Trip chain complexity: a comparison among latent classes of daily mobility patterns

This paper studies the relationship between trip chain complexity and daily travel behaviour of travellers. While trip chain complexity is conventionally investigated between travel modes, our scope is the more aggregated level of a person’s activity-travel pattern. Using data from the Netherlands Mobility Panel, a latent class cluster analysis was performed to group people with similar mode choice behaviour in distinct mobility pattern classes. All trip chains were assigned to both a travel mode and the mobility pattern class of the traveller. Subsequently, differences in trip chain complexity distributions were analysed between travel modes and between mobility pattern classes. Results indicate considerable differences between travel modes, particularly between multimodal and unimodal trip chains, but also between the unimodal travel modes car, bicycle, walking and public transport trip chains. No substantial differences in trip chain complexity were found between mobility pattern classes. Independently of the included travel modes, the distributions of trip chain complexity degrees were similar across mobility pattern classes. This means that personal circumstances such as the number of working hours or household members are not systematically translated into specific mobility patterns.

     

Car ownership and attitudes towards transport modes for shopping purposes in Singapore

The heightening of issues, such as sustainable development and environmental pollution have resulted in many governments pursuing transport policies which aim to promote the use of public transport modes, including walking, as well as discourage the use of the car for various activities, such as shopping, work, recreation, etc. However, little has been done on understanding shoppers' perceptions of transport modes for shopping purposes. Particularly, not much research has been done on examining the attitudes of car owners and non-car owners towards transport modes for shopping purposes. Using Singapore as a study area, this study has attempted to analyse car owners and non-car owners' perceptions of the different types of transport modes (i.e., car, taxi, bus, mass rapid transit and walk) in their shopping trips. The research found that each transport mode has its own unique set of attributes. In addition, car owners and non-car owners portray different attitudes towards the public transport modes and the car. This calls for different strategies for these two groups of shoppers in encouraging them to use the public transport modes and restrain the use of the car.     

Understanding urban mobility patterns from a spatiotemporal perspective: daily ridership profiles of metro stations

Transportation - Smart card data derived from automatic fare collection (AFC) systems of public transit enable us to study resident movement from a macro perspective. The rhythms of traffic...     

Learning daily activity patterns with probabilistic grammars

Daily activity pattern is the reflection and abstraction of actual individual activity participation on daily basis. It carries information on activity type, frequency and sequence. Preference of daily activity patterns varies among population, and thus can be interpreted as personal life styles. This paper advances studies on human daily activity patterns by providing new perspective and methodology in the modeling and learning of daily activity patterns using probabilistic context-free grammars. In this paper, similarities between daily activity pattern—which is defined as activity sequence—and language are explored. We developed context-free grammars to parse and generate daily activity patterns. To replicate people’s heterogeneity in selecting daily activity patterns, we introduced probabilistic context-free grammars and proposed several formulations to estimate the probability of a context-free grammar with daily activity patterns observed in household travel survey. We conducted experiments on the proposed formulations, finding that under proper context-free grammar and problem formulation, the estimated probabilistic context-free grammar is able to reproduce the observed pattern distribution in household travel survey with satisfactory precision. Practically, the proposed methodology sheds light on the issue of generating stochastic and accessibility-dependent choice sets for daily activity pattern models in certain activity-based modeling frameworks.     

Shifting towards environment-friendly modes: profiling travelers using Q-methodology

Due to a variety of reasons, the previous century is characterized by an extraordinary growth in car use that has continued into the current century. This has resulted in serious environmental repercussions. Despite technological advancements, the externalities remain an ecological threat that can not be discarded by policy makers. Therefore, it is essential that policy makers focus on reducing car use and on stimulating the shift towards more environment-friendly transport modes. In this study, Q-methodology is adopted as the technique to segment people, and to ascertain which approaches and determinants matter to medium distance travel. Segmentation is important, as policy measures will be more efficient and effective if they are fine-tuned on specific target groups. The analysis revealed that four discourses preponderate the paradigm of environmentally sustainable transport: travelers who use public transport as a dominant alternative, car-dependent travelers, travelers with a positive perception of using public transport, and travelers with a preference for car use. Concerning rational, economic motives, individuals evaluate travel time reliability as most important. To increase the reliability policy makers should consider the use of separate bus lanes and traffic light manipulation. In addition, public transport can be made even more attractive, when costs of cars are made more variable by road or congestion charging. When the s motives are discussed, the differences between the different groups of travelers were more pronounced. Next to increasing the benefits of using public transport, policy makers should also pay attention to removing psycho-social barriers.

The development of public attitudes towards the Stockholm congestion trial

A full-scale congestion charging trial was carried out in Stockholm the first months of 2006. Almost half of respondents in a county-wide survey stated that they changed their attitudes towards congestion charges during the trial. Most of them became more positive.An analysis of media shows that the attitudinal change in media towards the trial coincides with the attitudinal change of the public. There was no dramatic change in the proportion of articles expressing a negative view. Instead, the result indicates that the increase in positive views was driven by a shift from neutral to positive articles during the trial.In order to ascertain why the public attitudes swung, we have analysed the anticipated and perceived effects of the trial. Generally, the analysis seems to indicate that improved understanding of the type and magnitude of concrete effects was not a main driving force behind the attitudinal change. Instead, it seems that the public attitude changed because personal experience gave a new understanding of the implications of the charges for the personal well-being. This would imply that trials, generally, may be a more useful tool than information in the process of implementing ‘difficult’ policy measures, such as congestion charges.     

Understanding urban mobility patterns with a probabilistic tensor factorization framework

The rapid developments of ubiquitous mobile computing provide planners and researchers with new opportunities to understand and build smart cities by mining the massive spatial-temporal mobility data. However, given the increasing complexity and volume of the emerging mobility datasets, it also becomes challenging to build novel analytical framework that is capable of understanding the structural properties and critical features. In this paper, we introduce an analytical framework to deal with high-dimensional human mobility data. To this end, we formulate mobility data in a probabilistic setting and consider each record a multivariate observation sampled from an underlying distribution. In order to characterize this distribution, we use a multi-way probabilistic factorization model based on the concept of tensor decomposition and probabilistic latent semantic analysis (PLSA). The model provides us with a flexible approach to understand multi-way mobility involving higher-order interactions—which are difficult to characterize with conventional approaches—using simple latent structures. The model can be efficiently estimated using the expectation maximization (EM) algorithm. As a numerical example, this model is applied on a four-way dataset recording 14 million public transport journeys extracted from smart card transactions in Singapore. This framework can shed light on the modeling of urban structure by understanding mobility flows in both spatial and temporal dimensions.     

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.     

Micro-simulation of daily activity-travel patterns for travel demand forecasting

The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns. This revised version was published online in June 2006 with corrections to the Cover Date.     

Shared versus private mobility: Modeling public interest in autonomous vehicles accounting for latent attitudes

Emerging autonomous vehicles (AVs) and shared mobility systems per se will transform urban passenger transportation. Coupled together, shared AVs (SAVs) can facilitate widespread use of shared mobility services by providing flexible public travel modes comparable to private AV. Hence, it may be conjectured that future urban mobility is likely an on-demand service and AV private ownership is unappealing. Nonetheless, it is still unclear what observable and latent factors will drive public interest in (S)AVs, the answer to which will have important implications on transportation system performance. This paper aims to jointly model public interest in private AVs and multiple SAV configurations (carsharing, ridesourcing, ridesharing, and access/egress mode) in daily and commute travels with explicit treatment of the correlations across the (S)AV types. To this end, multivariate ordered outcome models with latent variables are employed, whereby latent attitudes and preferences describing traveler safety concern about AV, green travel pattern, and mobility-on-demand savviness are accounted for using structural and measurement equations. Drawing from a stated preference survey in the State of Washington, important insights are gained into the potential user groups based on the socio-economic, built environment, and daily/commute travel behavior attributes. Key policies are also offered to promote public interest in (S)AVs by scrutinizing the marginal effects of the latent variables.     

A cluster analysis of cyclists in Europe: common patterns,behaviours, and attitudes

Transportation - This study uses cluster analysis on a sample of regular cyclists from six European countries (the U.K., the Netherlands, Sweden, Hungary, Italy, and Spain) to shed light on common...     

National policy towards cars: the Netherlands

This paper describes the historical development of Dutch motorization after the Second World War and the policy of the Dutch Government towards the car. Developments are presented in a context of population growth and changes in population structure, in the economic situation, and in land use. Trends in the use of public transport and the bicycle are also highlighted. Special attention is given to the economic recession and the rise of unemployment since 1980.     

中国物流:走向供应链时代--美国物流发展趋势对中国物流的影响

进入21世纪,变革成为永恒的主题,变化的速度远远超过人们学习的速度.物流产业在科技进步和管理技术创新的驱动下,经历了从量变到质变的过程,全球物流已经进入供应链时代.     

The influence of individuals’ environmental attitudes and urban design features on their travel patterns in sustainable neighborhoods in the UK

This paper explores the influence of individuals’ environmental attitudes and urban design features on travel behavior, including mode choice. It uses data from residents of 13 new neighborhood UK developments designed to support sustainable travel. It is found that almost all respondents were concerned about environmental issues, but their views did not necessarily ‘match’ their travel behavior. Individuals’ environmental concerns only had a strong relationship with walking within and near their neighborhood, but not with cycling or public transport use. Residents’ car availability reduced public transport trips, walking and cycling. The influence of urban design features on travel behaviors was mixed, higher incidences of walking in denser, mixed and more permeable developments were not found and nor did residents own fewer cars than the population as a whole. Residents did, however, make more sustainable commuting trips than the population in general. Sustainable modes of travel were related to urban design features including secured bike storage, high connectivity of the neighborhoods to the nearby area, natural surveillance, high quality public realm and traffic calming. Likewise the provision of facilities within and nearby the development encouraged high levels of walking.     

Residential mobility and location choice: a nested logit model with sampling of alternatives

Residential mobility and relocation choice are essential parts of integrated transportation and land use models. These decision processes have been examined and modeled individually to a great extent but there remain gaps in the literature on the underlying behaviors that connect them. Households may partly base their decision to move from or stay at a current location on the price and quality of the available alternatives. Conversely, households that are on the market for a new location may evaluate housing choices relative to their previous residence. How and the degree to which these decisions relate to each other are, however, not completely understood. This research is intended to contribute to the body of empirical evidence that will help answer these questions. It is hypothesized that residential mobility and location choice are related household decisions that can be modeled together using a two-tier hierarchical structure. This paper presents a novel nested logit (NL) model with sampling of alternatives and a proposed procedure for sampling bias correction. The model was estimated using full-information maximum likelihood estimation methods. The results confirm the applicability of this NL model and support similar findings from other empirical studies in the residential mobility and location choice literature.     

National policy towards cars: the federal republic of Germany

Although much of the early technical development of the automobile occurred in Germany, the spread of car ownership within Germany was relatively slow up to 1933. Besides the general economic situation, this was due to the high costs of purchasing and running a car. With deliberate promotion of automobility by the national‐socialists after 1933, the pace of motorization proceeded more rapidly until the outbreak of World War II. Immediately after the war, motorization was slow to regain momentum but by the middle fifties, after the initial phase of post‐war reconstruction, the rapid build‐up of cars began again and has continued ever since. By 1986, the West German car fleet exceeded 27 million and 80% of motorized passenger kilometres were made by car.

This rapid post‐war growth was made possible by a liberal transport policy which reacted to growing car use by adaptation and provision of the necessary infrastructure. The adverse effects of vehicular traffic on the environment and on the urban quality of life moved policy at the end of the sixties towards stronger support for urban public transport and regulations for noise and exhaust emissions of automobiles. Also, the high toll of death and injuries from road accidents made improvement of road safety another important policy objective. So far, however, measures taken have fallen short of requiring changes in driver behaviour. Although there is widespread awareness of the environmental and accident costs of automobility, there is a reluctance to legislate (or for people voluntarily) to modify driving behaviour for social objectives.

This paper presents, briefly, the main instruments that have been applied in West Germany to achieve car‐related transport policy objectives, including the latest modifications in the tax system intended to foster the use of low‐emission vehicles. Possible future directions of policy towards the car, depending inter alia on changes in government, are also explored.     

Airport ground transportation management: moving towards the turn of the century

Over the last fifty years ground transportation management (GTM) has slowly evolved into a major function at most larger airports. However, during this time there has been relatively little written discussing the idea, organization structures or duties included within this functional activity. This paper reviews and updates the limited, earlier research. This study replicates initial work done in 1989 and thus provides a short longitudinal view of the airport GTM function. The final results demonstrate the current position of GTM and suggest trends for the future.     

The future mobility of the world population

On average a person spends 1.1 h per day traveling and devotes a predictable fraction of income to travel. We show that these time and money budgets are stable over space and time and can be used for projecting future levels of mobility and transport mode. The fixed travel money budget requires that mobility rises nearly in proportion with income. Covering greater distances within the same fixed travel time budget requires that travelers shift to faster modes of transport. The choice of future transport modes is also constrained by path dependence because transport infrastructures change only slowly. In addition, demand for low-speed public transport is partially determined by urban population densities and land-use characteristics. We present a model that incorporates these constraints, which we use for projecting traffic volume and the share of the major motorized modes of transport—automobiles, buses, trains and high speed transport (mainly aircraft)—for 11 regions and the world through 2050. We project that by 2050 the average world citizen will travel as many kilometers as the average West European in 1990. The average American's mobility will rise by a factor of 2.6 by 2050, to 58,000 km/year. The average Indian travels 6000 km/year by 2050, comparable with West European levels in the early 1970s. Today, world citizens move 23 billion km in total; by 2050 that figure grows to 105 billion.