Travel patterns in Dutch metropolitan cities: The importance of external trips

Using a variety of data sources, decentralisation of population and employment in four Dutch urban areas (Amsterdam, Rotterdam, The Hague and Utrecht) over the last 20 years, is analysed. It is found that suburbanisation, plus an ever growing car share, has increased the number of external journeys related to the metropolitan cities enormously. With the use of the 1982 National Travel Survey, current travel patterns in and around the metropolitan cities are studied: the importance of external trips for urban transport planning shows clearly. They account for about half the number of city related car trips, and for nearly three quarters of the total vehicle kilometres of travel within the city.(requests for reprints)     

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.     

Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.     

A modeling approach for matching ridesharing trips within macroscopic travel demand models

State of the art travel demand models for urban areas typically distinguish four or five main modes: walking, cycling, public transport and car. The mode car can be further split into car-driver and car-passenger. As the importance of ridesharing may increase in the coming years, ridesharing should be addressed as an additional sub or main mode in travel demand modeling. This requires an algorithm for matching the trips of suppliers (typically car drivers) and demanders (travelers of non-car modes). The paper presents a matching algorithm, which can be integrated in existing travel demand models. The algorithm works likewise with integer demand, which is typical for agent-based microscopic models, and with non-integer demand occurring in travel demand matrices of a macroscopic model. The algorithm compares two path sets of suppliers and demanders. The representation of a path in the road network is reduced from a sequence of links to a sequence of zones. The zones act as a buffer along the path, where demanders can be picked up. The travel demand model of the Stuttgart Region serves as an application example. The study estimates that the entire travel demand of all motorized modes in the Stuttgart Region could be transported by 7% of the current car fleet with 65% of the current vehicle distance traveled, if all travelers were willing to either use ridesharing vehicles with 6 seats or traditional rail.     

Comparing French carpoolers and non-carpoolers: Which factors contribute the most to carpooling?

Carpooling is an effective solution to major environmental problems but it is insufficiently used, particularly in France. In order to increase carpooling, it is important to understand why people do or not carpool. This study, carried out a large sample of drivers, was aimed at (1) identifying whether or not people carpool, (2) investigating the factual data (e.g. socio-demographics, transportation accessibility) and motivational factors (e.g. attitudes regarding car use, public transportation, environment) upon which carpoolers and non-carpoolers differ, and (3) highlighting the main determinants of the practice of carpooling. An online survey was administered to 1207 French drivers (48% men, ages 19–87) recruited by means of a random-quota method. In our sample, 52.5% of the participants said they were using carpooling. Carpoolers and non-carpoolers were similar in terms of kilometers driven per year, distance to their workplace or schools/universities, and public transportation accessibility. Compared to non-carpoolers, carpoolers were more likely to be women, have children, have positive attitudes toward public transport, and be more environmentally aware. These results suggest various different strategies for increasing the number of carpoolers and the frequency of carpooling use by taking into account the gender of road users.     

Transport Demand Management in Turkey: A Genetic Algorithm Approach

Abstract

This article proposes new models for estimating transport demand using a genetic algorithm (GA) approach. Based on population, gross national product and number of vehicles, four forms of the genetic algorithm transport planning (GATP) model are developed – one exponential and the others taking quadratic forms – and applied to Turkey. The best fit models in terms of minimum total average relative errors in the test period are selected for future estimation. Demand management strategies are proposed based on three scenarios: restricting private car use, restricting truck use and the simultaneous management of private car use and goods movement. Results show that the GATP model may be used to estimate transport demand in terms of passenger-kilometers traveled (pass-km), vehicle-kilometers traveled (veh-km) and ton-kilometers completed (ton-km). Results also show that the third scenario – simultaneous restrictions on private car use and goods movement – could reduce total veh-km by about 35% by 2025 in this study of Turkish rural roads.     

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.     

How does environmental concern influence mode choice habits? A mediation analysis

Starting from the intuition that people with high environmental concern have a better perception of public transport and therefore a better perception of the utility of public transport, we construct a theoretical model in which the effect of environmental concern on mode choice habits is mediated by the indirect utility of travel. Travel procures the direct utility of providing access to activities, but it also offers an indirect utility that is inherently personal and perceptual. We approach the indirect utility of public transport by measuring perceptions of time and feelings. The indirect utility of the car is approached by measuring affective and symbolic motives. Taking into account car use habits and habits of public transport use, the results show that people who have a high environmental concern perceive public transport use as easier, more useful and more pleasurable than people who do not have that environmental motivation. Such positive attitudes foster public transport use. Conversely, low environmental concern generates non-instrumental motives for car use, such as affective and symbolic motives. However, the relationship between affective and symbolic motives and car use habits is not robust. We can conclude that environmental concern influences mode choice habits and that the effect is partially mediated by perceptions and feelings towards public transport but not significantly by affective and symbolic motives for car use.     

Car ownership,travel and land use: a comparison of the US and Great Britain

This paper conducts an international comparative analysis of relationships between car ownership, daily travel and urban form. Using travel diary data for the US and Great Britain, we estimate models of car ownership and daily travel distance. Both a structural model with daily travel conditional upon car ownership and a reduced form model for daily travel, excluding car ownership, are estimated. Model results are similar, and show that differences in travel are explained by (1) differences in demographics between the two countries; (2) lower household income in Great Britain; (3) country specific differences in costs of car ownership and use, transport supply and other factors we have not been able to control. We find that metropolitan size affects travel only in the largest metropolitan areas of the US. Daily travel distance is inversely related to local population density, but the effect is much stronger for the US than Great Britain. We conclude that higher transport costs in Great Britain promote economizing behavior, which in turns leads to more consumption of local goods and services and more use of alternative transport modes.     

Could you also have made this trip by another mode? An investigation of perceived travel possibilities of car and train travellers on the main travel corridors to the city of Amsterdam,The Netherlands

We investigated perceived travel possibilities (or subjective choice-sets, consideration-sets) of car and train travellers on the main corridors to the city of Amsterdam, The Netherlands, and associations with traveller and trip characteristics. We conducted secondary analysis on a survey sample consisting of 7950 train and 19,232 car travellers. Forty-five percent of train travellers had a car in their objective choice-set, 27% of them would however never use it for this trip. Trip destination city centre, trip purpose, paying for the trip, public transport commitment, traffic congestion and parking problems were associated with consideration of car as alternative. Forty-two percent of car travellers had public transport in their subjective choice-set. The ratio between perceived public transport and objective car travel time stood out as determinant of consideration-sets, next to destination city centre, trip purpose, travel time and private versus company car ownership. On average, car travellers’ perceptions of public transport travel time exceeded objective values by 46%. We estimated that if perceptions would be more accurate, two out of three car travellers that currently do not see public transport as an alternative would include it in their choice-set, and use it from time to time. This effect has strong theoretical and policy implications.     

Measuring inaccuracy in travel demand forecasting: methodological considerations regarding ramp up and sampling

Project promoters, forecasters, and managers sometimes object to two things in measuring inaccuracy in travel demand forecasting: (1) using the forecast made at the time of making the decision to build as the basis for measuring inaccuracy and (2) using traffic during the first year of operations as the basis for measurement. This paper presents the case against both objections. First, if one is interested in learning whether decisions about building transport infrastructure are based on reliable information, then it is exactly the traffic forecasted at the time of making the decision to build that is of interest. Second, although ideally studies should take into account so-called demand “ramp up” over a period of years, the empirical evidence and practical considerations do not support this ideal requirement, at least not for large-N studies. Finally, the paper argues that large samples of inaccuracy in travel demand forecasts are likely to be conservatively biased, i.e., accuracy in travel demand forecasts estimated from such samples would likely be higher than accuracy in travel demand forecasts in the project population. This bias must be taken into account when interpreting the results from statistical analyses of inaccuracy in travel demand forecasting.     

Modelling car ownership in Great Britain

Over the last 50 years there has been a tenfold increase in the number of cars in Great Britain, rising from 2.6 million vehicles in 1951 to 27 million vehicles in 2001. Over the same period there has been a steady reduction in the proportion of households without access to a car and a steady increase in the proportion of households with two or more cars. If such trends continue, it is likely that there will be increased energy consumption, increased problems with traffic congestion and atmospheric pollution, and reductions to the financial viability of public transport. Given the importance of car ownership to transport and land-use planning and its relationship with energy consumption, the environment and health, it is the objective of this research to develop econometric models of household car ownership and apply the models to generate forecasts across Britain to the year 2031. To achieve this objective, the research develops discrete choice models of the household’s decision to own zero, one, two or three or more vehicles as a function of market saturation, licence holding, household income and structure, household employment, company car provision, and purchase and use costs. The models are validated to data from the 2001 Census and are used to develop a range of forecasts taking into account changes to the socio-demographic characteristics of Britain.     

Identifying variations and co-variations in discrete choice models

This study introduces an extended version of a standard multilevel cross-classified logit model which takes co-variations into account, i.e., variations jointly caused by two or more unobserved factors. Whilst focusing on mode choice behavior, this study deals with four different types of variation: spatial variations, inter-individual variations, intra-individual variations and co-variations between inter-individual and spatial variations. Such co-variations represent individual-specific spatial effects, reflecting different responses to the same space among individuals, which may for example be due to differences in their spatial perceptions. In our empirical analysis, we use data from Mobidrive (a continuous six-week travel survey) to clarify the existence of co-variation effects by comparing two models with and without co-variation terms. The results of this analysis indicate that co-variations certainly exist, especially for utility differences in bicycle and public transport use in comparison with car use. We then sequentially introduce four further sets of explanatory variables, examine the sources of behavioral variations and determine what types of influential factors are dominant in mode choice behavior.     

Modelling the impact of rail fare increases

Rail fares in South-East England have been increasing in real terms for several years, and are expected to continue to do so. In this paper, the impact of such increases is examined in terms of the choices of mode of travel, home and job location, and residential migration. Forecasts are made using a model in which the population is partitioned into four sets according to whether they have changed home and/ or job over the forecast period. The model allocates population to homes and workers to jobs, and commuters to the three modes of travel considered. The impact of an increase of 25% in real fares over a five-year period is examined and a number of conclusions are drawn. The model shows that rail patronage will decline even if transport costs remain constant in real terms, because of decentralisation of jobs and rising car ownership. The overall long-term rail fare elasticity is found to be –0.7, but this is the mean of a wide range of values for different parts of the study area. People ceasing to commute by rail would divide almost equally between car and bus, the latter being used particularly to Central London. Those people who commute to London who are seeking new homes would tend to choose to live nearer London than they would have otherwise. The paper concludes with a discussion of the findings in terms of the assumptions implied in the model.     

Integrated Agent-based and System Dynamics Modelling for Simulation of Sustainable Mobility

In this article, a conceptual framework for a comprehensive evaluation of the diffusion process of alternative fuel vehicles is introduced. The framework takes into account the most influencing stakeholders, including car manufacturers, car dealers, consumers, energy supply system, fuel stations and government. The underlying mathematical models of different stakeholders are then integrated in one model of the whole energy and transport system. The hybrid modelling framework links the two powerful dynamic simulation approaches of system dynamics (SD) and agent-based (AB) modelling. Integrated modelling structure gives the potential of building more accurate and computationally efficient models for simulating the transition to sustainable mobility. We specify the integration process and the most important linking variables between various energy and transport components. Then the application of the integrated model is explained through a test case and, finally, the applicability of the hybrid AB and SD approach and its potential contribution to the models of transition to sustainable mobility will be concluded.     

Towards a more equitable distribution of resources: Using activity-based models and subjective well-being measures in transport project evaluation

In this paper, we develop an innovative and comprehensive transport evaluation criterion to better account for equity considerations in transport project evaluation. This work explores transportation benefits from the consumer’s perspective to accessibility as a key benefit generated by any transportation project. To assess the full benefits of transportation project implementation for various consumers and calculate the improvement in accessibility, it is best to use Activity-Based Models (ABM). ABMs have two important advantages for equity analysis, which have not been utilized in the literature so far: first, ability to analyze results by various groups of the population; second, these models can utilize the Activity Based Accessibility (ABA) measure to estimate the overall benefits from transport investments and policies. The ABA measure allows one person to have different accessibilities for different choice situations, depending on his/her characteristics. We suggest including social and spatial factors in social welfare assessment by introducing the concept of accessibility gains to key social activities. Specifically, it is suggested to incorporate subjective well-being consideration into a new evaluation framework “Equity Benefit Analysis” (EBA). we use an alternative measure, “Subjective Value of Accessibility gains” (SVOA), which is based on the ABM accessibility measure as well as on Subjective Well-Being (SWB) measure, as the key benefit taken into account in the evaluation process. The SVOA is not intended to replace the current practice of analyzing equity by comparing various impacts on different groups of the population, but can aid by providing policymakers with a single measure advancing both equity and efficiency considerations and facilitating comparison among alternatives. Initial case study results indicate the SVOA can show higher benefits to policies focusing on the needs of vulnerable social groups that compared traditional measures.     

Establishing car sharing services in rural areas: a simulation-based fleet operations analysis

Today, car sharing represents a generally accepted and widespread mode of individual transport. Car sharing providers operate their fleets effectively in many cities around the world. Surprisingly, rural areas don’t seem to have been considered in provider’s current expansion strategies. However, studies suggest that car sharing would have the greatest impact on improving sustainability and reducing traffic if it were offered nationwide. In this paper, we analyze the factors that prevent car sharing enterprises from developing their services in rural regions. Supported by a simulation model, we elaborate strategic implications on how to deal with potential hindrances such as lower demand or longer driving distances. For this purpose, a symbiosis of urban and rural car sharing services was analyzed. Our findings indicate a certain feasibility of rural car sharing development, while highlighting the positive effect it could have on car sharing demand in urban areas.

     

Why has car-fleet specific fuel consumption not shown any decrease since 1990? Quantitative analysis of Dutch passenger car-fleet specific fuel consumption

The Dutch car-fleet specific fuel consumption has not shown any decrease since 1990. The main reasons for the car-fleet specific fuel consumption no longer showing a decrease after 1990, namely, increases in vehicle weight and cylinder capacity, have been concluded from an analysis of Dutch car-fleet specific fuel consumption in the period 1980–1997. The increase in weight of the average sales-weighted new car in this period can be almost completely explained by the increase in weight of successive models (upgrading). This upgrading is partly the result of competition between car manufacturers but is also due to stricter safety requirements. However, because upgrading has been fairly extreme, the 1981 model of a car type often belonged to a different car type than the 1997 model of the same type. Upgrading is therefore a consequence, not only of the competition among car manufacturers and stricter safety requirements, but probably also of the shift in consumer demand for more expensive, larger and heavier cars. The 1998 agreement with the European car manufacturers (ACEA) and the Dutch CO₂ differentiation in car purchase taxes will probably lead to a further decrease in specific fuel consumption in the European fuel test-cycle (Eurotest) in the near future. However, real-world specific fuel consumption will decrease less because the difference between specific fuel consumption measured in the Eurotest and real-world specific fuel consumption is expected to increase as a result of the increasing use of both air conditioners and direct-injection gasoline engines.     

Comparison of car ownership models

Car ownership models found in the academic literature (with a focus on the recent literature and on models developed for transport planning) are classified into a number of model types. The different model types are compared on a number of criteria: inclusion of demand and supply side of the car market, level of aggregation, dynamic or static model, long‐ or short‐run forecasts, theoretical background, inclusion of car use, data requirements, treatment of business cars, car‐type segmentation, inclusion of income, of fixed and/or variable car cost, of car quality aspects, of licence holding, of sociodemographic variables and of attitudinal variables, and treatment of scrappage.     

Institutional constraints on transport policymaking: the case of company cars in Israel

Transportation analysis emphasizes the necessity to internalize the transport externalities of car usage through taxation. Yet taxation decisions are often made with non-transport goals in mind. In such cases, transport policies are made ‘by the way.’ This paper examines such a case: Israel’s taxation policy on company cars. It shows that current taxation policies result in increasing numbers of company cars and growing numbers of transport users who are not sensitive to the marginal cost of car use and make excessive use of the car. As a result, a significant portion of Travel Demand Management (TDM) measures cannot affect this group. The Israeli case of company car tax reform demonstrates the problematic effect of a policy that does not take its overall consequences on other policy fields into account and thereby impairs efforts to reduce the negative impacts of the transport system. Also, it demonstrates the importance of institutional aspects of transport policymaking.