Conformity: How VMT-speed distributions can affect mobile emission inventories

Transportation conformity is a US regulatory process that requires that transportation modeling be integrated with air quality modeling. Consequently, every change to either modeling process is undertaken with great scrutiny by the regional governments, who have to use the models for demonstrating conformity. This paper explores the "trip versus link debate," which stems from the fact that the standard travel demand models used by most metropolitan planning organizations are primarily link oriented, while the air quality models have been primarily trip oriented. Using the Sacramento region we examine the effects on mobile source emissions inventories when speed-VMT distributions are constructed using the trip and link-based philosophies. The results of our study indicate that trip-based VMT-speed distributions produce consistently lower emissions estimates than the link-based distributions. We use the results to assert that deciding between a trip-based or link-based conformity modeling process involves more than the technical difficulty of changesto the models or the potential political ramifications, it involves assessing which method will provide the most accurate estimates of regional motor vehicle emissions. We also examine ways to think about constructing mobile source emission inventories.     

Roll Dynamics of Commercial Vehicles

An analytical model is developed here for studying the roll dynamics of commercial vehicles. Large displacements and rotations are accounted for in this nonlinear model so that it can be used for the study of roll dynamics well beyond the limits of wheel lift-off. The model is used to illustrate some of the dynamic phenomena in vehicle rollover, especially the interactive coupling between the roll and the vertical modes of motion. The influence of suspension backlash on rollover resistance is demonstrated, and the phenomenon of roll motion resonance is illustrated to suggest new means for evaluating vehicle rollover sensitivity.     

Engine performance and toxic gas analysis of biobutanol-blended gasoline as a vehicle fuel

A comprehensive study evaluating the performance of biobutanol-blended gasoline in passenger cars was conducted because biobutanol is considered a better biofuel than bioethanol as it has no water solubility and it has a higher caloric value, giving it a higher energy value. Several kinds of samples—suboctane gasoline, 8 volume percentage and 16 volume percentage biobutanol—blended gasoline, and a 10 volume percentage MTBE-blended market sample (as the oxygencontaining gasoline)-were tested to evaluate the engine performance in terms of the detergency of the intake valves and combustion chambers, power, emissions, and fuel efficiency. Additionally, the toxicity of the emissions from these biobutanolblended samples was tested in order to assess the viability of biobutanol as one of the competitive potential substitutes for MTBE as an oxygenator in the near future. The results show that biobutanol-blended gasoline samples had relatively better detergency, relatively higher power, and similar levels of emissions compared with those of MTBE-blended gasoline. Formaldehyde was emitted from all of the samples at almost the same levels and within the error range, whereas biobutanolblended gasoline samples emitted approximately three times the amount of acetaldehyde than did the suboctane gasoline. This study shows that biobutanol is one of the best alternative bioalcohol fuels for use in the near future.     

A reduced-gravity model of the Catalan Sea

A reduced-gravity model is used to study the effects of the wind on the upper layer circulation in the Catalan Sea. The model parameters were set by observed features of the circulation in the basin. It is shown that the results are particularly sensitive to the open sea boundary conditions. Simulations were done using the following boundary fluxes: (i) mean values estimated by Bethoux (1980) and (ii) more recent geostrophic transports computed from hydrographic data by Font et al. (1988). The latter seem to lead to more realistic circulation patterns. The influence of seasonal winds (climatological data) on the dynamics is clear, especially during the winter.     

Design and Practice of Cloud Computing Platform for TBM Operation Information北大核心CSCD

The problems of TBM construction data loss, information barriers and absence of data mining have con⁃ strained the advancement of basic technologies in TBM field. Aimed at building a cloud computation platform for TBM operation information, a new concept of 3B, i. e. Born by digit, Born in format and Born to the cloud, was pre⁃ sented, the issues of information acquisition, transmission and storage during TBM operation were solved, and massive heterogeneous information intelligent transmission system and big data warehouse of TBM group were established. A structure model of cloud computation platform was designed by taking Hadoop system as ecosphere, and a cloud computation platform was built to deploy related algorithm, realizing on-line monitoring and data sharing, further⁃ more the data law mining of interaction of rock mass versus TBM machine was conducted based on big data tech⁃ nique, exploring the development direction of the information platform. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

Determinants of airport retail revenue: a review of literature

ABSTRACT

As the airport retail industry continues to grow due to increasing travel demands, airport operators are increasingly developing their retail revenue potential to ensure financial viability. This study aims to provide a review of airport retail literature and identify the salient factors associated with passenger shopping behaviour. The paper presents a review of contemporary airport retail literature, covering a total of 50 studies from 1998 to 2018. The review identified 26 factors, which could broadly be grouped into five categories: airport/operator related; passengers' demographic related; passengers’ travel related; passengers’ psychological related and passengers’ resources related. In addition to providing a summary of the statistically significant factors across studies, the review identifies and discusses potential approaches for future research. These include the importance of considering both “to spend or not” decision and how much to spend and how most empirical studies focussed on the former; the gap in empirical analysis on the impact of airport terminal design layout on retail performance; and the gap in application of general consumer shopping behavioural models to airport retail problems. The paper concludes with the suggestion that we can build on the existing studies to develop a hybrid approach to solve several of the identified gaps simultaneously.     

Analysis of factors that may be essential in the decision to fly on fully autonomous passenger airliners

This research investigates factors that influence opinion in the decision to fly on fully autonomous passenger airliners primarily from the perspective of aviation and technology professionals. Bayesian statistical inference and a two‐level fractional factorial survey are used to sample passengers' views on fully autonomous airliners. Eight trust, safety, and cost factors are incorporated into a vignette set in the future. Factors include automation levels, safety records, liability guarantees, airline integrity, and service disruptions. Dependent variables exist in five post‐vignette questions and essentially ask “Would you” or “Would you not” be willing to fly on a fully autonomous airliner? Sixteen versions of the vignette, each with unique trust, safety, and cost levels, present varying (unknown) degrees of influence to the survey respondents. For every demographic, the research shows a 99% statistically significant difference between the “prior” and “posterior” sampled population proportions willing to fly. The most significant positive influence involves integrity characteristics of the airline, while the most negative influence relates to life insurance liability guarantees. Research from 2003 suggested that this mode of travel would be acceptable to only 10.5% of respondents. When the 2003 research is used as a Bayesian prior probability, the resulting posterior probability for the demographics sampled can be modeled as a beta distribution, indicating 95% probability that the sampled proportion of the population willing to fly is between 33.2% and 36.4%. After adjusting for age and profession demographics to match the US population, the 95% probability bounds on the proportion willing to fly are 31.35% and 34.15%. Copyright © 2015 John Wiley & Sons, Ltd.     

A traffic flow simulator for short‐term travel time forecasting

This paper presents an off‐line forecasting system for short‐term travel time forecasting. These forecasts are based on the historical traffic count data provided by detectors installed on Annual Traffic Census (ATC) stations in Hong Kong. A traffic flow simulator (TFS) is developed for short‐term travel time forecasting (in terms of offline forecasting), in which the variation of perceived travel time error and the fluctuations of origin‐destination (O‐D) demand are considered explicitly. On the basis of prior O‐D demand and partial updated detector data, the TFS can estimate the link travel times and flows for the whole network together with their variances and covariances. The short‐term travel time forecasting by O‐D pair can also be assessed and the O‐D matrix can be updated simultaneously. The application of the proposed off‐line forecasting system is illustrated by a numerical example in Hong Kong.