Agent-based model for continuous activity planning with an open planning horizon

The paper proposes the microscopic travel demand model continuous target-based activity planning (C-TAP) that generates multi-week schedules by means of a continuous planning approach with an open planning horizon. C-TAP introduces behavioral targets to describe people’s motivation to perform activities, and it uses a planning heuristic to make on-the-fly decisions about upcoming activities. The planning heuristic bases its decisions on three aspects: a discomfort index derived from deviations from agents’ past performance with regard to their behavioral targets; the effectiveness of the immediate execution; and activity execution options available in the near future. The paper reports the results of a test scenario based on an existing 6-week continuous travel diary and validates C-TAP by comparing simulation results with observed behavioral patterns along several dimensions (weekday similarities, weekday execution probabilities of activities, transition probabilities between activities, duration distributions of activities, frequency distributions of activities, execution interval distributions of activities and weekly travel probability distributions). The results show that C-TAP has the capability to reproduce observed behavior and the flexibility to introduces new behavioral patterns.     

Does habitual car use not lead to more resistance to change of travel mode?

An experiment examined the effects of an intervention (combination of information and a free public transport ticket) in a changed decision context (moving to a new residence) on travel mode choice by car users. If past frequency of car use has resulted in an automatic response to goal-related cues, one should expect resistant to change of travel mode. However, the results failed to show this. Neither past behavior or a direct habit measure predicted future travel behavior. Instead, the intervention influenced attitude, subjective norm, and perceived behavioral control, and consistent with Ajzen's theory of planned behavior, these were the main causes of the change of travel mode.     

Do partners influence each other’s travel patterns? A new approach to study the role of social norms

To better understand the role of social norms in relation to people’s travel behavior this study addresses the question whether and to what extent partners in two-partner households influence each other’s travel patterns. For example, is the male household head more likely to start using the bicycle if the female household head also uses the bicycle (and vice versa)? While this is a straightforward question, it has, to the best of the author’s knowledge, not been explored in previous research. Using data from 958 couples from the German Mobility panel, the bidirectional effects between the travel patterns of male and female household heads are explored. To this end, the relatively new method of latent class transition analysis is used. The results show that, over time, travel pattern membership of the male household head influences travel pattern membership of the female household head and vice versa. Given that the effects are controlled for a range of individual and shared household characteristics, these results suggest that social norms at the household level play an important role. The paper concludes with an outlook on how the developed framework can be extended in the future.     

Understanding adolescents’ intentions to commute by car or bicycle as adults

This study focuses on the intentions of adolescents to commute by car or bicycle as adults. The behavioral model is based on intrapersonal and interpersonal constructs from the theory of planned behavior extended to include constructs from the institutional, community and policy domains. Data from a survey among Danish adolescents is analyzed. It is found that car use intentions are related to positive car passenger experience, general interest in cars, and car ownership norms, and are negatively related to willingness to accept car restrictions and perceived lack of behavioral control. Cycling intentions are related to positive cycling experience, willingness to accept car restrictions, negative attitudes towards cars, and bicycle-oriented future vision, and are negatively related to car ownership norms. Attitudinal constructs are related to individual characteristics, such as gender, residential location, current mode choice to daily activities, and parental travel patterns.     

The impacts of time of day pricing on car user behavior: findings from the Port Authority of New York and New Jersey��s initiative

This paper discusses the key findings from a research project that assessed the impacts of the Port Authority of New York and New Jersey??s Time of Day Pricing Initiative on the behavior of passenger car users. The survey data, comprised of 505 observations, show that 7.4% of passenger trips changed behavior because of the time of day pricing initiative, and that demand is inelastic to tolls with elasticities in the range of ?0.11 to ?0.24. Passenger car users who changed behavior responded to time of day pricing by implementing multidimensional strategies (3.23 different behavioral changes per user on average), involving behavioral responses such as changes in facility usage, changes in time of travel, changes in the payment type, and changes in mode/occupancy. The most frequently cited behavioral response was to shift mode, either to transit or carpool, and maintain the original time of travel (done in 2.55% of trips), instead of changing time of travel and maintaining the use of the passenger car (0.69% of trips). This reluctance to change travel schedules is undoubtedly a reflection of the limited time of travel flexibility that, on average, was estimated to be 20.4 and 12.3 min for early and late arrival for work-related trips. This, in turn, suggests the need for comprehensive policies, possibly involving incentives or regulations to foster employers?? participation in staggered/flexible work hour programs. Such approaches, combined with time of day pricing, are likely to be more effective in balancing car traffic during the day. Other behavioral responses of significance were reduce the number of trips made during the weekday peak-hours (1.65%), and switching to EZ-Pass to take advantage of the toll discounts (0.81%).     

Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers

For developing sustainable travel policies, it may be helpful to identify multimodal travelers, that is, travelers who make use of more than one mode of transport within a given period of time. Of special interest is identifying car drivers who also use public transport and/or bicycle, as this group is more likely to respond to policies that stimulate the use of those modes. It is suggested in the literature that this group may have less biased perceptions and different attitudes towards those modes. This supposition is examined in this paper by conducting a latent class cluster analysis, which identifies (multi)modal travel groups based on the self-reported frequency of mode use. Simultaneously, a membership function is estimated to predict the probability of belonging to each of the five identified (multi)modal travel groups, as a function of attitudinal variables in addition to structural variables. The results indicate that the (near) solo car drivers indeed have more negative attitudes towards public transport and bicycle, while frequent car drivers who also use public transport have less negative public transport attitudes. Although the results suggest that in four of the five identified travel groups, attitudes are congruent with travel mode use, this is not the case for the group who uses public transport most often. This group has relatively favorable car attitudes, and given that many young, low-income travelers belong to this group, it may be expected that at least part of this group will start using car more often once they can afford it. Based on the results, challenges for sustainable policies are formulated for each of the identified (multi)modal travel groups.     

When strike comes to town… anticipated and actual behavioural reactions to a one-day,pre-announced,complete rail strike in the Netherlands

We conducted secondary analysis on data collected among rail users, days before and after a national rail strike in the Netherlands. Our aim was to compare anticipated and actual behavioural reactions to the rail strike, investigate associations with traveller and trip characteristics, and perceived behavioural control and satisfaction with the chosen alternative. Forty-four percent of the people who had anticipated to travel by train on the day of the strike abandoned their trip, 24% switched to car as driver, 14% switched to another mode (as passenger), 18% stayed with the train and rescheduled the planned activity to another day. Almost half of people who had anticipated travelling by car expected to change behaviour as well. Multinomial logistic regression showed low preference for car among rail users. Considerable marginal effects were found for several variables, e.g.: young people and females were less likely to switch to car; short and middle distance trips were less likely abandoned or switched to another day; commute and business trips were more likely done by car, and business trips less likely cancelled. Despite high levels of perceived behavioural control and satisfaction with the chosen alternative, permanent modal shift as result of this strike is not expected.     

Using structural equations modeling to unravel the influence of land use patterns on travel behavior of workers in Montreal

This paper addresses the relations between travel behavior and land use patterns using a Structural Equations Modeling (SEM) framework. The proposed model structure draws on two earlier models developed for Lisbon and Seattle which show significant effects of land use patterns on travel behavior. The travel behavior variables included here are multifaceted including commuting distance, car ownership, the amount of mobility by mode (car, transit and non-motorized modes), both in terms of total kilometers travelled and number of trips. The model also includes a travel scheduling variable, which is the total time spent between the first and last trips to reflect daily constraints in time allocation and travel.The modeled land use variables measure the levels of urban concentration and density, diversity, both in terms of types of uses and the mix between jobs and inhabitants/residents, the transport supply levels, transit and road infrastructure, and accessibility indicators. The land use patterns are described both at the residence and employment zones of each individual included in the model by using a factor analysis technique as a data reduction and multicollinearity elimination technique. In order to explicitly account for self selection bias the land use variables are explicitly modeled as functions of socioeconomic attributes of individuals and their households.The results obtained show that people with different socioeconomic characteristics tend to work and live in places of substantially different urban environments. But besides these socioeconomic self-selection effects, land use variables significantly affect travel behavior. More precisely the effects of land use are in great part passed thru variables describing long term decisions like commuting distance, and car ownership. These results point to similar conclusions from the models developed for Lisbon and Seattle and thus give weight to the use of land use policies as tools for changing travel behavior.     

Volatility of car ownership, commuting mode and time in the UK

This paper has two objectives: to examine the volatility of travel behaviour over time and consider the factors explaining this volatility; and to estimate the factors determining car ownership and commuting by car. The analysis is based on observations of individuals and households over a period of up to 11 years obtained from the British Household Panel Survey (BHPS). Changes in car ownership, commuting mode and commuting time over a period of years for the same individuals/households are examined to determine the extent to which these change from year-to-year. This volatility of individual behaviour is a measure of the ease of change or adaptation. If behaviour changes easily, policy measures are likely to have a stronger and more rapid effect than if there is more resistance to change. The changes are “explained” in terms of factors such as moving house, changing job and employment status. The factors determining car ownership and commuting by car are analysed using a dynamic panel-data models.     

The bicycle as a feedering mode: experiences from three European countries

Bike-and-ride, or the combined use of bicycle and public transport for one trip, is a multimodal alternative for the car. This paper discusses the use of bike-and-ride in three countries with widely differing bicycle cultures and infrastructures: the Netherlands, Germany and the UK. The share of the bicycle in access trips is comparable to general levels of bicycle ridership in each country, but only for train services and other fast modes of public transport. Strong similarities are found in the characteristics of bike-and-ride trips and users, in terms of travel distances, travel motives, and the impact of car availability. The majority of bike-and-ride users travels between 2 and 5 km to a public transport stop, with longer access distances reported for faster modes of public transport. Work and education are the main travel motives, with the first dominating the faster modes and the second the slower modes of public transport. Car availability hardly influences the choice for a combined use of bicycle and train, but strongly affects the levels of bike-and-ride for slower modes of transport.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Modal shift implications of e-bike use in the Netherlands: Moving towards sustainability?

This paper investigates the modal shift patterns of e-bike users in the Dutch context. We focus on the change in e-bikers’ travel behavior to assess whether this change benefits sustainability. Our study provides direct ecologically valid evidence on modal shift by using a longitudinal dataset from the Netherlands Mobility Panel survey. We examine e-bikers’ modal shift patterns before and after acquiring an e-bike. The findings indicate that after e-bike adoptions, conventional bike use reduces significantly, while car use reduces less strongly. Nonetheless, the share of car kilometers is much larger than that of conventional bikes at the baseline. Besides, the emission rate per passenger kilometer of an e-bike is several times lower than that of a car. These imply a net environmental gain after e-bike adoptions. The present study also sheds light on modal shifts at a disaggregated level by investigating those e-bikers who are more likely to drive less after e-bike adoption. The findings suggest that e-bikers younger than 50 and those around retirement age (60–69) seem more likely to step out of their cars. Additionally, people living in rural areas tend to be more likely to reduce their car use than their counterparts in highly urbanized areas. Based on our findings, we present policy recommendations for achieving a greener shift in mobility systems.     

Incorporating aggregate behavior in an individual’s discrete choice: An application to analyzing illegal bicycle parking behavior

Many types of travel behavior involve positive social interaction (conformity effect) and it sometimes induces undesirable results, such as chronic illegal bicycle parking and illegal car parking. In this study, the conformity effects among bicycle users in the choice problem of bicycle parking locations were modeled and estimated within a discrete choice framework. The proposed model combines discrete choice behavior of bicycle parking locations at an individual level (micro-level) with an average choice at an aggregate level (macro-level). The social equilibrium equation, which is derived from the individual-level choice model, entails multiple equilibria with regard to the choice proportion for each reference group of individuals. The model was econometrically identified by using the data collected in a survey conducted in Tokyo in 2001. The empirical results indicated that large variations in collective behavior occur across subgroups, which were defined by the stations the respondents visit often, since there was an intensive positive social interaction. Finally, the marginal frequency of police patrols required to drastically reduce the level of illegal bicycle parking was also calculated using the identified model.     

Moving between mobility cultures: what affects the travel behavior of new residents?

This paper analyzes the complex interdependencies between residential relocation and daily travel behavior by focusing on modal change. To help explain changes in daily travel patterns after a long distance move between cities the concept of urban mobility cultures is introduced. This comprehensive approach integrates objective and subjective elements of urban mobility, such as urban form and socio-economics on the one hand, and lifestyle orientations and mode preferences on the other, within one socio-technical framework. Empirically, the study is based on a survey conducted among people who recently moved between the German cities Bremen, Hamburg and the Ruhr area. Bivariate analyses and linear multiple regression models are applied to analyze changes in car, rail-based and bicycle travel. This is done by integrating variables that account for urban mobility cultures and controlling for urban form, residential preferences and socio-demographics. A central finding of this study is, that changes in the use of the car and rail-based travel are much more dependent on local scale, such as neighborhood type and residential preferences, whereas cycling is more affected by city-wide attributes, which we addressed as mobility culture elements.     

Commuting costs and the residential mobility of job changers

In traffic and transport research, attention is given to the relevance of location patterns of activities to moving behaviour, the inverse causality being mostly left out of account. This paper considers what influence (changes in) travel costs have on moving behaviour and residential choice. The analysis has been carried out for employed people who change jobs. The residential choice has been split into a marginal probability of moving and a conditional destination choice. Both choices appear to be influenced significantly by travel‐cost variables.     

The role of VMT reduction in meeting climate change policy goals

This article evaluates the case for vehicle miles traveled (VMT) reduction as a core policy goal for reducing greenhouse gases (GHGs), concluding the economic impacts and social consequences would be too severe given the modest potential environmental benefits. Attempts to reduce VMT typically rely on very blunt policy instruments, such as increasing urban densities, and run the risk of reducing mobility, reducing access to jobs, and narrowing the range of housing choice. VMT reduction, in fact, is an inherently blunt policy instrument because it relies almost exclusively on changing human behavior and settlement patterns to increase transit use and reduce automobile travel rather than directly target GHGs. It also uses long-term strategies with highly uncertain effects on GHGs based on current research. Not surprisingly, VMT reduction strategies often rank among the most costly and least efficient options. In contrast, less intrusive policy approaches such as improved fuel efficiency and traffic signal optimization are more likely to directly reduce GHGs than behavioral approaches such as increasing urban densities to promote higher public transit usage. As a general principle, policymakers should begin addressing policy concerns using the least intrusive and costly approaches first. Climate change policy should focus on directly targeting greenhouse gas emissions (e.g., through a carbon tax) rather than using the blunt instrument of VMT reduction to preserve the economic and social benefits of mobility in modern, service-based economies. Targeted responses are also more cost effective, implying that the social welfare costs of climate change policy will be smaller than using broad-brushed approaches that directly attempt to influence living patterns and travel behavior.     

The relation between bicycle commuting and non-work cycling: results from a mobility panel

This study aims to establish whether or not bicycle commuting and cycling for other purposes (e.g. shopping, visiting friends) are related over time. Using previously gathered panel data (the Dutch mobility panel) these relationships are revealed by (1) a series of conditional change models and (2) a latent transition model. The conditional change models indicate that, with a lag of 1 year and controlling for a range of background characteristics, bicycle commuting and non-work cycling (in number of weekly trips) have a positive reciprocal influence on each other. The models show that work-related factors, such as the distance to work or whether a person receives a travel allowance, affect not only bicycle commuting but also non-work cycling. The latent transition model indicates that people can be clustered into four groups: non-cyclists, non-work cyclists, all-around cyclists and commuter cyclists. This model shows that people with a consistent propensity to not cycle at all (non-cyclists) or to cycle for both work and non-work purposes (all-around cyclists) are most stable in their travel behavior. Non-work cyclists and commuter cyclists are less stable in travel behavior. The model also shows that all-around cyclists are not (significantly) affected by a change in the distance to work. The article concludes with several directions for future research.     

Bicycle in Shanghai: Movement patterns,cyclist attitudes and the impact of traffic separation

Transportation demand continues to grow at an even faster rate than the economies of Chinese cities, placing increasing pressure on a limited road network. In certain cities of the more highly developed coastal plains, the bicycle assumed a dominant role in urban transport in the 1980s, a position maintained in the 1990s. In Shanghai, the bicycle continues to play a dominant role, although policies favour a switch to public transport. In the present paper, cyclist attitudes toward public transport policies were probed with a pilot questionnaire at two important central destinations. An important example of current policies with regard to bicycles involves the creation of separate networks for motorized and non-motorized modes. A pilot scheme for eventual application over a very large area was recently introduced in the central area. We report on the traffic volumes by mode and street before and after its implementation in 1999. Both bicycle and car volumes diminished in the central area, although the decrease was greater for bicycles. On the other hand, interviewed cyclists expressed resistance to various incentives to use public transport. The question raised here is whether the planned increase in public transport share of total intracity travel can be achieved without disincentives to use the bicycle.     

Effects of increased awareness on choice of travel mode

This paper reports a field experiment with the purpose of studying the effects of increased awareness on travel mode choice. One hundred fifteen subjects were randomly assigned to an experimental and a control group. In the experimental group, a more deliberate choice of travel mode was induced and expected to result in a stronger relationship between attitude and behavior, a weaker relationship between habit and behavior, and a behavioral change among individuals with a strong habit. Attitude, habit, and behavior were measured in travel diaries and questionnaires. The results indicated no significant change in the relationship between attitude and behavior and no significant change in the relationship between habit and behavior. However, a temporally extended decrease in car use was observed in the experimental group. The effect was noted for individuals with a strong habit who reduced their car use but not for subjects with a weak habit.     

The value of time and external benefits in bicycle appraisal

We estimate the value of time savings, different cycling environments and additional benefits in cost-benefit analysis of cycling investments. Cyclists’ value of travel time savings turns out to be high, considerably higher than the value of time savings on alternative modes. Cyclists also value other improvements highly, such as separated bicycle lanes. As to additional benefits of cycling improvements in the form of health and reduced car traffic, our results do not support the notion that these will be a significant part in a cost-benefit analysis. Bicyclists seem to take health largely into account when making their travel choices, implying that it would be double-counting to add total health benefits to the analysis once the consumer surplus has been correctly calculated. As to reductions in car traffic, our results indicate that the cross-elasticity between car and cycle is low, and hence benefits from traffic reductions will be small. However, the valuations of improved cycling speeds and comfort are so high that it seems likely that improvements for cyclists are cost-effective compared to many other types of investments, without having to invoke second-order, indirect effects. In other words, our results suggest that bicycle should be viewed as a competitive mode of travel and not primarily as a means to achieve improved health or reduced car traffic.