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.

     

Changes in private car ownership associated with car sharing: gauging differences by residential location and car share typology

Transportation - While a large body of literature shows that car share encourages low car ownership, the evidence is rather limited in the context of different types of car share (fleet-based...     

Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto

Bike Share Toronto is Canada’s second largest public bike share system. It provides a unique case study as it is one of the few bike share programs located in a relatively cold North American setting, yet operates throughout the entire year. Using year-round historical trip data, this study analyzes the factors affecting Toronto’s bike share ridership. A comprehensive spatial analysis provides meaningful insights on the influences of socio-demographic attributes, land use and built environment, as well as different weather measures on bike share ridership. Empirical models also reveal significant effects of road network configuration (intersection density and spatial dispersion of stations) on bike sharing demands. The effect of bike infrastructure (bike lane, paths etc.) is also found to be crucial in increasing bike sharing demand. Temporal changes in bike share trip making behavior were also investigated using a multilevel framework. The study reveals a significant correlation between temperature, land use and bike share trip activity. The findings of the paper can be translated to guidelines with the aim of increasing bike share activity in urban centers.     

An analysis of trip length and land use patterns in the Greater Athens Area

The research described in this paper is an attempt to quantify the impact of a certain distribution of land uses upon trip characteristics — notably trip lengths. The idea is to relate trip lengths classified by mode and purpose to the distance of one trip end from the conurbation centre. The latter is defined as the point which represents a reasonable estimate of the place where the economic, administrative, and cultural life of the urban area is centered.By relating trip lengths to the distance of one trip end from the centre, one could obtain a relation which in effect would be a quantitative expression of the relation between transport and land use. The first application of this idea was in London using the 1966 journey to work data, and it gave quite satisfactory results.The area examined in this research is the Greater Athens Area. The method of analysis is similar to that followed in London so the results of the two studies can be compared. Only work trips are considered for four modes: car, bus, train and all modes (total). It is found that in the case of Athens too, when distance of the workplace from the centre is considered, trip lengths change in smoothly varying ways and a series of mathematical curves can be fitted to the data with an acceptable degree of accuracy. These curves are of the Gamma family having a constant spread factor and varying scale factors for each mode considered. When the distance of the residence end of the trip from the centre is considered, the trip length distributions are not very smooth, a clear mathematical curve cannot be fitted, but again a considerable degree of order can be detected. In addition to the above results a discussion is given on their meaning and the possibilities for future research. In fact the results so far are considered to be the first stage of a more extended research programme which will eventually connect trip length distributions to income and other economic or social parameters in an urban area.The author wishes to express his thanks and appreciation for the comments and constructive criticism made on the various drafts of this paper by M.J.M.     

Home-based trip end models — A comparison between category analysis and regression analysis procedures

The trip end models which have been used in past transportation studies are briefly summarised. Problems associated with the use of zone-based models are outlined and reasons are given to support the development of models at the household rather than zonal level.It is suggested that recent developments which have taken place in household-based models have not been entirely logical. In particular, arguments between regression models and category analysis models have been confused with the use of aggregate (zonal) as against disaggregate (household) data — regression models being associated with the use of zonal data and category analysis models with household data. Misunderstood arguments and false notions regarding sample sizes have directed attention from the regression analysis approach.A detailed comparison of the category analysis and regression analysis methods for developing household-based trip end models is given. Both methods have been applied using data from the Monmouthshire Land Use Transportation Study. The regression results reported are from a very preliminary analysis and contain a number of anomalies, although it is thought that sufficient work has been done to provide an objective evaluation of the two methods.It is recommended that the household regression approach should be further investigated since it has advantages as a modelbuilding procedure and makes better use of sample data. A certain amount of categorisation of household types is necessary and the investigations would attempt to determine the best balance between categorisation and regression fitting. Further development will be restricted if the trend towards minimum sample sizes of about 1000 households is continued. Larger samples should be taken in certain circumstances to pursue development work.     

Substitution of bus for car travel in urban Britain: an economic evaluation of bus and car exhaust emission and other costs

Car exhaust emissions cause serious air pollution problems in many regions and, at a global level, contribute to climate change. Car use is also an important factor in other problems including traffic congestion, road accidents, noise pollution, community severance, and loss of countryside from road building. Forecasts of further increases in car ownership and use have prompted calls for policy-makers to encourage car users to switch to other forms of transport, particularly the bus. The effects of substituting bus for car travel in urban areas are simulated by specifying a spreadsheet model incorporating two types of car (petrol and diesel engine) and three types of bus (mini-, midi- and large bus). Six types of exhaust emission are considered for each vehicle type for the years 1992, 1995 and 1999: carbon monoxide, volatile organic compounds, nitrogen oxides, sulphur dioxide, (small) particulate matter and carbon dioxide. The paper provides a synthesis of monetary estimates of these exhaust emission and other costs. The other costs considered are traffic congestion, fuel consumption, noise pollution, road accidents and road damage. The exhaust emission monetary cost estimates, mainly from the United States and the United Kingdom, are discussed within the context of a sensitivity analysis which allows for changes in parameters such as load factors, emission factors and the individual exhaust emission cost estimates. The simulation results show that substitution of bus for car travel generally decreases the overall costs, particularly the costs of congestion, but increases exhaust emission costs if bus load factors are insufficiently high. In order to reduce exhaust emission costs from car to bus transfer at given load factors, the most effective policy option is to encourage the reduction of particulate emissions from bus engines. In terms of the overall costs, increasing bus load factors by relatively modest amounts can lead to substantial reductions in these overall costs. These results should be regarded as illustrative rather than definitive, given the uncertainties in a number of parameter estimates and the need for further research in areas not covered by the paper.     

Analyzing car ownership in Quebec City: a comparison of traditional and latent class ordered and unordered models

Private car ownership plays a vital role in the daily travel decisions of individuals and households. The topic is of great interest to policy makers given the growing focus on global climate change, public health, and sustainable development issues. Not surprisingly, it is one of the most researched transportation topics. The extant literature on car ownership models considers the influence of exogenous variables to remain the same across the entire population. However, it is possible that the influence of exogenous variable effects might vary across the population. To accommodate this potential population heterogeneity in the context of car ownership, the current paper proposes the application of latent class versions of ordered (ordered logit) and unordered response (multinomial logit) models. The models are estimated using the data from Quebec City, Canada. The latent class models offer superior data fit compared to their traditional counterparts while clearly highlighting the presence of segmentation in the population. The validation exercise using the model estimation results further illustrates the strength of these models for examining car ownership decisions. Moreover, the latent class unordered response models perform slightly better than the latent class ordered response models for the metropolitan region examined.     

Modelling car availability,modal split and trip distribution by Monte-Carlo simulation: A short way to integrated models

The model used a Monte-Carlo algorithm to simulate modal split and trip distribution as an interconnected decision process at the individual level. Using census data, the individuals of a planning region are classified into situation groups, which represent significantly different decision situations with respect to socio-demographic position and territorial location. According to the theoretical framework, which emphasises mobility constraints instead of preferences, household structure and sex (time budget and car availability constraints) and work place characteristics (location constraints) are the key variables. For each situation group, decision profiles are empirically determined; these describe car availability, travel time constraints and work place distribution. Modal split and trip distribution are simulated as an interconnected individual decision process, which is stochastically determined by the location of the individual and the decision profile of his situation group.The algorithm is very sensitive and flexible and extremely well suited to electronic processing. An extended and modified version is currently being used in the preparation of regional transporation plans for several German city regions.     

Explaining public transport information use when a car is available: attitude theory empirically investigated

Despite recent investments in and growing availability of various public transport information services, levels of apparent non-use (of particular information services) across the population remain high. Policymakers and information service providers could benefit from a better understanding of factors affecting information use. The goal of this paper is to provide more insight into the (non-)use of public transport information by applying attitude theory. A postal survey was sent to a random sample of 10,000 households in Bristol and Manchester, UK. The response rate was 13%. Respondents were questioned about an uncertain journey they were going to make. Structural equation modelling has been used to investigate interdependencies among the factors studied. The results show that the desire to consult public transport information for an uncertain journey is affected by attitudes, subjective norms, and past behaviour. These social-psychological factors are in turn affected by constraints such as travel behaviour and trip context. Crucially in terms of addressing issues of non-use of information it is found that consulting information is influenced by propensity to consider using public transport rather than vice versa as has hitherto been implicitly assumed by many involved in the provision of transport and information services.     

Unraveling the relationship between trip chaining and mode choice: evidence from a multi-week travel diary

Abstract

Trip chaining (or tours) and mode choice are two critical factors influencing a variety of patterns of urban travel demand. This paper investigates the hierarchical relationship between these two sets of decisions including the influences of socio-demographic characteristics on them. It uses a 6-week travel diary collected in Thurgau, Switzerland, in 2003. The structural equation modeling technique is applied to identify the hierarchical relationship. Hierarchy and temporal consistency of the relationship is investigated separately for work versus non-work tours. It becomes clear that for work tours in weekdays, trip-chaining and mode choice decisions are simultaneous and remain consistent across the weeks. For non-work tours in weekdays, mode choice decisions precede trip-chaining decisions. However, for non-work tours in weekends, trip-chaining decisions precede mode choice decisions. A number of socioeconomic characteristics also play major roles in influencing the relationships. Results of the investigation challenge the traditional approach of modeling mode choice separately from activity-scheduling decisions.     

A dynamic model system of household car ownership,trip generation,and modal split: model development and simulation experiment

A dynamic model of household car ownership and mode use is developed and applied to demand forecasting. The model system consists of three interrelated components: car ownership, mechanized trip generation, and modal split. The level of household car ownership is represented as a function of household attributes and mobility measures from the preceding observation time point using an ordered-response probit model. The trip generation model predicts the weekly number of trips made by household members using car or public transit, and the modal split model predicts the fraction of trips that are made by public transit. Household car ownership is a major determinant in the latter two model components. A simulation experiment is conducted using sample households from the Dutch National Mobility Panel data set and applying the model system to predict household car ownership and mode use under different scenarios on future household income, employment, and drivers’ license holding. Policy implications of the simulation results are discussed.     

Steering short-term demand for car-sharing: a mode choice and policy impact analysis by trip distance

Transportation - Car-sharing could have substantial benefits. However, there is not enough evidence about if more people choosing car-sharing would reduce private car usage or public transport...     

The relationship between land use and intrazonal trip making behaviors: Evidence and implications

This paper addresses the relationship between land use, destination selection, and travel mode choice. Specifically, it focuses on intrazonal trips, a sub-category of trip making where both trip origin and trip destination are contained in the same geographic unit of analysis, using data from the 1994 Household Activity and Travel Diary Survey conducted by Portland Metro. Using multinomial logit and binary logistic models to measure travel mode choice and decision to internalize trips, the evidence supports the conclusions that (1) intrazonal trips characteristics suggest mode choice for these trips might be influenced by urban form, which in turn affects regional trip distribution; (2) there is a threshold effect in the ability of economic diversity/mixed use to alter travel behavior; and (3) greater emphasis to destinations within the area where an individual’s home is located needs to be given in trip distribution models.     

Modelling inter-urban transport flows in Italy: A comparison between neural network analysis and logit analysis

In the present paper a modal split problem is analysed by means of two competing statistical models, the traditional logit model and the new technique for information processing, viz. the feedforward neural network model. This study aims to explore the modal split between rail and road transport modes in Italy in relation to the introduction of a new technological innovation, the new High-Speed Train. The paper is sub-divided into two major parts. The first part offers some general considerations on the use of neural networks in the light of the increasing number of empirical applications in the specific area of transport economics. The second part describes the Italian case study by using the two above mentioned statistical models. The results highlights the fact that the two adopted models, although methodologically different, are both able to provide a reasonable spatial forecasting of the phenomenon studied. In particular, the neural network model turns out to have a slightly better performance, even though there are still critical problems inherent in its application.     

Effects of land-use transport scenarios on travel patterns: a multi-state supernetwork application

Understanding travellers’ response is essential to address policy questions arising from spatial and transport planning sectors. This paper demonstrates the usefulness of the multi-state supernetwork approach to investigate the effects of land-use transport scenarios on individuals’ travel patterns. In particular, it illustrates that multi-state supernetworks are capable of representing activity-travel patterns at a high level of detail, including the choice of mode, route, parking and activity location. Multi-faceted activity-travel preferences can be accommodated in supernetworks. Using a micro-simulation approach, the adaptation of individuals’ travel patterns to policies can be readily captured. The illustration concerns hypothetical land-use and transport scenarios for the city of Rotterdam (The Netherlands), focusing on accessibility changes, modal substitution and shift in the use of transport and location facilities.     

Household-level commuting mode choices,car allocation and car ownership level choices of two-worker households: the case of the city of Toronto

The paper presents a comprehensive investigation on household level commuting mode, car allocation and car ownership level choices of two-worker households in the City of Toronto. A joint econometric model and a household travel survey dataset are used for empirical investigations. Empirical models reveal that significant substitution patterns exist between auto driving and all other mode choices in two-worker households. It is revealed that, female commuters do not prefer auto driving, but in case of a one car (and two commuters with driving licenses) household, a female commuter gets more preference for auto driving option than the male commuter. Reverse commuting (commuting in opposite direction of home to central business district) plays a critical role on household level car allocation choices and in defining the stability of commuting behaviour of two-worker households. Two worker households in higher income zones and with longer commuting distances tend to have higher car ownership levels than others. However, higher transit accessibility to jobs reduces household car ownership levels. The study reveals that both increasing two worker households and reverse commuting would increase dependency on private car for commuting.     

Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC

This study analyzes the potential benefits and drawbacks of taxi sharing using agent-based modeling. New York City (NYC) taxis are examined as a case study to evaluate the advantages and disadvantages of ride sharing using both traditional taxis (with shifts) and shared autonomous taxis. Compared to existing studies analyzing ride sharing using NYC taxi data, our contributions are that (1) we proposed a model that incorporates individual heterogeneous preferences; (2) we compared traditional taxis to autonomous taxis; and (3) we examined the spatial change of service coverage due to ride sharing. Our results show that switching from traditional taxis to shared autonomous taxis can potentially reduce the fleet size by 59% while maintaining the service level and without significant increase in wait time for the riders. The benefit of ride sharing is significant with increased occupancy rate (from 1.2 to 3), decreased total travel distance (up to 55%), and reduced carbon emissions (up to 866 metric tonnes per day). Dynamic ride sharing, wich allows shared trips to be formed among many groups of riders, up to the taxi capacity, increases system flexibility. Constraining the sharing to be only between two groups limits the sharing participation to be at the 50–75% level. However, the reduced fleet from ride sharing and autonomous driving may cause taxis to focus on areas of higher demands and lower the service levels in the suburban regions of the city.     

Pathways for GHG emission reduction in Norwegian road transport sector: Perspective on consumption of passenger car transport and electricity mix

Electrification of the transport sector is considered as a solution to reduce greenhouse gases (GHGs) emissions and achieve sustainable mobility. Specifically in the case of electrification of passenger vehicles, various industrial and policy initiatives have been introduced. In this article, we present and assess three approaches – pro-technology, pro-simplicity and mix (of the aforementioned approaches) – to achieve target emission reductions in the Norwegian road transport sector. We also assess the influence of including ‘Guarantee of Origin’ certification for the electricity production in accounting for typical consumption electricity mix in Norway.Results show that for the same reductions in tail-pipe GHG emissions, pro-technology, pro-simplicity, and the mix scenario offer 22%, 29% and 28% reduction in the life cycle GHG emissions respectively, compared to the reference scenario in year 2020. However, the pro-simplicity scenario requires 25% reduction in vehicle-km driven compared to the pro-technology scenario, which provides the same passenger car mobility as in the reference case. When the GHG intensity of the electricity mix used to power EVs is corrected to account for actual consumption mix in Norway, a 13% reduction in the net GHG benefit of pro-technology scenario is observed.     

Changes in level of household car ownership: the role of life events and spatial context

Recent longitudinal studies of household car ownership have examined factors associated with increases and decreases in car ownership level. The contribution of this panel data analysis is to identify the predictors of different types of car ownership level change (zero to one car, one to two cars and vice versa) and demonstrate that these are quite different in nature. The study develops a large scale data set (n = 19,334), drawing on the first two waves (2009–2011) of the UK Household Longitudinal Study (UKHLS). This has enabled the generation of a comprehensive set of life event and spatial context variables. Changes to composition of households (people arriving and leaving) and to driving licence availability are the strongest predictors of car ownership level changes, followed by employment status and income changes. Households were found to be more likely to relinquish cars in association with an income reduction than they were to acquire cars in association with an income gain. This may be attributed to the economic recession of the time. The effect of having children differs according to car ownership state with it increasing the probability of acquiring a car for non-car owners and increasing the probability of relinquishing a car for two car owners. Sensitivity to spatial context is demonstrated by poorer access to public transport predicting higher probability of a non-car owning household acquiring a car and lower probability of a one-car owning household relinquishing a car. While previous panel studies have had to rely on comparatively small samples, the large scale nature of the UKHLS has provided robust and comprehensive evidence of the factors that determine different car ownership level changes.     

Investigating commute satisfaction differences of private car users and public transport users in a developing country context

Transportation - The objective of this paper is to investigate commute satisfaction differences across car users and public transport (PT) users in a developing country context. Using survey data...