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In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

Over the past decade, transportation researchers have leveraged global positioning system (GPS) technology to improve the accuracy and increase the depth of spatial and temporal details obtained through household travel surveys. While earlier studies used GPS as a supplement to traditional household travel survey methods, measuring the accuracy of trips reported (Wolf et al., 2006), studies are now underway to identify the methods and tools that will allow us to do away with paper diaries entirely and simply rely on GPS to obtain trip details. This paper finds that while GPS clearly helps to improve participation among some groups, it decreases participation among others. Thus, it should be considered a tool in the household travel survey toolbox and not “the” solution to non-response issues in household travel surveys.

Purpose — The Regional Household Travel Survey (RHTS) was a large-scale regional household travel survey that covered 28 counties in the New York, North New Jersey, and Connecticut regions (i.e., the New York City “megaregion”). Data collection for the survey began in October 2010 and concluded in November 2011.

The chapter discusses the multiple modes and methodologies used in the RHTS, and presents the participation rates and trip rates obtained using this multimodal approach.

Methodology/approach — This survey used a combination of web, telephone, and mail-out/mail-back methods to collect household and travel information from approximately 18,800 households. Ten percent of the sampled households participated in the survey by using wearable global positioning system (GPS) devices that collected detailed travel data which, in turn, were processed and presented back to the households in a GPS-based prompted recall interview administered by web or telephone. The GPS component was used to generate trip rate correction factors for the other 90% diary-based households.

Findings — This large regional survey was the first to use this specific combination of methods and technologies, and provides many insights into the success of targeted survey modes and methods for different population groups.

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and misspecification-robust alternative to the quasi-maximum likelihood estimator (QMLE). In this paper we investigate the asymptotic behavior of the VTE when the stationary distribution of the GARCH process has infinite fourth moment. Existing studies of historical asset returns indicate that this may be a case of empirical relevance. Under suitable technical conditions, we establish a stable limit theory for the VTE, with the rate of convergence determined by the tails of the stationary distribution. This rate is slower than that achieved by the QMLE. The limit distribution of the VTE is nondegenerate but singular. We investigate the use of subsampling techniques for inference, but find that finite sample performance is poor in empirically relevant scenarios.

The purpose of this paper is to propose a stable high-order absorbing boundary condition (ABC) based on new continued fraction for scalar wave propagation in 2D and 3D unbounded layers.

The ABC is obtained based on continued fraction (CF) expansion of the frequency-domain dynamic stiffness coefficient (DtN kernel) on the artificial boundary of a truncated infinite domain. The CF which has been used to the thin layer method in [69] will be applied to the DtN method to develop a time-domain high-order ABC for the transient scalar wave propagation in 2D. Furthermore, a new stable composite-CF is proposed in this study for 3D unbounded layers by nesting the above CF for 2D layer and another CF.

The ABS has been transformed from frequency to time domain by using the auxiliary variable technique. The high-order time-domain ABC can couple seamlessly with the finite element method. The instability of the ABC-FEM coupled system is discussed and cured.

This manuscript establishes a stable high-order time-domain ABC for the scalar wave equation in 2D and 3D unbounded layers, which is based on the new continued fraction. The high-order time-domain ABC can couple seamlessly with the finite element method. The instability of the coupled system is discussed and cured.

In this chapter, we address the question if and how modern technology can be used to design questionnaires, diaries, web sites, and experiments to improve the validity of reliability of active data collection instruments. In particular, it discusses the history of computer-assisted activity diary data, reenactment sessions, stated preference methods, and interactive computer experiments with a special focus on the design of these instruments in terms of respondent support and user interfaces. Empirical evidence and experience suggests that although fascinating instruments may increase respondent motivation and involvement and therefore improve the reliability of the measurements, there is also the danger that respondents' answers are influenced by features of the electronic instrument that are not essential, reducing validity and reliability.