An empirical investigation on the dynamic processes of activity scheduling and trip chaining

Investigation of the dynamic processes of activity scheduling and trip chaining has been an interest of transportation researchers over the past decade because of its relevance to the effectiveness of congestion management and intelligent transportation systems. To empirically examine the processes, a computerized survey instrument is developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes the investigation on the dynamic processes of activity scheduling and trip chaining based on data collected from a pilot study of the instrument. With the data, ordered logit models are applied to identify factors that are pertinent to the scheduling horizon of activities. Results of the empirical analysis show that a daily schedule often starts with certain activities occupying a portion of the schedule and other activities are then arranged around these pre-occupants. Activities of shorter duration are more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Persons with children often expect more constraining activities than those with no children. The analysis also shows that female respondents tend to be more structured in terms of how the week is planned. Additionally, analysis of travel patterns reveals that many trip-chains are formed opportunistically. Travel time required to reach an activity is positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.     

Modelling the joint choice of activity timing and duration

This paper develops a model of activity and trip scheduling that combines three elements that have to date mostly been investigated in isolation: the duration of activities, the time-of-day preference for activity participation and the effect of schedule delays on the valuation of activities. The model is an error component discrete choice model, describing individuals’ choice between alternative workday activity patterns. The utility function is formulated in a flexible way, applying a bell-shaped component to represent time-of-day preferences for activities. The model was tested using a 2001 data set from the Netherlands. The estimation results suggest that time-of-day preferences and schedule delays associated with the work activity are the most important factors influencing the scheduling of the work tour. Error components included in the model suggest that there is considerable unobserved heterogeneity with respect to mode preferences and schedule delay.     

Analysis of activity duration using the Puget sound transportation panel

In this paper, we extend previous analyses of temporal effects by examining the factors associated with activity generation and duration over four waves of the Puget sound transportation panel survey (PSTPS). A Cox proportional hazards model was specified for each of five activities: visiting, appointment, free time, personal business, and shopping. For each activity, the duration times are modeled with an emphasis on examining important higher order interactions. The results suggest that activity durations have changed significantly over the survey period. Many of the differences in activity durations over time were significant, and often associated with increasing numbers of children in the household and higher order interactions between sex and the sequencing of activities.     

Effects of household structure and selected travel characteristics on trip chaining

This paper analyzes trip chaining, focusing on how households organize non-work travel. A trip chaining typology is developed using household survey data from Portland, Oregon. Households are organized according to demographic structure, allowing analysis of trip chaining differences among household types. A logit model of the propensity to link non-work trips to the work commute is estimated. A more general model of household allocation of non-work travel among three alternative chain types — work commutes, multi-stop non-work journeys, and unlinked trips — is also developed and estimated. Empirical results indicate that the likelihood of linking work and non-work travel, and the more general organization of non-work travel, varies with respect to household structure and other factors which previous studies have found to be important. The effects of two congestion indicators on trip chaining were mixed: workers who commuted in peak periods were found to have lower propensity to form work/non-work chains, while a more general congestion indicator had no effect on the allocation of non-work trips among alternative chains.     

A model of daily time allocation to discretionary out-of-home activities and trips

This paper presents a model of discrete activity choice and continuous resource allocation which is based on the premise of random utility maximization and which can be conveniently estimated using existing statistical software packages. The model derivation involves virtually no approximations and adheres strictly to the utility maximization concept. The empirical analysis applies the model to the participation choice and resource (time) allocation to nonwork, out-of-home activities by workers. The statistical results show that activity choice and time allocation are governed by the same mechanism as the utilitarian assumptions indicate and support the theoretical framework employed in the model development.     

Measuring the impacts of weather variability on home-based trip chaining behaviour: a focus on spatial heterogeneity

Using the 2011 Swedish national travel survey data, this paper explores the influence of weather characteristics on individuals’ home-based trip chaining complexity. A series of panel mixed ordered Probit models are estimated to examine the influence of individual/household social demographics, land use characteristics, and weather characteristics on individuals’ home-based trip chaining complexity. A thermal index, the universal thermal climate index (UTCI), is used in this study instead of using directly measured weather variables in order to better approximate the effects of the thermal environment. The effects of UTCI are segmented into different seasons to account for the seasonal difference of UTCI effects. Moreover, a spatial expansion method is applied to allow the impacts of UTCI to vary across geographical locations, as individuals in different regions have different weather/climate adaptions. The effects of weather are examined in subsistence, routine, and discretionary trip chains. The results reveal that the ‘ground covered with snow’ condition is the most influential factor on the number of trips chained per trip chain among all other weather factors. The variation of UTCI significantly influences trip chaining complexity in autumn but not in spring and winter. The routine trip chains are found to be most elastic towards the variation of UTCI. The marginal effects of UTCI on the expected number of trips per routine trip chain have considerable spatial variations, while these spatial trends of UTCI effects are found to be not consistent over seasons.     

A latent class accelerated hazard model of social activity duration

Over the past decade, activity scheduling processes have gained increasing attention in the field of transportation research. However, still little is known about the scheduling of social activities even though these activities account for a large and growing portion of trips. This paper contributes to this knowledge. We analyze how the duration of social activities is influenced by social activity characteristics and characteristics of the relationship between the respondent and the contacted person(s). To that end, a latent class accelerated hazard model is estimated, based on social interaction diary data that was collected in the Netherlands in 2008. Chi-square tests and analyses of variance are used to test for significant relations between the latent classes and personal and household characteristics. Findings suggest that the social activity characteristics and the characteristics of the relationship between the socializing persons are highly significant in explaining social activity duration. This shows that social activities should not be considered as a homogenous set of activities and it underlines the importance of including the social context in travel-behavior models. Moreover, the results indicate that there is a substantial amount of latent heterogeneity across the population. Four latent classes are identified, showing different social activity durations, and different effects for both categories of explanatory variables. Latent class membership can be explained by household composition, socio-economic status (education, income and work hours), car ownership and the number of interactions in 2 days.     

Understanding the impact of e-commerce on last-mile light goods vehicle activity in urban areas: The case of London

Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.     

Modelling the dynamics between tour-based mode choices and tour-timing choices in daily activity scheduling

Transportation - The paper presents a dynamic discrete–continuous modelling approach to capture individuals’ tour-based mode choices and continuous time expenditure choices tradeoffs in...     

Modeling the spatial and temporal dimensions of recreational activity participation with a focus on physical activities

This study presents a unified framework to understand the weekday recreational activity participation time-use of adults, with an emphasis on the time expended in physically active recreation pursuits by location and by time-of-day. Such an analysis is important for a better understanding of how individuals incorporate physical activity into their daily activities on a typical weekday, and can inform the development of effective policy interventions to facilitate physical activity. Furthermore, such a study of participation and time use in recreational activity episodes contributes to activity-based travel demand modeling, since recreational activity participation comprises a substantial share of individuals’ total non-work activity participation. The methodology employed here is the multiple discrete continuous extreme value (MDCEV) model, which provides a unified framework to explicitly and endogenously examine time use by type, location, and timing. The data for the empirical analysis is drawn from the 2000 Bay Area Travel Survey (BATS), supplemented with other secondary sources that provide information on physical environment variables. To our knowledge, this is the first study to jointly address the issues of ‘where’, ‘when’ and ‘how much’ individuals choose to participate in ‘what type of (recreational) activity’.     

The regional impact of the TGV

Evidence on the regional impact of the TGV high speed rail line between Paris and Lyons is provided, on the basis of surveys carried out both before and after its inauguration. The timing of the TGV and the nature of the surveys are explained, while the analysis contrasts the impact on the Paris and Rhone-Alps regions at each end of the TGV line. Tourism and service industries are the main subjects of the research.Original in French.     

Assessing the impact of the National Cycle Network and physical activity lifestyle on cycling behaviour in England

This paper examines the association between access to National Cycle Network (NCN) routes in England and an individual’s cycling behaviour whilst accounting for their broader physical activity lifestyle and controlling for their socio-economic circumstances. It identifies a positive association between access to these routes and the total minutes of any form of cycling, and the number of days that cycling takes place primarily for recreational purposes. The broader physical activity of individuals also has a positive association with cycling. Walking appears most likely to be complementary to non-recreational cycling, whilst participation in sport with all forms of cycling, but not with longer duration utilitarian trips. The research also indicates that access to NCN routes has the potential to increase such cycling further, with the exception of longer utilitarian trips, as does a more physically active lifestyle, particularly walking. The main policy implications of the research are to recognise that cycling is intrinsically linked to other physical activity, notably, walking, but that the NCN routes measured in this study primarily support longer duration recreational activity, which is also affected by sporting activity. This suggests that one avenue for achieving the health benefits of cycling may be through promoting NCN routes to harness a more generally active lifestyle and particularly in leisure, whilst sustainability may be further promoted through being linked more to other active travel such as walking. There is a therefore a need to exploit the potential of such NCN route provision as part of this promotion.     

Temporal stability of travelers' activity choice and home-stay duration: Some empirical evidence

This paper explores the temporal stability of activity type-choice models and models of travelers' home-stay duration. To empirically evaluate this stability, a nested logit model of activity-type choice and a proportional hazards model of home-stay duration are estimated using data from two-day travel diaries collected in the fall of 1989 and again, from the same individuals, in the fall of 1990. The results show that the models are not temporally stable over the one year time period separating the two travel-diary samples. A number of possible reasons for this instability are discussed.     

The relation between daily travel and use of the home computer

On the basis of the Norwegian national personal travel survey (NPTS) 1997/98 and a connected mail back survey of the use of information – and communication technology at home, the relation between mobility and use of stationary communication has been studied. On the basis of these results we cannot see any direct substitutionary effects of the use of stationary technology at people's home on the use of mobile technology. Access to and use of information technology seems not to have a significant impact on travel activities in everyday life. Stationary communication seems to be a supplement to activities based on mobile technology. For people who work more than “normal” weekly working hours, stationary technology seems to give them greater flexibility in regard to where to work, but it does not necessarily reduce their travel activity. There is a tendency that people who own home computers make less work trips, but this does not affect the total number of daily trips. The spatial flexibility give a temporal flexibility, which means that work trips and other trips can be more dispersed over the day than is the situation today. The positive consequence can be a reduction in the rush-hour traffic; the negative is that it is more difficult to offer a high frequent public transport service when travel needs are more spread in time. Ownership and use of both mobile and stationary technologies are unequally distributed. Men, people with high education and income are the most frequent owners and users.     

Apps,activities and travel: an conceptual exploration based on activity theory

With the continuous advancement of (mobile) ICT devices and applications, their impact on travel, activities and time use becomes more diverse. This holds in particular for apps developed for mobile devices (smartphones). In this paper, we argue that the effect of ICT on travel and activities should be analysed at the level of a single specific device or application, rather than for broad classes of ICT devices. We propose activity theory as a framework to analyse the impact of smartphone apps on travel and activities. Activity theory describes how subjects apply tools (such as apps) to work on an object and achieve an outcome that is in line with the subject’s motive. The application of the tool is embedded in an activity system which includes a community, formal and informal rules and in which a division of labour exists. We apply activity theory to analyse the effects of Whatsapp and travel feedback apps, based on existing literature about these apps. The analyses suggest that the activity systems of each app differ greatly in terms of object, motive, outcomes, community and rules, with implications for their use and impact. Both apps have an impact on travel, but differ with respect to whether this effect is intentional. For both apps contradictions in the activity system can be identified, which may give rise to further development of the activity system. These seem, however, to be largest for travel feedback apps. Based on our exploration, we argue that quantitative research on the impact of apps should be complemented by qualitative research based on activity theory. In particular, activity theory may help to gain a better understanding of underlying mechanism by which apps influence travel, to strengthen the theoretical underpinning and interpretation of the results of quantitative research and to explore changes in the development and use of apps and their impact on travel behaviour.     

Studying the relationship between activity participation,social networks,expenditures and travel behavior on leisure activities

Transportation - In the context of an increasing interest in understanding travel for non-mandatory activities, such as recreation and socializing, this work focuses on studying the relationships...     

The impact of high-speed technology on railway demand

This paper estimates a passenger railway demand function to analyse effects arising from the introduction and use of high-speed technologies. The paper reports estimates of demand elasticities with respect to price, income, quality of service and a range of exogenous characteristics. The results show that travel time savings from conventional high-speed technology have a larger impact on passenger demand than tilting train technology. The introduction of conventional high-speed technology is associated with an 8% increase in passenger railway demand. Increasing the use of either type of high-speed technology appears to induce small positive effects on demand beyond those obtained from usual traffic density increases on non-high-speed existing technology.

The impact of ride-hailing on vehicle miles traveled

Transportation - Ride-haling such as Uber and Lyft are changing the ways people travel. Despite widespread claims that these services help reduce driving, there is little research on this topic....