80-2.82) and be members of sports clubs (males, OR 1.88, 95% CI 1.55-2.88; females, OR 2.07, 95% CI 1.71-2.52). Significant associations were observed between male users of wearable devices and taking part in active travel behavior (OR 1.39, 95% CI 1.04-1.86).ConclusionsAlthough Finnish adolescents report more ownership of PATs than Irish adolescents, the patterns of use and ownership remain similar among the cohorts. The findings of our study show that physical activity behaviors were positively associated with wearable device users and app users. These findings were similar between males and females. Given the cross-sectional nature of this data, the relationship between using apps or wearable devices and enhancing physical activity behaviors requires further investigation.

Mode choice behaviour of students, integrating residential location characteristics: a study from Kochi City, India

Mode choice decision of individuals plays a vital role in transportation planning. Individual travel behaviour models can be improved by extending the set of influencing variables used for modelling. In a developing country like India, students contribute a major share of total travel demand especially during morning and evening peak hours of traffic; whose individual travel characteristics are very less studied by transportation professionals. This paper presents exploratory and statistical analysis of mode choice behaviour of students in Kochi City, India. The socio-demographic characteristics, activity-travel behaviour as well as residential location characteristics of students during a usual working day is collected using activity-travel survey data, in Kochi Municipal Corporation. Preliminary analysis gives details on daily activity-travel pattern, mode choice preferences and other particulars of commuters in the study area. Statistical models were developed for understanding the factors affecting mode choice decision and separate mode choice models are also developed for different categories of students. Simulation of choice probabilities over different attributes is also done to identify the potential policy variables that can promote the use of sustainable modes.

How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago

The novel COVID-19 pandemic has caused upheaval around the world and has led to drastic changes in our daily routines. Long-established routines such as commuting to workplace and in-store shopping are being replaced by telecommuting and online shopping. Many of these shifts were already underway for a long time, but the pandemic has accelerated them remarkably. This research is an effort to investigate how and to what extent people's mobility-styles and habitual travel behaviors have changed during the COVID-19 pandemic and to explore whether these changes will persist afterward or will bounce back to the pre-pandemic situation. To do so, a stated preference-revealed preference (SP-RP) survey is designed and implemented in the Chicago metropolitan area. The survey incorporates a comprehensive set of questions associated with individuals' travel behaviors, habits, and perceptions before and during the pandemic, as well as their expectations about the future. Analysis of the collected data reveals significant changes in various aspects of people's travel behavior. We also provide several insights for policymakers to be able to proactively plan for more equitable, sustainable, and resilient cities.

Exploring the correlations between spatiotemporal daily activity-travel patterns and stated interest and perception of risk with self-driving cars

Abstract. The key to Autonomous Vehicles (AVs) successful penetration of markets lies in identifying specific needs that AVs satisfy for daily activity-travel participation of individuals. In this paper we explore whether and to what extent people’s exhibited spatiotemporal activity-travel patterns correlate with their stated perceptions about self-driving cars. We investigate the travel diaries of 3,411 survey respondents who live in the Puget Sound region of the U.S. in 2017 using sequence analysis. In parallel, we apply hierarchical clustering to identify people’s attitudes based on their stated interest and perception of risks about AVs. A multinomial regression model is built to examine the correlations between AV attitude clusters and daily activity-travel patterns. Statistically significant correlations are then identified. The model results suggest that people exhibiting different activity-travel behavior patterns also express distinct attitudes towards the uses of AVs. The model shows that people who travel to work during the day are more likely to be positive to AVs. In particular, the group traveling to work later than the regular 8-to-5 schedule shows stronger interest and less concerns to AVs, which can be partially explained by the diverse activities they do throughout the day, the variety of travel modes they use and presumably more schedule flexibility they need than the public transportation system offers.

A study of tour formation: pre-, during, and post-recession analysis

This study examines changes in activity-travel patterns of employed people during a recession by using a tour-based representation of the activity-based approach. The term tour is defined as a sequence of trips and activities that begins and ends at home and contains at least one non-home activity. Tours are classified based on the presence of work and/or non-work activities. We are interested in investigating how a recession can affect an individual’s tour choices. We developed a rigorous methodological framework by using multi-group structural equation modeling (SEM) to analyze changes in tour choice. In particular, we developed a causal structure conceptualsizing the interrelationships among socio-demographic and economic characteristics, activity-travel participation, and the choice of various work and non-work tours. Using data from the American Time Use Survey (ATUS), the study found that activity-travel relationships and their role in tour choice differed in the recession year (2009) compared to pre- and post-recession years (2009 and 2012, respectively). By analyzing temporal changes in causal structure, we identified four sub-trend groups defined by: (1) norms that did not change in pre-, during, and post-recession years, (2) norms that changed during the recession but returned to the old norm, (3) norms that changed during the recession and were maintained as new norm, and finally (4) 2006 norms that did not change during the 2009 recession but changed after the recession. Via analysis of multiple group SEM, we identified instances of each of these cases and provided potential rationales in the context of how a recession can influence norms and thus can affect activity-travel behavior.

How Did People Respond to the COVID-19 Pandemic during Its Early Stage? A Case Study in Japan

With the aim of urgently providing policymakers with immediate scientific evidence about how to better inform the public about fighting against COVID-19, the author made an initial attempt to assess how people responded to this unprecedented virus during its early stages, in terms of both behaviors and attitudes. For this purpose, the author implemented a nation-wide questionnaire survey in Japan at the end of March when the country had 1,953 confirmed infection cases, in total. Valid data were collected from 1,052 residents from the whole of Japan with a balanced population distribution in terms of age, gender, and regions. Respondents were asked to report changes in their daily activity-travel behavior, long-distance trips, and other life activities caused by the COVID-19 pandemic, and their associated factors (information reliability, risk perception, attitudes about policy-making and communications with the public). Results of both aggregate and modeling (a structural equation model and a data mining approach) analyses indicate that poor communication with the public may be closely related to the spread of COVID-19 in Japan. It is also revealed that differentiated communications are necessary to encourage different types of behavioral changes.

Quantifying Travel Physical Energy Expenditure for Urban Travellers – A Case Study of Beijing

Travel physical energy expenditure for travellers has impact on travel mode choice behaviour. However, quantitative study on travel physical energy expenditure is rare. In this paper, the concept of travel physical energy expenditure coefficient has been presented. A case study has been carried out of young travellers in Beijing to get the value of physical energy expenditure per unit time under three transport modes, walking, car and public transportation. A series of experiments have been designed and conducted, which consider influence factors including age, gender, travel mode, riding posture, luggage level and crowded level. By analysing the travel data of money, travel time and physical energy expenditure, we determined that the value of travel physical energy expenditure coefficient δ is 0.058 RMB/KJ, which means that travellers can pay 0.058 RMB to reduce 1 KJ physical energy expenditure. Next, a travel mode choice model has been proposed using a multinomial logit model (MNL), considering economic cost, time cost and physical energy cost. Finally, the case study based on OD from Xizhimen to Tiantongyuan in Beijing was conducted. It is verified that it will be in better agreement with the actual travel behaviour when we take the physical energy expenditure for different types of travellers into account.

Statewide Analysis of Individuals’ Exposure to Business Establishments and Active Travel Behavior

This study analyzes the association between exposure to various economic establishments, such as retail stores and schools, and walking and cycling at the individual level. Instead of using a land use mix indicator applied in many previous studies, 17 types of establishments were investigated, based on the North American Industrial Classification System, located within individuals’ activity spaces. The 2017 Wisconsin Add-On to the National Household Travel Survey was used to compute the density of establishments for two different activity space measurements: (1) time-weighted one standard deviational ellipses, and (2) convex hulls. Among the significant results agreed on by both activity space measurements, walking and cycling are positively associated with exposure to educational services and public administration establishments, and negatively associated with exposure to finance and insurance establishments. The results indicate a possible strategy: active travel promotion could leverage the potential for schools and local government offices to serve as anchor institutions for health-promoting travel behavior. In addition to strategies for the built environment, the research also suggests that physical activity encouragement could target individuals, such as workers, who probably have exposure to establishments with a negative association with active travel, such as in the finance and insurance sector.