Novel large scale simulation process to support dot’s cafe modeling system

This paper demonstrates a new process that has been specifically designed for the support of the U.S. Department of Transportation’s (DOT’s) Corporate Average Fuel Economy (CAFE) standards. In developing the standards, DOT’s National Highway Traffic Safety Administration made use of the CAFE Compliance and Effects Modeling System (the “Volpe model” or the “CAFE model”), which was developed by DOT’s Volpe National Transportation Systems Center for the 2005–2007 CAFE rulemaking and has been continuously updated since. The model is the primary tool used by the agency to evaluate potential CAFE stringency levels by applying technologies incrementally to each manufacturer’s fleet until the requirements under consideration are met. The Volpe model relies on numerous technology-related and economic inputs, such as market forecasts, technology costs, and effectiveness estimates; these inputs are categorized by vehicle classification, technology synergies, phase-in rates, cost learning curve adjustments, and technology “decision trees”. Part of the model’s function is to estimate CAFE improvements that a given manufacturer could achieve by applying additional technology to specific vehicles in its product line. A significant number of inputs to the Volpe decision-tree model are related to the effectiveness (fuel consumption reduction) of each fuel-saving technology. Argonne National Laboratory has developed a fullvehicle simulation tool named Autonomie, which has become one of the industry’s standard tools for analyzing vehicle energy consumption and technology effectiveness. Full-vehicle simulation tools use physics-based mathematical equations, engineering characteristics (e.g., engine maps, transmission shift points, and hybrid vehicle control strategies), and explicit drive cycles to predict the effectiveness of individual and combined fuel-saving technologies. The Large-Scale Simulation Process accelerates and facilitates the assessment of individual technological impacts on vehicle fuel economy. This paper will show how Argonne efficiently simulates hundreds of thousands of vehicles to model anticipated future vehicle technologies.     

Development of route information based driving control algorithm for a range-extended electric vehicle

A route information based driving control algorithm was developed for an RE-EV which consists of two motorgenerators, MG1 and MG2. A threshold power which controls the engine on/off to charge the battery was obtained by an optimization process using route information, such as the vehicle velocity and altitude. The threshold power allows the vehicle to travel to the final destination while making the final battery SOC close to SOC _low. Using the threshold power, route based control (RBC) was proposed by considering the driver’s characteristics and traffic conditions using the driving data base. In addition, a relationship between the threshold power and various initial battery SOC was obtained by off-line optimization. The performance of the RBC was evaluated by simulation and human-in-the-loop simulation (HILS) for city driving. It was found from the simulation and HILS results that the RBC achieved approximately 4 % to 12 % reduction in fuel consumption compared to the existing charge depleting/charge sustaining (CD/CS) driving control.     

Improving multi-channel wave-based V2X communication to support advanced driver assistance system (ADAS)

The advent of vehicle-to-everything (V2X) communication has opened the opportunity to design advanced driver assistance systems (ADAS) that collect information from sensors in neighboring vehicles and roadside infrastructure. IEEE and ETSI have designed network protocol standards for V2X communications. Despite the differences between the vehicular wireless communication architecture defined by ETSI and the IEEE protocol stack, the two standards have multichannel operations as a main commonality, with some channels dedicated to safety-critical applications and others to nonsafety services. Some recent studies have demonstrated that these standards might not provide sufficient channel utilization for reliable exchange of information in mid- and heavily congested scenarios. In this paper, we propose and evaluate the performance of a driver-assistance system to reduce the connectivity gaps between vehicles and roadside units (RSUs). This cooperative system of multi-service channel allocation will improve radio channel utilization. We also show that the required latency for this inter-vehicle communication can be obtained using the IEEE-WAVE standards and dedicated short-range communication (DSRC) proposed for vehicular environments. Simulation results show that the proposed scheme can improve the average throughput by up to 15 % in various traffic density conditions compared with the dynamic channel allocation method.     

Non-intrusive polynomial chaos for efficient uncertainty analysis in parametric roll simulations

Monte Carlo analyses are generally considered the standard for uncertainty analysis. While accurate, these analyses can be expensive computationally. Recently, polynomial chaos has been proposed as an alternative approach to the estimation of uncertainty distributions (Hosder et al. A non-intrusive polynomial chaos method for uncertainty propagation in CFD simulations. In: 44th AIAA aerospace sciences meeting and exhibit, Reno, Nevada, 2006; Wu et al. Uncertainty analysis for parametric roll using non-intrusive polynomial chaos. In: Proceedings of the 12th international ship stability workshop, Washington, DC, USA, 2011). This approach works by representing the function as a series of orthogonal polynomials; the weights for which can be calculated via several methods. Previous studies have demonstrated the usefulness of this technique for comparatively simple systems such as parametric roll modeled by the Mathieu equation with normally distributed parameter values (Wu et al. Uncertainty analysis for parametric roll using non-intrusive polynomial chaos. In: Proceedings of the 12th international ship stability workshop, Washington, DC, USA, 2011). In the present work, a polynomial chaos method is applied to a nonlinear computational ship dynamics model with normally distributed input parameters. Test cases were selected where parametric roll was expected to potentially occur. The resulting probability distributions are compared to the results of a Monte Carlo analysis. In general, these results demonstrate good agreement between Monte Carlo simulation and polynomial chaos in the absence of capsize with significant computation gains found with polynomial chaos. Overall, we conclude that polynomial chaos is an effective tool for reducing simulation time costs when studying parametric roll, and potentially other ship dynamics phenomena, particularly in the absence of capsize-like bifurcations.     

SiMoCo: the viability of a prototype platform for a coastal monitoring system: a case study

Coastal zones are among the most productive areas in the world, offering a wide variety of valuable habitats and ecosystems services. Despite the low population density in the Brazilian coastal zone, their distribution is quite concentrated near some coastal cities and state capitals. This concentration places enormous pressure on coastal resources. Therefore, the main objective of this paper is to present an overview on the current status of SiMoCo (Sistema de Monitoramento Costeiro, or Coastal Monitoring System in English) project as a possible early warning system that can be integrated to the Brazilian Coastal Management Information System. This prototype platform provides a real-time access to the composition, organization and simulation of planktonic communities. First, our results demonstrate such a system detecting a target dinoflagellate; second, we apply structural and functional indexes to compare and characterize the ecological networks from two different coastal areas. Conclusions are made about SiMoCo’s feasibility and its possible contribution to the decision-making process within integrated coastal zone management (ICZM) strategies.     

建设武汉城市圈城际轨道交通的必要性研究

借鉴国内外城市圈城际轨道交通发展经验,分析武汉城市圈社会经济及交通现状与发展目标,从促进区域经济发展、引导城市空间布局、建设“资源节约型、环境友好型”社会、优化综合运输体系、适应城际客流需求等方面论述建设城际轨道交通的必要性。     

The Gulf Stream, rings and North Atlantic eddy structures from remote sensing (Altimeter and SeaWiFS)

Seasonal SeaWiFS chlorophyll a concentrations cycles and annual changes of altimeter Sea Level Anomaly are derived for the subtropical North Atlantic near  35°N and along a Gulf Stream axis. Spatial structure of SeaWiFS, is defined in terms of deviations from a local seasonal cycle and examined in relation to altimeter eddy structure. In the subtropical region near 35°N, SeaWiFS structure is evident during the spring bloom period with a scale of  430 km, or about twice the eddy scale. A Gulf Stream axis has been selected as a region where the Sea Level Anomaly variance is a maximum. Eddy propagation speeds and scales are examined. Cold-core (cyclonic) rings correspond to areas of high SeaWiFS chlorophyll a. Warm-core (anticyclonic) rings relate to areas of low chlorophyll concentration. Both SeaWiFS structure and eddy structure have a spatial scale of  450 km or twice the ring scale along the Gulf Stream axis. SeaWiFS chlorophyll anomalies and Altimeter Sea Level Anomaly structure have an overall negative correlation coefficient of r = − 0.34. Swirl currents between eddies redistribute surface chlorophyll concentrations and can spatially bias maximum and minimum concentration levels off eddy centre.     

Choice valuation of traffic restrictions: Noise, pollution, and congestion preferences. A note

This Note looks at the choice valuation restrictions on traffic entering the city of Lisbon, based on individual preferences in relation to noise, pollution and congestion. The analysis employs a questionnaire distributed in 2007 to ascertain the significant characteristics of traveling to Lisbon, with the aim of curbing the number of cars that are associated with the probability of individuals supporting a charge on motor vehicles entering the city. The model also takes into account the uncontrolled heterogeneity of the data.     

How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles

This study explores the relationships between adoption and consideration of three travel-related strategy bundles (travel maintaining/increasing, travel reducing, and major location/lifestyle change), linking them to a variety of explanatory variables. The data for this study are the responses to a fourteen-page survey returned by nearly 1,300 commuting workers living in three distinct San Francisco Bay area neighborhoods in May 1998. We first identified patterns of adoption and consideration among the bundles, using pairwise correlation tests. The test results indicate that those who have adopted coping strategies continue to seek for improvements across the spectrum of generalized cost, but perhaps most often repeating the consideration of a previously-adopted bundle. Furthermore, we developed a multivariate probit model for individuals’ simultaneous consideration of the three bundles. It is found that in addition to the previous adoption of the bundles, qualitative and quantitative Mobility-related variables, Travel Attitudes, Personality, Lifestyle, Travel Liking, and Sociodemographics significantly affect individual consideration of the strategy bundles. Overall, the results of this study give policy makers and planners insight into understanding the dynamic nature of individuals’ responses to travel-related strategies, as well as differences between the responses to congestion that are assumed by policy makers and those that are actually adopted by individuals.

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.