An integrated spatio-temporal GIS toolkit for exploring intra-household interactions

This paper reports on the development of an integrated spatio-temporal GIS toolkit that facilitates the exploration of intra-household interactions. Two tools comprise the toolkit. The first tool, Space-Time Coincidence Analyst, identifies joint activity/travel episodes undertaken by household members. The core of this tool is a set of flexible criteria for classifying episodes as either joint or independent. The second tool, Space-Time Path Visualizer, not only displays space-time paths for household members, but also shows joint episodes undertaken by any two household members together. The toolkit can be applied to any household-based, activity/travel data set so long as required information is specified by the user. To demonstrate its usefulness for research, the toolkit is applied to the TAPS (Toronto Activity Panel Survey) 2002–03 data set. The results suggest that considerable variation exists in the number of joint activity/travel episodes identified using different classification criteria. Specifically, when using restrictive criteria (i.e., same timing, specific activity type/travel mode), only 2,265 joint activity/travel episodes are identified compared to 8,791 when using more flexible criteria. In turn, our results show that certain key attributes for independent and joint activity/travel episodes (i.e., frequency per household, starting time, ending time and duration) also vary under the different classification criteria.

Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach

Although telecommuting has become a popular option as a new mode of working, no theoretical or empirical consensus has been reached on its potential for substituting or generating travel. This study aims to evaluate the impact of a household head’s telecommuting on household travel while controlling for the interdependence within a household and across travel purposes, by applying seemingly unrelated censored regression models to data from the 2006 Household Travel Survey in the Seoul Metropolitan Area. In terms of vehicle kilometers traveled, the analysis shows that telecommuters’ non-commute and non-work trips as well as his/her household members’ non-work trips are greater than those of non-telecommuters and their household members’, whereas telecommuting partially reduces commuting trips. However, an analysis stratified by household type reveals that the difference for household members is significant only in households with less than one vehicle per employed member: in such households (with insufficient vehicles available), the vehicle otherwise used for mandatory travel, such as for the household head’s commute, can be used for non-commute purposes or by other household members if the household head does not use it for commuting. This implies that, when vehicle travel budgets of a given household are limited, this compensatory travel mechanism can make optimum use of limited resources (i.e., vehicles), but offsets the travel-substituting effect of telecommuting. Accordingly, to more precisely estimate the impact of telecommuting-promotion policies and apply them as part of travel demand management strategies, their counteracting effects among household members should be considered.     

The intra-household choices regarding commuting and housing

This paper is an empirical analysis of the relationships between commuting decisions of spouses in dual-income households, where the role of housing and housing tenure is taken into account. The study is based on a large survey of US commuters and actual commuting and housing choices. Household commuting decisions are analyzed together with housing choices using the data from the 2001 American Housing Survey. A sample of dual-career spouses who commute to work by car only is used to explore the inter-relationship between male and female commuting decisions in such households and the effect of housing choices on their commuting. The inter-relationships between spousal commuting decisions are examined separately for the two forms of housing tenure: ownership and renting. In general, men commute further than women and owners commute further than renters.It is shown that for both renters and homeowners, journeys to work by men and women in such dual-earner households appear to be “complements” and not “substitutes”. This means that commute trips are jointly chosen to be longer (or shorter) for both spouses, as part of household selection of preferred housing and neighborhood characteristics. The residuals of equations explaining commute times and commute distances for men are strongly positively correlated with those for women. Many of the explanatory factors affect the men and women in similar ways. In particular, housing value is positively correlated with commute times and distances for both genders. The commute distance for women owners appears more sensitive to housing value than that of men, meaning women adjust their trips to work even more so than men do, as part of obtaining better housing.For both homeowners and renters, longer commute distances were correlated with higher salaries for both spouses. Somewhat surprisingly, it was found that commuting distances for women are similarly or even more sensitive to income increments than are those of men. Household size appears to affect women who own housing in ways opposite from those who rent. Other housing and neighborhood factors also affect the joint commuting decisions of these men and women.     

Modeling the interactions between car and bicycle in heterogeneous traffic

In this paper, a new cellular automata model is proposed to simulate the car and bicycle heterogeneous traffic on urban road. To capture the complex interactions between these two types of vehicles, a novel occupancy rule is adopted in the proposed model to consider the variable lateral distances of mixed vehicular traffic. Based on massive simulations, microscopic fundamental diagrams under different bicycle densities are devised. With these, the bicycle's spilling behavior is then investigated and discussed. In order to reflect the interference of a bicycle on a car, the interference transformation from friction state to block state is modeled explicitly. Finally, different simulation results under different occupancy rules indicate that the constant and fixed occupancy rule adopted in the previous studies might lead to overestimation of car flux in the heterogeneous traffic flows with different bicycle densities. Copyright © 2013 John Wiley & Sons, Ltd.     

Modeling household interactions in daily in-home and out-of-home maintenance activity participation

The activity travel patterns of individuals in a household are inter-related, and the realistic modeling of activity-travel behavior requires that these interdependencies be explicitly accommodated. This paper examines household interactions impacting weekday in-home and out-of-home maintenance activity generation in active, nuclear family, households. The in-home maintenance activity generation is modeled by examining the duration invested by the male and female household heads in household chores using a seemingly unrelated regression modeling system. The out-of-home maintenance activity generation is modeled in terms of the decision of the household to undertake shopping, allocation of the task to one or both household heads, and the duration of shopping for the person(s) allocated the responsibility. A joint mixed-logit hazard-duration model structure is developed and applied to the modeling of out-of-home maintenance activity generation. The results indicate that traditional gender roles continue to exist and, in particular, non-working women are more likely to share a large burden of the household maintenance tasks. The model for out-of-home maintenance activity generation indicates that joint activity participation in the case of shopping is motivated by resource (automobiles) constraints. Finally, women who have a higher propensity to shop are also found to be inherently more efficient shoppers.     

A sequential group decision-making approach to strategic planning for the development of commercial vehicle operations systems

This paper explores a new sequential decision methodology which integrates a generalized sequential probability ratio testing approach with a strategy-value matrix analytical tool to determine the developmental priorities of commercial vehicle operations (CVO) technical packages for CVO time-based strategic planning. The proposed method executes a sequential decision algorithm utilizing the strategic elements of strategy-value matrices which are estimated on the basis of the data collected from the survey respondents. In the process of sequential decision making, the identification of a specific CVO value-added technology package can be made once the condition of the minimum group decision-making cost is met. In addition to methodology development, a real case study together with a nation-wide mail survey to aid the estimation of the strategy-value matrix samples which were used as inputs to the proposed sequential decision algorithm was conducted in Taiwan to demonstrate the feasibility of the proposed method. Utilizing the proposed method, we determined efficiently the developmental priorities of CVO technology packages for short-term, mid-term, and long-term strategic plans, respectively. Our analyses results indicated that the CVO package used for fleet management appears to be the most urgently needed in the short-term CVO strategic plan; value-added technology packages including: (1) data warehousing, (2) information technology, (3) integration with the supply chain management (SCM) platform, (4) freight mobility, (5) integration with advanced traffic management systems (ATMS), and (6) extension for intermodal operations are assigned to the mid-term CVO strategic plan; and others including: (1) freight administration, (2) HAZMAT management, (3) on-board safety monitoring, and (4) roadside safety inspections are involved in the long-term CVO strategic plan. We expect that this study can make available the proposed decision-making support method with benefits not only for planning CVO development strategies, but also for re-examining the role of commercial vehicle operations in a comprehensive extent.     

Incorporating uncertainty and risk in transportation investment decision-making

This paper presents a framework for addressing uncertainty and risk for large-scale transportation investments involving public–private participation. Demand, fare/toll and demand responsive costs are considered in the uncertainty analysis. Uncertainty analysis provides information on economic feasibility of the project. A set of relaxation policies is proposed to form various Ownership, Tenure and Governance (OTG) strategies reflecting the nature and level of participation by the public and private entity. A Monte Carlo Simulation-based Value at Risk is used to quantify risk. Finally, a methodology is proposed to integrate uncertainty and risk. The framework is tested on the proposed multibillion dollar Detroit River International Crossing connecting the cities of Detroit in the USA with Windsor in Canada. The analysis provides insights to probable outcomes for this transportation infrastructure investment under different OTG scenarios.     

Future air traffic management systems and financial decision-making constraints

The object is to identify characteristics of feasible systems for UK – and European – Air Traffic Management (ATM) in the coming decades. ATM here covers Air Traffic Control (ATC) provision plus wider issues, such as airspace design. The analytical focus is on the financial decision-making processes and constraints that will act to shape this future system. R&D work into control workload and planning based on an "ATM core concept" are proposed as likely to offer the best way forward.     

Site selection for EVCS in Istanbul by GIS and multi-criteria decision-making

Considering the depletion of fossil fuels and the environmental impact of transport, reducing the use of such fuels is a globally accepted priority. Thus, when moving towards alternative energy types, the first will undoubtedly be electrical energy. In order to accelerate and contribute to this process, electric vehicles (EV) must be preferred over conventional motor vehicles. However, there are various problems associated with the use of EVs, such as range and recharge status. Optimal planning of electric vehicle charging stations (EVCS) is a solution to these problems. For this purpose, parameters affecting EVCS locations have been determined in the paper. Considering these parameters and the current EVCS locations, the most suitable alternative EVCS locations were identified using Geographical Information Systems (GIS). Both the current and alternative EVCS locations were evaluated by Analytic Hierarchy Process (AHP), Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) from multi-criteria decision-making (MCDM) methods. The results show that, in Istanbul, the southeast of the European side and the southwest of the Anatolian side were most suitable for EVCS.     

Co-location decision tree for enhancing decision-making of pavement maintenance and rehabilitation

This paper presents a new decision tree induction method, called co-location-based decision tree (CL-DT), to enhance the decision-making of pavement maintenance and rehabilitation strategies. The proposed algorithm utilizes the co-location characteristics of spatial attribute data in the pavement database. The paper first presented the co-location mining algorithm, including spatial attribute data selection, determination of rough candidate co-locations, determination of candidate co-locations, pruning the non-prevalent co-locations, and induction of co-location rules, and then focused on the development of the co-location decision tree (CL-DT) algorithm, which includes the non-spatial attribute data selection, co-location algorithm modeling, node merging criteria, and co-location decision tree induction. A pavement database covering four counties, which are provided by North Carolina Department of Transportation (NCDOT), is used to verify the proposed method. The experimental results demonstrated that (1) the proposed CL-DT algorithm can make a better decision, and has higher accuracy than the existing decision tree methods do; (2) the training data can be fully played roles in contribution to decision tree induction and the computational time taken for the tree growing, tree drawing and rule generation is largely decreased; (3) quantity and locations of six treatment strategies proposed by the ITRC and by CL-DT is much close for each treatment strategy.     

The politics of collective public participation in transportation decision-making

Citizen involvement in transportation planning is typically modeled on a liberal democracy in which individuals express their preferences about a project. In this paper we present an analysis based on interviews with stakeholders whose involvement was grounded in a complementary model of public participation, one in which an organized community used collective action (instead of only individual expression), and worked both within and outside of the formal public involvement process to influence the design of an arterial highway in their neighborhood. This case reflects a commonplace context for public participation: residents opposing a highway expansion and the negative effects of heavy traffic in neighborhoods. The problem presented in this case is that the process for citizen involvement was not designed to fully utilize the community’s collective capacity. Three aspects of collective action—representation, the ability to shape a policy agenda, and methods of engagement—were contested in the public participation process. We argue that these conflicts around collective action in the public participation process exposed its “one-way communication,” and enabled a different kind of political process in which neighbors’ organizing was powerful and influenced decisions.     

A three-stage evacuation decision-making and behavior model for the onset of an attack

Pedestrian behavior models have successfully reproduced human movement in many situations. However, few studies focus on modeling human behavior in the context of terrorist attacks. Terrorist attacks commonly occur in crowded public areas and result in a large number of casualties. This paper proposes a three-stage model to reproduce a series of complex behaviors and decision-making processes at the onset of an attack, when pedestrians generally do not have clear targets and have to deal with fuzzy information from the attack. The first stage of the model builds a Bayesian belief network to represent the pedestrians’ initial judgment of the threat and their evacuation decisions. The second stage focuses on pedestrians’ global assessment of the situation through an analogy with diffusion processes. The third stage uses a cost function to reproduce the trade-offs of distance, safety, and emotional impact when considering a path to take. The model is validated using a video from the November 2015 Paris attack. The behavioral characteristics and trajectories of three pedestrians extracted from the video are reproduced by the simulation results based on the model. The research can be used to set rules when performing risk analysis and strategic defensive resource allocation of terrorist attacks using agent-based simulation methods.     

A three-stage decision-making model for selecting electric vehicle battery technology

This study proposes a three-stage decision-making model for the selection of electric vehicle battery technology. Data used for analysis include surveys completed by 45 technology experts from industry, academia, and research throughout Taiwan. A three-stage model that includes developing multiple-criteria during the first stage, integrating the importance of criteria assessment using the fuzzy analytical hierarchy process in the second stage, and using patent analysis tools to further identify the patent portfolio of the technology selected by experts in the third stage are employed. The empirical results indicate that power source management technology and battery module technology are the key technologies for development by the electric vehicle industry. Battery energy storage management and cooling technology are found to be the key for building patent portfolios. When faced with substantial technical and market uncertainty, multiple-criteria for research and development (R&D) selection and stage-wise integration of decision tool must be employed by battery firms to effectively allocate the resources for R&D decisions.     

Spoke airports,intentional and unintentional ground travel,and the air travel decision-making process

For air travelers originating from the spokes of the US hub-and-spoke air network, price, flight frequency, and aircraft type are all known factors in their travel decision-making process. Less well known, however, is the extent to which different elements of ground travel enter into these travelers’ air journeys. Based on 51 interviews at four universities at spokes surrounding O’Hare International Airport, this article describes how considerations such as vehicle availability, individual driving ability, localized weather, and unanticipated ground travel are fundamentally part of the air travel decision-making process for spoke travelers.     

Location privacy preferences: A survey-based analysis of consumer awareness,trade-off and decision-making

With the advent and rapid dissemination of location-sensing information technology, the issue of location information privacy is receiving growing attention. Perhaps of greatest concern is ensuring that potential users of mobile Information and Communications Technologies (e.g., Location-Based Services and Intelligent Transportation Systems) are comfortable with the levels of privacy protection afforded them, as well as with the benefits they will receive in return for providing private location information. This paper explores the concepts of privacy risks, benefits, willingness to trade, and compensation in relationship to mobile and locational technologies using a stated preference survey to ascertain areas of interest in determining the trade-offs that consumers will be willing to make in return for mobility enhancements. Analysis of the survey leads to findings that while respondents believe that sharing data in the mobile environment may pose privacy risks, they do not generally take steps necessary to address these risks; that privacy preferences are impacted by a range of factors, including both personal and contextual considerations (such as factors arising from their specific situation at the time of information seeking); and that willingness to trade private location data is dependent upon a number of factors related to context, personal characteristics, expected benefits and degree of trust in the collecting organization.     

Junction interactions and monotonicity in traffic assignment

We consider the traffic equilibrium problem when the travel demand is inelastic and stationary in time. Junction interactions, which abound in urban road networks, are permitted. We prove that the set of equilibria (solutions to the assignment problem) is convex when certain monotonicity and continuity conditions are statisfied at each junction.     

Psychological benefits from vanpooling and group composition

Prospective carpool satisfaction varies with respect to carpool size, acquaintanceship and gender composition, at least for carpool arrangements of 2–4 members. It is not known whether such variations apply in the same kind or to the same degree for vanpools of 9–15 members. A study of 15 vanpool programs in Southern California operating over 700 vanpools with more than 8,000 members was used to test for such effects. Five measures of retrospective vanpool satisfaction were derived from 40 vanpool benefit items using factor analysis in LISREL. The five perceived vanpool satisfaction factors included reliability, social, relaxation, economic and environmental benefits. Variations in these five benefit factors were analyzed with respect to vanpool group composition using difference of means tests and correlation analysis. Perceived vanpool reliability showed the largest statistical association with most of the group composition variables studied, perhaps because it was better identified in the analysis in terms of the total number of individual items loading on it. Gender had the largest statistical association with most of the vanpool benefit factors, perhaps because it was most clearly identified with individual vanpool members in the data. Based on this analysis, it appears that perceived vanpool benefits are qualitatively as well as quantitatively different than perceived carpool benefits. Vanpool program marketing strategies may need to be rethought and recast based on these research findings.     

Modeling and measurements of bus service reliability

A new concept for predicting the performance reliability of a bus service is developed and evaluated. Reliability of bus service is defined as the amount of consistency associated with an operational performance measure from day to day. The variability of travel time performance is posited as the best indicator of reliability. Travel time is found to be an accurate and easily collectible performance measure, and data are collected for several steady periods. These are defined as periods in which performance measure characteristics remain relatively unchanged. A beta distribution with predicted parameters r and T is fitted for the bus travel time data, both for peak and off-peak situations. Based on this distribution, a strategy for predicting perfomance reliability is suggested.