Towards integrated land use and transportation: A dynamic disequilibrium based microsimulation framework for built space markets

Investigating the factors and processes that influence the spatiotemporal distribution of built space and population in an urban area, plays an extremely important role in our greater understanding of the urban travel behaviour. Existing location of activity centres, especially home and work, strongly influences the short-term individual-level decisions such as mode of transportation, and long-term household-level decisions such as change in job and residential location. Conditions in the built space market also affect households’ and firms’ location and relocation decisions, and hence influence the general travel patterns in an urban area. In this context, this paper addresses a very important, but at the same time, not very widely investigated dimension that plays a key role in the evolution of built space and population distribution: Market. A disequilibrium based microsimulation modelling framework is developed for the built space markets. This framework is then used to operationalize the Greater Toronto and Hamilton Area’s owner-occupied housing market within Integrated Land Use Transportation and Environment (ILUTE) modelling system. Simulation results captured heterogeneity in the transaction prices, due to type of dwellings and different market conditions, in a very disaggregate fashion. The proposed methodology is validated by running the simulation from 1986 to 2006 and comparing the results with the historic data.     

Gender differences in activity participation,time-of-day and duration choices: new evidence from Calgary

To date only limited research has quantified differences between female and male activity patterns, and analyses at an individual activity level are scarce. Past research has focused on investigating gender differences in mobility levels based on observed travel patterns, especially those related to commuting. This article reports new evidence based on analyses of a household activity survey data-set collected from a Canadian city – Calgary – in 2001. Results show that contemporary females and males have a very similar activity participation pattern. On the other hand, analyses applied to activity starting times support the view that there are minor gender differences in time-of-day choices. In addition, duration and survival analyses through log-rank and Wilcoxon tests show that women and men tend to spend more or less time on some of the 10 weekend/weekday activities, and thus indicate that they share different domestic and societal responsibilities: males tend to spend longer time for out-of-home activities, such as work, school, social, and out-of-town; whereas females contribute more to domestic work, including shopping, eating, and religious activity. In general, this article contributes new evidence to gender differences in activity participation, time-of-day, and duration choices at the individual activity level. Such differences may influence travelers’ time, mode, and location choices and thus have important implications for the complexity of an activity-based modeling framework. These implications are discussed along with recommendations for incorporating gender differences in an activity-based modeling framework.     

Airline energy efficiency measures considering carbon abatement: A new strategic framework

In this paper, airline energy efficiency is divided into two stages: Operations Stage and Carbon Abatement Stage. This new two-stage operating framework is a modification of existing ones. Then the model, Network SBM with weak disposability, is presented to evaluate the efficiency of 22 international airlines from 2008 to 2012. The results show that: (1) Most airlines’ energy efficiencies have not declined in the period. (2) The average efficiency of European airlines is higher than that of non-European airlines. (3) Non-European airlines have smaller advancements in efficiency score than European airlines. (4) Most airlines’ efficiencies in Operations Stage are higher than Carbon Abatement Stage.     

Built environments and mode choice: toward a normative framework

Compact, mixed-use, and walk-friendly urban development, many contend, can significantly influence the modes people choose to travel. Despite a voluminous empirical literature, most past studies have failed to adequately specify relationships for purposes of drawing inferences about the importance of built-environment factors in shaping mode choice. This paper frames the study of mode choice in Montgomery County, Maryland around a normative model that weighs the influences of not only three core dimensions of built environments – density, diversity, and design – but factors related to generalized cost and socio-economic attributes of travelers as well. The marginal contributions of built-environment factors to a traditionally specified utility-based model of mode choice are measured. The analysis reveals intensities and mixtures of land use significantly influence decisions to drive-alone, share a ride, or patronize transit, while the influences of urban design tend to be more modest. Elasticities that summarize relationships are also presented, and recommendations are offered on how outputs from conventional mode-choice models might be “post-processed” to better account for the impacts of built environments when testing land-use scenarios.     

Evaluating the pedestrian realm: instrumental rationality,communicative rationality and phenomenology

Following the passage of ISTEA, increased attention to pedestrian planning has led to the development of pedestrian plans, particularly at the metropolitan and municipal levels. This has raised the issue of how cities and metropolitan areas evaluate the walkability of the pedestrian realm and identify improvement projects. Three approaches to evaluating the pedestrian realm are examined: instrumental rationality, communicative rationality, and phenomenology. Case studies demonstrating the application of these approaches to the development of pedestrian plans are examined in the Phoenix metropolitan area, Portland, Oregon, and Cambridge, Massachusetts.

Modeling traffic crash rates of road segments through a lognormal hurdle framework with flexible scale parameter

This study examines distributional characteristics of crash rates for road segments using observed accident data. The results indicate that the distribution of crash rates is mixed and right‐skewed, which motivates the consideration of non‐normal distributions. With the aid of Kolmogorov–Smirnov tests, kernel density plots, and Q–Q plots, the lognormal distribution is verified as an appropriate candidate for representing the positive domain of crash rates. Then, a lognormal hurdle model was developed and also compared with gamma and Weibull hurdle models. Further, the lognormal hurdle model was revised by allowing the scale parameter to vary with respect to explanatory variables. Such a modification enables the heterogeneous skewness of samples to be captured while enhancing the modeling flexibility. The proposed model was also compared with a Tobit model, an alternative approach that treats crash rates as censored data. Among all these models, the proposed lognormal hurdle model with flexible scale parameter presents the best modeling performance, and the analyses also reveal that several explanatory variables affect crash rates through not only the location parameter but also the scale parameter in the lognormal model. This study finally attempted to inspect crash rates through count models, and it discovered that the proposed hurdle model is superior because it is able to output the whole distribution form of crash rates, whereas the crash count model can only provide the expected value of crash rates, provided the exposure variable servers as an offset term in the link function of the mean parameter. Copyright © 2015 John Wiley & Sons, Ltd.     

What transportation modeling needs from a GIS: a conceptual framework

Both the geographic information system (GIS) and transportation modeling environments have seen continually developing analytic concepts and techniques. However, these developments have seldom resulted in the integration of GISs and transportation models. This paper explores the potential inherent in merging of these environments through a systematic investigation of the fundamental basis of integration. To do this, the traditional four step transportation modeling process is extended to include input and output steps. We then define functional components for GIS data handling — data management, manipulation, and analysis. The steps of modeling are matched against the list of GIS data handling functions within a matrix‐based framework. GIS functions that enhance a land‐use based urban transportation modeling process are then categorized. Conclusions are drawn and directions for future developments are discussed.     

A new composite decision support framework for strategic and sustainable transport appraisals

This paper concerns the development of a new decision support framework for the appraisal of transport infrastructure projects. In such appraisals there will often be a need for including both conventional transport impacts as well as criteria of a more strategic and/or sustainable character. The proposed framework is based on the use of cost-benefit analysis featuring feasibility risk assessment in combination with multi-criteria decision analysis and is supported by the concept of decision conferencing. The framework is applied for a transport related case study dealing with the complex decision problem of determining the most attractive alternative for a new fixed link between Denmark and Sweden – the so-called HH-connection. Applying the framework to the case study made it possible to address the decision problem from an economic, a strategic, and a sustainable point of view simultaneously. The outcome of the case study demonstrates the decision making framework as a valuable decision support system (DSS), and it is concluded that appraisals of transport projects can be effectively supported by the use of the DSS. Finally, perspectives of the future modelling work are given.     

Vehicle routing problem and driver behaviour: a review and framework for analysis

Vehicle routing problems (VRPs) whose typical objective is to minimise total travel costs over a tour have evolved over the years with objectives ranging from minimising travel times and distances to minimising pollution and fuel consumption. However, driver behaviour continues to be neglected while planning for vehicle routes. Factors such as traffic congestion levels, monotonous drives and fatigue have an impact on the behaviour of drivers, which in turn might affect their speed-choice and route-choice behaviours. The behaviour of drivers and their subsequent decision-making owing to these factors impact the revenue of transport companies and could lead to huge losses in extreme cases. There have been studies on the behaviour of drivers in isolation, without inclusion of the objectives and constraints of the traditional routing problem. This paper presents a review of existing models of VRP, planner behaviour models in the VRP context and driver behaviour models and provides a motivation to integrate these models in a stochastic traffic environment to produce practical, economic and driver-friendly logistics solutions. The paper provides valuable insights on the relevance of behavioural issues in logistics and highlights the modelling implications of incorporating planner and driver behaviour in the framework of routing problems.     

Exploring transportation equity: Development and application of a transportation justice framework

Recent efforts to emphasize social equity in transportation are emerging as local, regional and national governments have set initiatives to identify, existing and potential, disproportionate impacts to low-income and minority populations, also referred to as transportation justice (TJ). Currently, there are suggested methods for identifying transportation justice areas; however, there is no streamlined method instituted across transportation agencies. Each jurisdiction identifies transportation justice (or environmental justice) areas based on their own methodology, typically based on either average regional thresholds, graduated thresholds, or a more unique in-house index methodology. This research explores and evaluates existing methods and develops a rigorous and comprehensive method called the Transportation Justice Threshold Index Framework (TJTIF) using Geographic Information Systems (GIS), as well as factors based on demographics, socio-economics, and transportation/land use. The framework is applied to a case study region in Pennsylvania reflective of the Marcellus Shale impact area, highlighting Sullivan County, PA. The methodology and the case study application serve as an example for how transportation agencies throughout the country can promote social sustainability and enhance transportation equity.     

Time taken for residents to adopt a new public transport service: examining heterogeneity through duration modelling

When a new public transport service is introduced it would be valuable for public authorities, financing organisations and transport operators to know how long it will take for people to start to use the service and what factors influence this. This paper presents results from research analysing the time taken for residents living close to a new guided bus service to start to use (or adopt) the service. Data was obtained from a sample of residents on whether they used the new service and the number of weeks after the service was introduced before they first used it. Duration modelling has been used to analyse how the likelihood of starting to use the new service changes over time (after the introduction of the service) and to examine what factors influence this. It is found that residents who have not used the new service are increasingly unlikely to use it as time passes. Those residents gaining greater accessibility benefits from the new service are found to be quicker to use the service, although the size of this effect is modest compared to that of other between-resident differences. Allowance for the possibility that there existed a proportion of the sample that would never use the new service was tested using a split population model (SPD) model. The SPD model indicates that 36% of residents will never use the new service and is informative in differentiating factors that influence whether Route 20 is used and when it is used.

Active travel as a pro-environmental behaviour: An integrated framework

A travel mode may be chosen due to its emotional appeal (affective motive) or to express social status (symbolic motive). Previous studies have overlooked the role of such motives in active mode use as pro-environmental behaviour. This study aims to examine the role of symbolic and affective motives, together with other significant theoretical perspectives, to explain the share of active modes of transport in trips to the university. It adds to the previous literature by considering the share of active modes of transport in different seasons. We collected a total of 316 completely filled questionnaires (response rate = 75.4 percent) from a cross-sectional self-administered survey in February 2019 in Trondheim, Norway. Among the psychological variables related to active mode use, only affective motives were found significant in both summer and winter. Environmental self-identity predicted both types of motives. No evidence suggested that personal environmental norms and attitudes towards transportation significantly explained active mode share, although car-related subjective norms reached significance. Furthermore, there was no evidence that environmental attitudes towards transportation had a mediating effect between motives and active mode use. Cycling journey time between place of residence and campus was found significant in the share of active modes of transport in both seasons. The results have important ramifications for the provision of relevant regulations and raising positive support from society to enhance the share of active modes of travel to the university.     

Cycle Network Planning: Towards a Holistic Approach Using Temporal Topology

ABSTRACT

Current cycle-network planning (CNP) at the local level tends to be dominated by a subjective-pragmatic approach in which it is only possible to consider a limited number of route alignment possibilities and development-sequencing scenarios. Although this method may produce acceptable results, it may also be true that the final design could be improved – and the construction efficiency could be enhanced – by a more comprehensive review of the available options in relation to the objectives of the intervention. Such objectives may include accident reduction, modal shift in favour of cycling, health benefits or strategic expansion of a network. This article presents work undertaken to demonstrate a holistic approach to CNP, based on a logically defined spatio-temporal model and allowing some semi-automated multiobjective optimization of network designs in a GIS-based decision-support system. The model is introduced briefly before a case study applying this model to development of a cycle network in a small town in northeast England is described. The results obtained from this case study and the implications of this research for cycle network planners are discussed.     

A survey on planning semi-flexible transit systems: Methodological issues and a unifying framework

When demand for transportation is low or sparse, traditional transit cannot provide efficient and good-quality service, due to its fixed structure. New transportation alternatives are therefore increasingly proposed, combining on-demand service adjustment capabilities to the regular route and schedule characteristics of traditional transit. Such so-called semi-flexible systems require careful planning, but no formalization of the corresponding decisions problems, nor any comprehensive methodology has been proposed yet. This paper aims at contributing to fill this gap by presenting a comprehensive literature review, and a general and unifying modeling framework for representing and planning semi-flexible systems. The latter takes the form of the Demand Adaptive Systems, which generalizes the semi-flexible systems described in the literature, and also offers a number of advanced features, the scheduling mechanism, in particular. The paper then provides a classification of planning decisions, which is used to structure a comprehensive and comparative literature review of the field of semi-flexible systems, including methodological contributions as well as a number of particularly significant practical experiences.     

Multi-modal and demand-responsive passenger transport systems: a modelling framework with embedded control systems

The LITRES-2 modelling system provides a framework for investigating the performance of urban passenger transport systems, with particular attention to demand-responsive transport modes and traveller information technologies. The modes covered include conventional timetabled services (buses, trains etc.), taxis (both single- and multiple-hire), and other demand-responsive services. Tables of estimated aggregate demand are disaggregated so as to produce a stream of fully-articulated travel-requests. Individual requests are resolved as single- or multiple-leg journeys, through the use of request-broking and journey-planning modules that seek to minimise travellers' generalised costs. Journey-legs allocated to demand-responsive modes are handled by a fleet-scheduling module which includes provision for “instantaneous” as well as advance-notice bookings, and for contingent situations such as breakdowns and passenger no-shows. The fleet-scheduling and journey-planning modules are designed as embedded control systems and are intended for use in real-time as well as modelling applications. The paper describes the main analytical and procedural components of LITRES-2, and assesses some methodological issues arising from experience in recent planning studies. The system appears to be well suited for use in modelling situations where the critical issues are concerned with the supply rather than demand side of transportation activity.     

Transport and environment interactions: the italian framework

With road traffic in Europe forecast to increase, strategies are needed to keep transportation sector growth within the bounds imposed by a sustainable development. Research is contributing through a large number of projects dealing with transport–environment interactions. This paper reviews international research activities in this field, focusing on technological innovations, air and noise pollution prediction models, and existing tools for socioeconomic evaluation of traffic impacts on the environment. In particular, research projects of the Second Special Project on Transport (PFT2) of the Italian National Research Council (CNR) are outlined.     

A discrete choice framework for modeling and forecasting the adoption and diffusion of new transportation services

Major technological and infrastructural changes over the next decades, such as the introduction of autonomous vehicles, implementation of mileage-based fees, carsharing and ridesharing are expected to have a profound impact on lifestyles and travel behavior. Current travel demand models are unable to predict long-range trends in travel behavior as they do not entail a mechanism that projects membership and market share of new modes of transport (Uber, Lyft, etc.). We propose integrating discrete choice and technology adoption models to address the aforementioned issue. In order to do so, we build on the formulation of discrete mixture models and specifically Latent Class Choice Models (LCCMs), which were integrated with a network effect model. The network effect model quantifies the impact of the spatial/network effect of the new technology on the utility of adoption. We adopted a confirmatory approach to estimating our dynamic LCCM based on findings from the technology diffusion literature that focus on defining two distinct types of adopters: innovator/early adopters and imitators. LCCMs allow for heterogeneity in the utility of adoption for the various market segments i.e. innovators/early adopters, imitators and non-adopters. We make use of revealed preference (RP) time series data from a one-way carsharing system in a major city in the United States to estimate model parameters. The data entails a complete set of member enrollment for the carsharing service for a time period of 2.5 years after being launched. Consistent with the technology diffusion literature, our model identifies three latent classes whose utility of adoption have a well-defined set of preferences that are significant and behaviorally consistent. The technology adoption model predicts the probability that a certain individual will adopt the service at a certain time period, and is explained by social influences, network effect, socio-demographics and level-of-service attributes. Finally, the model was calibrated and then used to forecast adoption of the carsharing system for potential investment strategy scenarios. A couple of takeaways from the adoption forecasts were: (1) placing a new station/pod for the carsharing system outside a major technology firm induces the highest expected increase in the monthly number of adopters; and (2) no significant difference in the expected number of monthly adopters for the downtown region will exist between having a station or on-street parking.     

Towards improved port capacity investment decisions under uncertainty: a real options approach

ABSTRACT

Port activity plays an important role in facilitating international trade. Sufficient capacity is indispensable for a port to attract flows to a region and retain them. The capacity decision is the result of a trade-off between investment and waiting costs. Traditional methods to value expansion projects do not deal adequately with managerial flexibility in the face of uncertainty from different sources in the complex port environment. In this paper, real options (RO) models are identified as an alternative method to making project valuations and investment decisions, as they attribute the correct value to managerial flexibility under uncertainty. In order to be able to build and use such RO models for port capacity investment decisions, the sources and implications of uncertainty in the port and the different RO model specifications need to be understood. To this end, both the literature about uncertainty in the port context and the literature about real options models are reviewed in order to provide researchers who want to build their own decision-making models, with the necessary knowledge of both fields. The review makes clear that the complex interactions in and competition between the logistics chains and their actors coming together in ports have significant impacts on port capacity. Uncertainty is also caused by uncertain international trade flows and changes in legislation following new technologies and environmental impacts. An analysis of the components of some general RO models shows how the options of flexible output, investment size and timing are valued by RO models in a setting with demand uncertainty. Moreover, the review presents researchers with insights in how to deal with cooperative and competitive interactions in the chain, time to build, cyclical markets and legislation changes. It also shows how to value the expansion and the phased investment options. The new insights resulting from this review are subsequently combined in a framework that serves as a guideline to build RO models for port capacity investments. Finally, an exemplifying application of the framework is used to build an actual port capacity investment decision model.