Travel Behavior Trends Research Articles

Can we focus long-distance travel survey sampling? Analyzing travel behavior trends between and within demographic groups

This work determines if there are statistically significant differences long-distance travel behaviors between and within different demographic groups, defined by income, age, and presence of children. This work considers data from three long-distance travel surveys, using ANOVA and Theil Index analyses. Results indicate long-distance sampling frames can be dramatically reduced based on simple combinations of household demographics. In most cases, only one or two demographics were necessary to statistically differentiate between the long-distance travel patterns of different groups. Therefore, practitioners could use these results to create more frequent and focused long-distance travel survey sampling frames reducing survey administrative costs and respondent burden.

Length-squared L-function for identifying clustering pattern of network-constrained flows

ABSTRACTThe network-constrained flow is defined as the movement between two locations along road networks, such as the residence-workplace flow of city dwellers. Among flow patterns, clustering (i.e. the origins and destinations are aggregated simultaneously) is one of the cities’ most common and vital patterns, which assists in uncovering fundamental mobility trends. The existing methods for detecting the clustering pattern of network-constrained flows do not consider the impact of road network topology complexity on detection results. They may underestimate the flow clustering between networks of simple topology (roads with simpler shapes and fewer links, e.g. straight roads) but with high network intensity (i.e. flow number per network flow space), and determining the actual scale of an observed pattern remains challenging. This study develops a novel method, the length-squared L-function, to identify clustering patterns of network-constrained flows. We first use the L-function and its derivative to examine the clustering scales. Further, we calculate the local L-function to ascertain the locations of the clustering patterns. In synthetic and practical experiments, our method can identify flow clustering patterns of high intensities and reveal the residents’ main travel behavior trends with taxi OD flows, providing more reasonable suggestions for urban planning.

Heterogeneity in mode choice behavior: A spatial latent class approach based on accessibility measures

We propose a method to estimate mode choice models, where preference parameters are sensitive to the spatial context of the trip origin, challenging traditional assumptions of spatial homogeneity in the relationship between travel modes and the built environment. The framework, called Spatial Latent Classes (SLC), is based on the integrated choice and latent class approach, although instead of defining classes for the decision maker, it estimates the probability of a location belonging to a class, as a function of spatial attributes. For each Spatial Latent Class, a different mode choice model is specified, and the resulting behavioral model for each location is a weighted average of all class-specific models, which is estimated to maximize the likelihood of reproducing observed travel behavior. We test our models with data from Portland, Oregon, specifying spatial class membership models as a function of local and regional accessibility measures. Results show the SLC increases model fit when compared with traditional methods and, more importantly, allows segmenting urban space into meaningful zones, where predominant travel behavior patterns can be easily identified. We believe this is a very intuitive way to spatially analyze travel behavior trends, allowing policymakers to identify target areas of the city and the accessibility levels required to attain desired modal splits.

Japanese travel behavior trends and change under COVID-19 state-of-emergency declaration: Nationwide observation by mobile phone location data

In the early stages of the COVID-19 pandemic, the Japan government could not impose strong restrictions such as lockdowns. Since there has been no such nation-wide behavioral analysis, we calculated indicators of nation-wide behavioral change using data based on mobile phone network.This study shows empirical facts and findings on behavioral changes under COVID-19 “state-of-emergency” declarations in Japan that are obtained by using mobile terminal network operational data. Results show that a significant reduction in trips and inter-prefectural travel was achieved without strong restrictions by the government. In addition, the population density index decreased by 20% and people avoided traveling to densely populated areas. This analysis shows that once people’s behavior is changed by the declaration of a state of emergency, it does not return to normal immediately after the lifting of the declaration; rather, it recovers slowly.

Incorporating habitual behavior into Mode choice Modeling in light of emerging mobility services

This paper presents a study in examining potential behavioral changes in light of emerging mobility options through a stated preference (SP) choice experiment. Particular focus was placed on incorporating habitual behavior into the modeling framework. Two parameters were constructed and explored in this study: habits associated with existing modes, and private mobility auxiliary expenses. A heuristic combined index was developed to quantify habitual strength of each mode based on their past behavior frequency and response frequency measures. Private mobility add-on expenses, i.e., parking cost and the time spent to find parking, were also analyzed. An error component model was developed to assess the impacts of habitual behavior and private mobility expenses on the propensity to shift from conventional modes (Auto driver, auto passenger, or public transit) to emerging modes (exclusive and shared on-demand services). The model was specifically designed to incorporate both random parameters and nested structure. Results showed that both parameters played significant roles in mobility choice decisions, and that their effects can compete with most of the traditional factors such as personal or trip attributes. Specifically, habits acted as a barrier toward behavioral changes, while the disutility factors associated with private mobility expenses could help break such habits. Market analysis based on habitual pattern and private mobility expense profiles can provide a foundation for better assessment of future travel behavior trends. This also paves the path towards the development of effective strategies in promoting alternative mobility options.

The city as a driver of new mobility patterns, cycling and gender equality: Travel behaviour trends in Stockholm 1985–2015

This paper analyses changes in individual travel behaviour in Stockholm County over 30 years, using three large cross-sectional travel survey data sets. It shows that travel patterns have diverged over time between city, suburban and rural residents. The trends in travel behaviour that we find are consistent with changes in the labour market, ICT use, land-use and transport policy, gender equality, and population composition trends. The inner city has become increasingly attractive: the share of trips is to the inner city is increasing for all purposes, socio-economic groups, and residential locations. The reduction of car traffic in response to the introduction of the congestion charges in 2006 is more than compensated by an increase in bicycle and transit trips to the inner city. Travel times by car are increasing in the city, although the car traffic volumes have decreased. The travel behaviour gender gap has closed completely in the inner city, but not further out in the region or in the rest of the country. Understanding long term trends in travel behaviour in different population segments, and the context under which they occur, helps to understand how the conditions, opportunities and constraints for different population segments are changing, which is key for transport policy and land-use planning. Since the societal trends driving travel behaviour in Stockholm and Sweden are much the same in many cities and countries, the findings are of general relevance.

The impact of millennials' travel behavior on future personal vehicle travel

The millennial generation, born between 1980 and 2000, is exhibiting different travel behavior trends than previous generations, which are shaped by several different yet correlated characteristics such as; place of residence, race/ethnicity, labor force participation, education level, income, living arrangements, lifecycle status, licensure status, vehicle ownership/availability, values, and propensity to substitute technology for travel. Many millennials are living with their parents longer, obtaining drivers licenses at older ages, postponing marriage and procreation, and substituting travel for work and socializing with telecommuting and social media. Millennials are currently shaping the nation's changing demographics, which in turn directly affect future travel behavior trends and their consequences on energy consumption and the environment.

Exploring public transport usage trends in an ageing population

An ageing population remains one of the most significant challenges for Western society in the 21st century. Whilst public transport use has attractive sustainability features for older generations there is mixed evidence with regard to trends in travel and public transport use in ageing societies. This paper explores public transport trip rates amongst older age groups using travel survey evidence collected from a household travel survey in Melbourne, Australia for the period 1994 to 1999. A particular aim of the research was to establish trends in trip rates so as to explore the impact of the ageing Baby Boomer generation on travel by public transport. The results suggested that compared to those aged below 60, those aged over 60 years demonstrated 30% lower trip making overall and 16% lower public transport trip rates. Longitudinal trends in trip rates showed those aged over 60 had a very small decline in trip rates by public transport (−0.004 average daily trips per annum) but increasing rates for car trips. A further analysis showed a small but significant increase in longitudinal trip rates of public transport use amongst Baby Boomers (0.004 daily trips p.a., p < .05) while car usage for Baby Boomers was steady. The implication of these findings is that trends in the existing over 60s population are not necessarily going to flow through to behaviour patterns in the Baby Boomer generations. The Baby Boomer age group showed longitudinal trends in travel behaviour which contrasted with those of the existing over 60s generation notably with a trend towards increased public transport usage.

Interrelations between travel mode choice and trip distance: trends in Germany 1976–2002

In recent decades, trends in travel behaviour have been characterised by increasing trip distances and a modal shift towards the private car. This paper reports findings from longitudinal analyses of the German nation-wide travel survey KONTIV for the period 1976–2002. It focuses on travel mode choice, subdivided by distance categories, and also takes car availability and city size into account. In addition, trends in car availability itself are examined by city size categories. The results indicate that even within the same distance categories car use has considerably increased. In some cases bicycle use has increased as well. Gains in the use of the private car are mainly at the expense of trips on foot and by public transport. Accordingly, the shift in modal split towards the car is not (only) caused by increasing trip distances but took place even within distance classes. Once car availability is taken into account, the modal shifts appear to be considerably weaker. This suggests that once car availability is held constant the decision rationales of mode choice for a certain trip distance have remained relatively stable. The increase in motorisation over the study period was considerably weaker in large cities than in small towns, although the cities started from a lower level in the 1970s. Thus, the motorisation divide between cities on the one hand, and suburban and rural areas on the other hand has become ever wider. For travel mode choice, the picture is similar. What is more, the results suggest that even car owners are more inclined to walk a given distance in the cities than in small towns, even more so if they live in a central urban area. The built environment, thus, appears to have a strong impact on whether an available car is used or not.

Two Cities, Two Realities?

Capitalizing on large-scale origin-destination travel surveys conducted in two large Canadian urban centers, Montreal and Toronto, this paper presents a comparative analysis of the travel behavior trends in relation to variables such as demography, car accessibility, home location, and employment status. With trip rate as the dependent variable, three disaggregate multivariate regression models were estimated to observe how behaviors have evolved over time and how individual features affect the way in which people travel. These multivariate models allow the observation of the similarities and differences between explanatory factors between regions and over time. Although both cities are facing similar trends, such as the aging of the population, increasing rates of motorization, declining household sizes, and urban sprawl, they are also the sites of different trends with respect to average trip rates, differences between genders, and the impacts of car access. The geographic and cultural differences found between the populations of Toronto and Montreal include a smaller gender impact on trip generation in Montreal and a smaller age impact in Toronto. The study identified changes in the magnitude of the influence of explanatory variables on trip generation over time, including the declining importance of age and gender. The most promising policy actions that could be taken to decrease trip rates would be those that affect a decrease in household automobile ownership, as determined on the basis of the analysis in this paper.

A gender perspective on urban car use: A qualitative case study

This paper examines the interconnections between the motor vehicle and social change for women. It summarises some of the key gender differences and trends in travel behaviour and transport use, and outlines a response to one broad question — how are the economic, social and cultural circumstances of the 1990s influencing women's transport patterns and car use?