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.     

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.     

Trip distribution for limited destinations: a case study for grocery shopping trips in the Netherlands

In this paper, we introduce a new trip distribution model for destinations that are not homogeneously distributed. The model is a gravity model in which the spatial configuration of destinations is incorporated in the modeling process. The performance was tested on a survey with reported grocery shopping trips in the Dutch city of Almelo. The results show that the new model outperforms the traditional gravity model. It is also superior to the intervening opportunities model, because the distribution can be described as a function of travel costs, without increasing the computational time. In this study, the distribution was described by a simple function of Euclidean distance, which provides a good fit to the survey data. The slope of the distribution is quite steep. This shows that most trips are made to nearby supermarkets. However, a significant fraction of trips, mainly made by car, still goes to supermarkets further away. We argue that modeling of these trips by the new method will improve traffic flow predictions.     

Evaluating locational accessibility to the US air transportation system

Although there are hundreds of airports that support commercial air passenger traffic in the United States (US), not all areas are equivalently served by the commercial air transportation system. Locations in the US differ with respect to their level of access to the commercial air network and their overall accessibility within the system. Given the complexity of the domestic commercial air passenger network and supporting infrastructure, past research has only been able to provide a limited assessment of locational accessibility within the United States. To address these complexities, this paper proposes a new metric that incorporates measures of access to air transport as well as accessibility within air transportation networks. Using a comprehensive dataset on scheduled airline service, the developed approach is then applied to the US domestic commercial passenger air transportation network to explore geographic differentials in accessibility. Results suggest marked differences between core-based statistical areas throughout the US.     

Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling

This study reviews the 50-year history of travel demand forecasting models, concentrating on their accuracy and relevance for public decision-making. Only a few studies of model accuracy have been performed, but they find that the likely inaccuracy in the 20-year forecast of major road projects is ±30 % at minimum, with some estimates as high as ±40–50 % over even shorter time horizons. There is a significant tendency to over-estimate traffic and underestimate costs, particularly for toll roads. Forecasts of transit costs and ridership are even more uncertain and also significantly optimistic. The greatest knowledge gap in US travel demand modeling is the unknown accuracy of US urban road traffic forecasts. Modeling weaknesses leading to these problems (non-behavioral content, inaccuracy of inputs and key assumptions, policy insensitivity, and excessive complexity) are identified. In addition, the institutional and political environments that encourage optimism bias and low risk assessment in forecasts are also reviewed. Major institutional factors, particularly low local funding matches and competitive grants, confound scenario modeling efforts and dampen the hope that technical modeling improvements alone can improve forecasting accuracy. The fundamental problems are not technical but institutional: high non-local funding shares for large projects warp local perceptions of project benefit versus costs, leading to both input errors and political pressure to fund projects. To deal with these issues, the paper outlines two different approaches. The first, termed ‘hubris’, proposes a multi-decade effort to substantially improve model forecasting accuracy over time by monitoring performance and improving data, methods and understanding of travel, but also by deliberately modifying the institutional arrangements that lead to optimism bias. The second, termed ‘humility’, proposes to openly quantify and recognize the inherent uncertainty in travel demand forecasts and deliberately reduce their influence on project decision-making. However to be successful either approach would require monitoring and reporting accuracy, standards for modeling and forecasting, greater model transparency, educational initiatives, coordinated research, strengthened ethics and reduction of non-local funding ratios so that localities have more at stake.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Prediction of fatigue life and estimation of its reliability on the parts of an air suspension system

Air suspension systems have been implemented in various commercial vehicles, such as buses and special purpose trucks, because of the comfortable ride and easy height control. An evaluation of the durability of vehicle parts has been required for service life and safety starting in the early stages of design. The cyclic load applied to the vehicle can cause fatigue failure of parts, such as the suspension frame. This paper presents a method to predict the fatigue life of the suspension frame at the design stage of the air suspension system used in a heavy-duty vehicle. To estimate the fatigue life using the SN method, the Dynamic Stress Time History (DSTH) is necessary for the part of interest. DSTH can be obtained from the results of the flexible body dynamic analysis using the Belgian road simulation and the Modal Stress Recovery (MSR) method. Furthermore, the reliability of the predicted fatigue life can be evaluated by considering the variations in material properties. The probability and distribution of the expected life cycle can be obtained using experimental design with a minimum number of simulations. The advantage of using statistical methods to evaluate the life cycle is the ability to predict replacement time and the probability of failure of mass-produced parts. This paper proposes a rapid and simple method that can be effectively applied to the design of vehicle parts.     

Design of power split transmission: Design of dual mode power split transmission

The power split type hybrid system transmits engine power by dividing it into the electrical unit and the mechanical unit. Its power transmission efficiency is highest at the mechanical point (MP), where the full power is transmitted to the mechanical unit. In this study, the equation for the MP was derived for the gear ratios of a general 4-node lever model. The MP characteristics for the transmission ratio (TR) of the input split and compound split structures were examined using the equation derived. Using the examined input split and compound split structures, a systematic design method for the dual mode power split transmission was proposed. In the dual mode power split transmission, the MP could be positioned at the desired TR, and the input split and compound split modes could be selectively used according to the clutch combination, which leads to the operation of the vehicle within a high system efficiency range.     

Robust lane markings detection and road geometry computation

Detection of lane markings based on a camera sensor can be a low-cost solution to lane departure and curve-over-speed warnings. A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue because of cast shadows, worn and occluded markings, variable ambient lighting conditions, for example. We focus on increasing detection reliability in two ways. First, we employed an image feature other than the commonly used edges: ridges, which we claim addresses this problem better. Second, we adapted RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane lines to the image features, based on both ridgeness and ridge orientation. In addition, the model was fitted for the left and right lane lines simultaneously to enforce a consistent result. Four measures of interest for driver assistance applications were directly computed from the fitted parametric model at each frame: lane width, lane curvature, and vehicle yaw angle and lateral offset with regard the lane medial axis. We qualitatively assessed our method in video sequences captured on several road types and under very different lighting conditions. We also quantitatively assessed it on synthetic but realistic video sequences for which road geometry and vehicle trajectory ground truth are known.