Showing papers in "Transportation Research Part A-policy and Practice in 2012"
TL;DR: The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control, and traffic volumes, and appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka “bicycle boulevards”), and bridge facilities.
Abstract: To better understand bicyclists' preferences for facility types, global positioning system (GPS) units were used to observe the behavior of 164 cyclists in Portland, Oregon, USA for several days each. Trip purpose and several other trip-level variables recorded by the cyclists, and the resulting trips were coded to a highly detailed bicycle network. The authors used the 1449 non-exercise, utilitarian trips to estimate a bicycle route choice model. The model used a choice set generation algorithm based on multiple permutations of path attributes and was formulated to account for overlapping route alternatives. The findings suggest that cyclists are sensitive to the effects of distance, turn frequency, slope, intersection control (e.g. presence or absence of traffic signals), and traffic volumes. In addition, cyclists appear to place relatively high value on off-street bike paths, enhanced neighborhood bikeways with traffic calming features (aka "bicycle boulevards"), and bridge facilities. Bike lanes more or less exactly offset the negative effects of adjacent traffic, but were no more or less attractive than a basic low traffic volume street. Finally, route preferences differ between commute and other utilitarian trips; cyclists were more sensitive to distance and less sensitive to other infrastructure characteristics for commute trips.
547 citations
TL;DR: Results highlight potential barriers to the uptake of current-generation (2010) plug-in electric cars by mainstream consumers, including the prioritization of personal mobility needs over environmental benefits, concerns over the social desirability of electric vehicle use, and the expectation that rapid technological and infrastructural developments will make current models obsolete.
Abstract: Plug-in electric vehicles can potentially emit substantially lower CO2 emissions than internal combustion engine vehicles, and so have the potential to reduce transport emissions without curtailing personal car use. Assessing the potential uptake of these new categories of vehicles requires an understanding of likely consumer responses. Previous in-depth explorations of appraisals and evaluations of electric vehicles have tended to focus on ‘early adopters’, who may not represent mainstream consumers. This paper reports a qualitative analysis of responses to electric cars, based on semi-structured interviews conducted with 40 UK non-commercial drivers (20 males, 20 females; age 24–70 years) at the end of a seven-day period of using a battery electric car (20 participants) or a plug-in hybrid car (20 participants). Six core categories of response were identified: (1) cost minimisation; (2) vehicle confidence; (3) vehicle adaptation demands; (4) environmental beliefs; (5) impression management; and, underpinning all other categories, (6) the perception of electric cars generally as ‘work in progress’ products. Results highlight potential barriers to the uptake of current-generation (2010) plug-in electric cars by mainstream consumers. These include the prioritization of personal mobility needs over environmental benefits, concerns over the social desirability of electric vehicle use, and the expectation that rapid technological and infrastructural developments will make current models obsolete. Implications for the potential uptake of future electric vehicles are discussed.
533 citations
TL;DR: In this article, a systematic review of the current state of research in travel time reliability is presented, and a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.
Abstract: Travel time reliability is a fundamental factor in travel behavior. It represents the temporal uncertainty experienced by travelers in their movement between any two nodes in a network. The importance of the time reliability depends on the penalties incurred by the travelers. In road networks, travelers consider the existence of a trip travel time uncertainty in different choice situations (departure time, route, mode, and others). In this paper, a systematic review of the current state of research in travel time reliability, and more explicitly in the value of travel time reliability is presented. Moreover, a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.
288 citations
TL;DR: The study shows that the impacts of area-covering disruptions are largely determined by the level of internal, outbound and inbound travel demand of the affected area itself, and the vulnerability to spatially spread events shows a markedly different geographical distribution.
Abstract: Road network vulnerability analysis of area-covering disruptions: A grid-based approach with case study
240 citations
TL;DR: In this paper, a stated preference discrete choice experiment with 598 potential German car buyers was conducted to simulate a realistic future purchase situation, and seven vehicle types were incorporated in each of the six choice sets, i.e. hybrid, gas, biofuel, hydrogen, and electric vehicles besides common gasoline and diesel vehicles.
Abstract: With respect to the German goal of a transition to a lead market for electromobility within a short time period, this paper empirically examines the preferences for alternative energy sources or propulsion technologies in vehicles and particularly for electric vehicles. The data stem from a stated preference discrete choice experiment with 598 potential German car buyers. In order to simulate a realistic future purchase situation, seven vehicle types were incorporated in each of the six choice sets, i.e. hybrid, gas, biofuel, hydrogen, and electric vehicles besides common gasoline and diesel vehicles. The econometric analysis with flexible multinomial probit models reveals that potential car buyers in Germany currently have a low stated preference for electric, hydrogen, and hybrid vehicles. While our paper also discusses the impact of common vehicle attributes such as purchase price or service station availability, it particularly considers the effect of socio-demographic and environmental awareness variables. The estimation results reveal that younger potential car buyers have a higher stated preference for hydrogen and electric vehicles, males have a higher stated choice of hydrogen vehicles, and environmentally aware potential car buyers have a higher stated preference for hydrogen and electric vehicles. These results suggest that common policy instruments such as the promotion of research and development, taxation, or subsidization in the field of electromobility could be supplemented by strategies to increase the social acceptance of alternative vehicle types that are directly oriented to these population groups. Methodologically, our study highlights the importance of the inclusion of taste persistence across the choice sets and a high number of random draws in the Geweke–Hajivassiliou–Keane simulator in the simulated maximum likelihood estimation of the multinomial probit models.
239 citations
TL;DR: In this paper, the authors make a moral argument for what would be a fair distribution of these benefits, in which the maximum gap between the lowest and highest accessibility, both by mode and in space, should be limited, while attempting to maximize average access.
Abstract: Transportation improvements inevitably lead to an uneven distribution of user benefits, in space and by network type (private and public transport). This paper makes a moral argument for what would be a fair distribution of these benefits. The argument follows Walzer’s “Spheres of Justice” approach to define the benefits of transportation, access, as a sphere deserving a separate, non-market driven, distribution. That distribution, we propose, is one where the maximum gap between the lowest and highest accessibility, both by mode and in space, should be limited, while attempting to maximize average access. We then review transportation planning practice for a priori distributional goals and find little explicit guidance in conventional and even justice-oriented transportation planning and analyses. We end with a discussion of the implications for practice.
236 citations
TL;DR: Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system, but measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.
Abstract: Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks. In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.
190 citations
TL;DR: In this paper, the authors combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes, and demonstrate by case studies in Zurich urban road network, that the output of a agentbased simulator is consistent with the physics of traffic flow dynamics, as defined by a Macroscopic Fundamental Diagram.
Abstract: Pricing is considered an effective management policy to reduce traffic congestion in transportation networks. In this paper we combine a macroscopic model of traffic congestion in urban networks with an agent-based simulator to study congestion pricing schemes. The macroscopic model, which has been tested with real data in previous studies, represents an accurate and robust approach to model the dynamics of congestion. The agent-based simulator can reproduce the complexity of travel behavior in terms of travelers’ choices and heterogeneity. This integrated approach is superior to traditional pricing schemes. On one hand, traffic simulators (including car-following, lane-changing and route choice models) consider travel behavior, i.e. departure time choice, inelastic to the level of congestion. On the other hand, most congestion pricing models utilize supply models insensitive to demand fluctuations and non-stationary conditions. This is not consistent with the physics of traffic and the dynamics of congestion. Furthermore, works that integrate the above features in pricing models are assuming deterministic and homogeneous population characteristics. In this paper, we first demonstrate by case studies in Zurich urban road network, that the output of a agent-based simulator is consistent with the physics of traffic flow dynamics, as defined by a Macroscopic Fundamental Diagram (MFD). We then develop and apply a dynamic cordon-based congestion pricing scheme, in which tolls are controlled by an MFD. And we investigate the effectiveness of the proposed pricing scheme. Results show that by applying such a congestion pricing, (i) the savings of travel time at both aggregated and disaggregated level outweigh the costs of tolling, (ii) the congestion inside the cordon area is eased while no extra congestion is generated in the neighbor area outside the cordon, (iii) tolling has stronger impact on leisure-related activities than on work-related activities, as fewer agents who perform work-related activities changed their time plans. Future work can apply the same methodology to other network-based pricing schemes, such as area-based or distance-traveled-based pricing. Equity issues can be investigated more carefully, if provided with data such as income of agents. Value-of-time-dependent pricing schemes then can also be determined.
180 citations
TL;DR: In this paper, the authors studied university students' commute and housing behaviors using samples from Los Angeles, a place notorious for car dependence and dominance, and found that being embedded in this place does not make university students drive alone more than their peers in other places.
Abstract: This paper studies university students’ commute and housing behaviors using samples from Los Angeles, a place notorious for car dependence and dominance. It finds that being embedded in this place does not make university students drive alone more than their peers in other places. Being multimodal and having a discounted transit pass increase the odds of alternative modes while holding a parking permit reduces the odds of these modes. Commute distance is positively related to carpool and telecommuting. Gender, status (undergraduate vs. gradate) and age are significantly correlated to biking, walking or public transit. Students living alone are more likely to commute by driving alone than other students. Having friends and classmates living nearby increases the odds of taking public transit. Due to data constraints, this study cannot prove whether there is any correlation between information contagion and the effects of living alone and having friends and classmates living nearby on alternative mode choice. But it proposes that the issue be worthwhile of further investigations. Base on the above, the paper recommends a comprehensive travel demand management program, utilization of information contagion effects of students and promotion of multimodal commute to better promote alternative mode of commute among university students.
175 citations
TL;DR: In this paper, a longitudinal structural equations modelling (SEM) approach was used to assess the importance of neighbourhood characteristics on travel behavior as opposed to the attitude-induced residential self-selection.
Abstract: The objective of this study is to explore whether changes in neighbourhood characteristics bring about changes in travel choice. Residential self-selection is a concern in the connections between land-use and travel behaviour. The recent literature suggests that a longitudinal structural equations modelling (SEM) approach can be a powerful tool to assess the importance of neighbourhood characteristics on travel behaviour as opposed to the attitude-induced residential self-selection. However, the evidence to date is limited to particular geographical areas and evidence from one country might not be transferrable to another because of differences in land-use patterns and land-use policies. The paper is to address the gap by extending the evidence using British data. The case study is based on the metropolitan area of Tyne and Wear, North East of England, UK. A SEM is applied to 219 respondents who reported residential relocation. The results identify that neighbourhood characteristics do influence travel behaviour after controlling for self-selection. For instance, the more people are exposed to public transport access, the more likely they drive less. Neighbourhood characteristics also impact through their influence on car ownership. A social environment with vitality also reduces the amount of private car travel. These findings suggest that land-use policies at neighbourhood level can play an important role in reducing driving.
156 citations
TL;DR: In this article, the authors consider the socio-economic impacts of road network degradation and seek to determine the most critical locations in the network by comparing the levels of remoteness (or its inverse accessibility) of localities within the study region, on the basis of the impacts of degradation of the road network on a recognised accessibility/remoteness index that can be applied to each and every location within the region.
Abstract: This paper considers the development of a method for network vulnerability analysis which considers the socio-economic impacts of network degradation and seeks to determine the most critical locations in the network. The method compares the levels of remoteness (or its inverse, accessibility) of localities within the study region, on the basis of the impacts of degradation of the road network on a recognised accessibility/remoteness index that can be applied to each and every location within the region. It thus extends the earlier work on accessibility-based vulnerability analysis which was limited to assessment of impacts on selected nodes in a network. The new method allows study of impacts on both specified locations (which do not have to be represented as network nodes) and the region as a whole. The accessibility/remoteness index is defined so that an accessibility surface can be calculated for the region, and the volume under this surface provides an overall measure of accessibility. Changes in the volume under different network states thus reflect the overall impacts. The method is applied to a rural region in south east Australia.
TL;DR: In this paper, the authors present a comprehensive investigation of the behaviour of carsharing members through the analysis of administrative datasets of a dominant car-sharing program in Toronto, and they use both descriptive and econometric approaches for in-depth investigations.
Abstract: The paper presents a comprehensive investigation of the behaviour of carsharing members through the analysis of administrative datasets of a dominant carsharing program in Toronto. The key objective of the investigation is to enhance our understanding on carsharing behaviour in the City of Toronto. Unlike other studies on carsharing, this paper intends to build a comprehensive understanding of the multiple dimensions of users’ behaviour including attitude towards environment, attitude towards safety, frequency of usage, membership duration, vehicle type choice and monthly demand, in terms of total vehicle-kilometre and vehicle-hour travel. The paper uses both descriptive and econometric approaches for in-depth investigations. One of the key contributions of the paper is linking carsharing with carbon offsetting. Investigations reveal that carsharing members are in general environmentally conscious people and are willing to pay for carbon offsetting if given an option. However, having the carbon offsetting option also encouraged a higher amount of driving per month. Results show that carsharing is most often used for off-peak period travel or on weekends, when transit service is poor and traffic congestion is low. The majority of trips made by carsharing members are short-distance trips. It is clear that carsharing is providing a segment of the population with enhanced accessibility and mobility and thus playing an important role in providing a seamless, integrated transportation service in the City of Toronto.
TL;DR: Numerical results show that an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network, and can significantly reduce the search space for determining the most critical links in large-scale networks.
Abstract: To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.
TL;DR: In this paper, the authors analyzed the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs) and found that travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach.
Abstract: This study analyses of the determinants of long distance travel in Great Britain using data from the 1995–2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths ( The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys. For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.
TL;DR: In this paper, the authors discuss the main topics that have been explored, from the debate between complementarity and substitution to analyses in terms of interactions with the spatiotemporal organization of daily activities, the size and maintenance of social networks, and, finally, perception of travel and spaces.
Abstract: The question of the relationship between the spread of communication tools and the physical mobility of individuals is not new and arose with the arrival of the fixed telephone and, more recently, the development of the Internet and especially e-commerce. The extraordinary spread of individual, especially portable, communication tools like the mobile phone, has recently generated new interest in this topic in the fields of transportation economics, geography and sociology. This article discusses the main topics that have been explored, from the debate between complementarity and substitution to analyses in terms of interactions with the spatiotemporal organization of daily activities, the size and maintenance of social networks, and, finally, perception of travel and spaces. We then identify several issues that we think merit further exploration.
TL;DR: In this paper, the authors explore port regionalisation in different contexts through a greater focus on the drivers and direction of a number of inland terminal development strategies, revealing different levels of integration and cooperation observed in different location splitting models.
Abstract: As theoretical approaches to port development have advanced over the years, the role of the inland terminal has attracted increasing focus, particularly under the framework of port regionalisation. This paper will explore port regionalisation in different contexts through a greater focus on the drivers and direction of a number of inland terminal development strategies. The paper will build on previous work by combining inland terminal taxonomies and the theory of directional development with traditional port development models. Regionalisation strategies will be compared and contrasted through examples derived from field work undertaken in Europe and the USA. The results contribute towards a disaggregation of the process of port regionalisation, revealing different levels of integration and cooperation observed in different location splitting models. In this way, different strategies will be elucidated, enabling further exploration and more nuanced understanding of the institutional aspects of spatial development.
TL;DR: In this article, the authors consider nine satisfaction measures of urban transit services, as expressed by a representative sample of Italian multimodal travelers (i.e. users of both private cars and public transport).
Abstract: The importance of measuring customer satisfaction for a public transport service is apparent, even beyond more immediate marketing purposes. The present paper shows how satisfaction measures can be exploited to gain insights on the relationship between personal attitudes, transit use and urban context. We consider nine satisfaction measures of urban transit services, as expressed by a representative sample of Italian multimodal travelers (i.e. users of both private cars and public transport). We use correlations and correspondence analyses to show if and how each attribute is related to the levels of use of public transport, and how the relationship is affected by the urban context. Then we apply a recently developed method to combine ordinal variables into one score, by adapting it to work with large samples and with satisfaction measures which have a neutral point in the scale (i.e. “neither satisfied nor dissatisfied”). The resulting overall satisfaction levels and frequency of use were not correlated in our sample. We also found the highest satisfaction levels in smaller towns and the lowest ones in metropolitan cities. Since we focus on multimodal travelers, an interpretation paradigm is proposed according to which transit services must be well evaluated by car drivers in smaller towns in order to be considered a real alternative to cars. On the other hand, transit is more competitive on factual elements in larger cities, so that it can still be used by drivers, even if it is not very well evaluated.
TL;DR: In this article, the impact of a set of simultaneous policy options and operational measures on the competitiveness and sustainability of hinterland multimodal distribution of import and export containers handled at the seaports of the Campania region located in Southern Italy are presented and discussed.
Abstract: Increasingly, the debate on freight transport and logistics involves the challenge of sustainable development. Key objectives of sustainable or “green” freight logistics systems are the mitigation of negative environmental and human health effects of distribution operations and the realization of a major modal shift in transport preferences, while at the same time achieving internal generalized cost efficiency and quality of services. Pursuing these goals requires the introduction of a range of measures. These measures call for private and public actors to take up various initiatives and adopt policies. Usually, it is more effective to combine different actions into an integrated package of measures than to introduce single instruments in isolation. This article explores the nexus between sustainability and port hinterland container logistics. In particular, the methodology and results of an empirical analysis based on applications of a network programming tool called the “interport model” are presented and discussed. The model enables an examination of all possible effects on inland container flows and their associated internal and external costs due to public and private initiatives in the field of port hinterland container logistics. The empirical analysis aims to evaluate the impact of a set of simultaneous policy options and operational measures on the competitiveness and sustainability of hinterland multimodal distribution of import and export containers handled at the seaports of the Campania region located in Southern Italy. The loading units can transit through the dry port facilities (the so called “interports”) located in the same region and/or through extra regional railway terminals, before reaching their ultimate inland destinations or the seaports. The integrated package of measures simulated by means of the model includes: (i) infrastructure policy, (ii) improvements of rail services, (iii) regulatory changes in terms of customs authorizations and procedures, (iv) removal of technical and legal barriers to fair and non-discriminatory competition in the market of rail traction between regional seaports and interports, (v) new business models integrating container logistics operations between seaports and interports, and (vi) social marginal cost charging of transport operations. Once this package of instruments is introduced, higher private and social cost efficiency of port hinterland container distribution through the investigated regional logistics system can be achieved. For instance, it has been estimated an annual saving of the order of about 12,660 tonnes of CO2 equivalent emissions from transport corresponding to an external cost reduction of 0.27 million euros from the observed real life situation, whereas the estimated saving in terms of air pollution (CO, NOx, PM, SO2, VOC) from transport is approximately 220 tonnes per year corresponding to an external benefit of 1.31 million euros. The most immediate priority appears to be the customs and intermodal logistics integration of seaports and interports by means of full implementation of the “extended gateway” concept as a way to increase the rail share of modal split and improve the overall cost efficiency of the system. In addition, the simultaneous introduction of a social marginal cost charging policy can contribute to make the regional interports a viable solution to expand the hinterland reach of the regional seaport cluster.
TL;DR: In this article, a review of link-based indicators is presented and a multi-linear fit of the indicators is made to find a better, combined, indicator to rank the links according to their vulnerability.
Abstract: It is computationally expensive to find out where vulnerable parts in a network are. In literature a variety of methods were introduced that use simple indicators (measured in real-life or calculated in a traffic simulator) to pre-determine the seriousness of the delays caused by the blocking of that link and thereafter perform a more detailed analysis. This article reviews the indicators proposed in the literature and assesses the quality of these indicators. Furthermore, a multi-linear fit of the indicators is made to find a better, combined, indicator to rank the links according to their vulnerability. The article shows that different indicators assess different links to be vulnerable. Also combined they cannot predict the vulnerability of a link. Therefore, it is concluded that to find vulnerable links, one has to look further than link-based indicators. © 2012 Elsevier Ltd.
TL;DR: In this article, the authors examine cruising for parking using a nationwide random sample of car trips and show that cruising is more common in large cities that receive more car trips, particularly for shopping and leisure activities.
Abstract: The literature on car cruising is dominated by theory. We examine cruising for parking using a nation-wide random sample of car trips. We exclude employer-provided and residential parking. We focus on the Netherlands, where levels of on-street and off-street parking prices are locally the same. We demonstrate then that due to this price setting the average cruising time in the Netherlands is only 36 s per car trip. Furthermore, we show that cruising is not random. It is more common in (large) cities that receive more car trips, particularly for shopping and leisure activities. Cruising time increases with travel duration as well as with parking duration. Cruising has a distinctive pattern over the day with a peak in the morning, so the order of arrival is essential to parking. Because cruising has a spatial and time component, policies may be considered that reduce cruising time through flexible pricing of parking or improved information about vacant parking spaces.
TL;DR: The ADAPTS (Agent-based Dynamic Activity Planning and Travel Scheduling) model as discussed by the authors is an activity-based microsimulation model, which dynamically simulates activity and travel planning and scheduling.
Abstract: This paper describes the representation of the activity planning process utilized in a new activity-based microsimulation model called the ADAPTS (Agent-based Dynamic Activity Planning and Travel Scheduling) model, which dynamically simulates activity and travel planning and scheduling. The model utilizes a dynamic activity planning framework within the larger overall microsimulation system, which is a computational process model that attempts to replicate the decisions which comprise time-dependent activity scheduling. The model presents a step forward in which the usual concepts of activity generation and activity scheduling are significantly enhanced by adding an additional component referred to as activity planning in which the various attributes which describe the activity are determined. The model framework, therefore, separates activity planning from activity generation and treats all three components, generation, planning and scheduling, as separate discrete but dynamic events within the overall microsimulation. The development of the planning order model, which determines when and in what order each activity planning decision is made is the specific focus of this paper. The models comprising the planning order framework are developed using recent survey data from a GPS-based prompted recall survey. The model development, estimation, validation, and its use within the overall ADAPTS system are discussed. A significant finding of the study is the verification of the apparent transferability of the activity planning order model.
TL;DR: In this paper, the authors present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys, using a comprehensive testing framework employing both Logit and mixed Logit structures, with no clear decreasing trend in scale across choice tasks in any of their studies.
Abstract: Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same respondent under varying choice scenarios. While this ability to capture multiple choices is generally seen as an advantage, there is a certain amount of unease about survey length. The precise definition about what constitutes a large number of choice tasks however varies across disciplines, and it is not uncommon to see surveys with up to twenty tasks per respondent in some areas. The argument against this practice has always been one of reducing respondent engagement, which could be interpreted as a result of fatigue or boredom, with frequent reference to the findings of Bradley and Daly (1994) who showed a significant drop in utility scale, i.e. an increase in error, as a respondent moved from one choice experiment to the next, an effect they related to respondent fatigue. While the work by Bradley and Daly has become a standard reference in this context, it should be recognised that not only was the fatigue part of the work based on a single dataset, but the state-of-the-art and the state-of-practice in stated choice survey design and implementation has moved on significantly since their study. In this paper, we review other literature and present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys. Using a comprehensive testing framework employing both Logit and mixed Logit structures, we provide strong evidence that the concerns about fatigue in the literature are possibly overstated, with no clear decreasing trend in scale across choice tasks in any of our studies. For the data sets tested, we find that accommodating any scale heterogeneity has little or no impact on substantive model results, that the role of constants generally decreases as the survey progresses, and that there is evidence of significant attribute level (as opposed to scale) heterogeneity across choice tasks.
TL;DR: In this paper, the authors explored how process related issues play out in Dutch planning practices and found that the biggest challenge lies in decreasing the level of mistrust and communication deficits revealed between plan owners and CBA calculators.
Abstract: Academic discussions on Cost Benefit Analysis (CBA) as an appraisal instrument for integrated land use and transportation plans tend to focus on its technical aspects. However, many issues of CBA also arise from process related matters, especially when assessing integrated plans. Using an inductive research design, we explored how these process related issues play out in Dutch planning practices. In two applied research techniques, focus group sessions and open in depth interviews, we focused on process related issues as perceived by CBA participants ranging from plan makers to CBA testers. This article presents the different perceptions of issues in CBA processes. Through these collected perspectives, we found that these issues are multi-layered and present a number of fundamental dilemmas. After relating our empirical data to theory, we conclude that the biggest challenge lies in decreasing the level of mistrust and communication deficits revealed between plan owners and CBA calculators and their respective frames of thinking when assessing complex integrated land use and transportation plans.
TL;DR: In this article, a cluster analysis was applied to Census data in order to identify potential alternative fuel vehicle drivers in the city of Birmingham, United Kingdom, based on characteristics of age, income, car ownership, home ownership, socio-economic status and education.
Abstract: The transport sector has been identified as a significant contributor to greenhouse gas emissions As part of its emissions reduction strategy, the United Kingdom Government is demonstrating support for new vehicle technologies, paying attention, in particular, to electric vehicles Cluster analysis was applied to Census data in order to identify potential alternative fuel vehicle drivers in the city of Birmingham, United Kingdom The clustering was undertaken based on characteristics of age, income, car ownership, home ownership, socio-economic status and education Almost 60% of areas that most closely fitted the profile of an alternative fuel vehicle driver were found to be located across four wards furthest from Birmingham city centre, while the areas with the poorest fit were located towards the centre of Birmingham The paper demonstrates how Census data can be used in the initial stages of identifying potential early adopters of alternative vehicle drivers It also shows how such research can provide scope for infrastructure planning and policy development for local and national authorities, while also providing useful marketing information to car manufacturers
TL;DR: In this paper, the authors estimate the value of time savings, different cycling environments and additional benefits in cost-benefit analysis of cycling investments, and 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.
Abstract: 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.
TL;DR: In this article, a meta-analysis of variations in seaports' mean technical efficiency (MTE) scores based on 40 studies published in refereed academic journals is presented, where the variation in estimated MTE scores are linked to differences in the frontier methodology used, which essentially are the Data Envelopment Analysis (DEA) and the Stochastic Frontier Analysis (SFA).
Abstract: This paper presents a meta-analysis of variations in seaports’ Mean Technical Efficiency (MTE) scores based on 40 studies published in refereed academic journals. We link the variation in estimated MTE scores to differences in the following factors: the frontier methodology used, which essentially are the Data Envelopment Analysis (DEA) and the Stochastic Frontier Analysis (SFA); regions where seaports are situated; type of data used; number of observations; and the total number of variables used. Furthermore, we compare fixed-effects against a random-effects regression model where the latter assumes that the individual study specific characteristics matter while the former assumes that there is one general tendency across all studies. We present several findings based on the data: (1) the random-effects model outperforms the fixed effects model in explaining the variations in MTEs, (2) recently published studies have lower MTE scores as compared with earlier published studies, (3) studies that used nonparametric DEA models depict higher MTE scores as compared with those that used SFA models, (4) panel data studies have lower TE scores as compared with cross-sectional data, and (5) studies using European seaport data produce lower MTE scores when compared with the rest of the world. Finally, our results contradict some previous meta-analysis studies of TE scores. We encourage the use of random-effects models in meta-analysis studies because they account for individual study specific effects.
TL;DR: In this paper, a consistent framework for road network robustness and vulnerability is presented, in which a definition, terms related to robustness, indicators and an evaluation method are included, and the evaluation method that is presented for evaluating the robustness of the road network against short term variations in supply (like incidents).
Abstract: There is a growing awareness that road networks, are becoming more and more vulnerable to unforeseen disturbances like incidents and that measures need to be taken in order to make road networks more robust. In order to do this the following questions need to be addressed: How is robustness defined? Against which disturbances should the network be made robust? Which factors determine the robustness of a road network? What is the relationship between robustness, travel times and travel time reliability? Which indicators can be used to quantify robustness? How can these indicators be computed? This paper addresses these questions by developing a consistent framework for robustness in which a definition, terms related to robustness, indicators and an evaluation method are included. By doing this, policy makers and transportation analyst are offered a framework to discuss issues that are related to road network robustness and vulnerability which goes beyond the disconnected definitions, indicators and evaluation methods used so far in literature. Furthermore, the evaluation method that is presented for evaluating the robustness of the road network against short term variations in supply (like incidents) contributes to the problem of designing robust road networks because it has a relatively short computation time and it takes spillback effects and alternative routes into account.
TL;DR: In this paper, a system dynamics modeling approach is employed due to the causal relationships and feedback loops that are observed in the problem structure and three potential strategies for policy making are tested with the developed dynamic simulation: fuel efficiency, public transportation and electric vehicle usage.
Abstract: The need for sustainable development is increasing as the industrial and service activities keep putting such a strain on the natural functions of the Earth, thus the ability of the planet’s to sustain future generations. Since most of the industrial and service activities are provided via transportation, it is one of the most crucial elements of sustainable development. In this paper, US highway system sustainability problem is studied. System dynamics modeling approach is employed due to the causal relationships and feedback loops that are observed in the problem structure. The reference mode is considered as the increasing CO2 emission trend. The objective is to meet the Liberman and Warner Climate Act’s targets by 2050. Three potential strategies for policy making are tested with the developed dynamic simulation: fuel efficiency, public transportation and electric vehicle usage. The results indicate that hybrid implementation of individual policies has a crucial impact on the success of policy making.
TL;DR: In this article, a bi-objective routing model is proposed to determine the route choice set of commuter cyclists by formulating a routing problem, where the two objectives considered are travel time and suitability of a route for cycling.
Abstract: It is widely acknowledged that cyclists choose their route differently to drivers of private vehicles. The route choice decision of commuter drivers is often modelled with one objective, to reduce their generalised travel cost, which is a monetary value representing the combined travel time and vehicle operating cost. Commuter cyclists, on the other hand, usually have multiple incommensurable objectives when choosing their route: the travel time and the suitability of a route. By suitability we mean non-subjective factors that characterise the suitability of a route for cycling, including safety, traffic volumes, traffic speeds, presence of bicycle lanes, whether the terrain is flat or hilly, etc. While these incommensurable objectives are difficult to be combined into a single objective, it is also important to take into account that each individual cyclist may prioritise differently between travel time and suitability when they choose a route. This paper proposes a novel model to determine the route choice set of commuter cyclists by formulating a bi-objective routing problem. The two objectives considered are travel time and suitability of a route for cycling. Rather than determining a single route for a cyclist, we determine a choice set of optimal alternative routes (efficient routes) from which a cyclist may select one according to their personal preference depending on their perception of travel time versus other route choice criteria considered in the suitability index. This method is then implemented in a case study in Auckland, New Zealand. The study provides a starting point for the trip assignment of cyclists, and with further research, the bi-objective routing model developed can be applied to create a complete travel demand forecast model for cycle trips. We also suggest the application of the developed methodology as an algorithm in an interactive route finder to suggest efficient route choices at different levels of suitability to cyclists and potential cyclists.
TL;DR: In this article, the authors developed simultaneous equation models for predicting aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation using panel data for the 48 continental states during the period 1998-2008.
Abstract: Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998–2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.