Research Needs for Determining Spatially Resolved Subfleet Characteristics

1998 ◽  
Vol 1625 (1) ◽  
pp. 139-146 ◽  
Author(s):  
William Bachman ◽  
Jessica Granell ◽  
Randall Guensler ◽  
John Leonard
Keyword(s):  
Data Availability ◽  
Vehicle Emission ◽  
Research Needs ◽  
Research Issues ◽  
Spatially Resolved ◽  
Registration Data ◽  
Regional Registration ◽  
Emission Models ◽  
Future Emission ◽  
Mobile Emission

Future emission models will need spatially resolved subfleet characteristics to determine mobile emission inventories. The use of geographic information systems and regional registration data for developing location-specific vehicle characteristics that can feed future models is addressed. Issues regarding data availability and quality are explored to define gaps in the research that may prevent development of comprehensive and accurate estimates. As a component of a larger research project studying vehicle emission modeling, a six-step process was developed and implemented for a 100 km2 area in Atlanta. Vehicles were geocoded by using registration addresses, and vehicle characteristics were determined through a series of computer programs, commercial software, and related datasets. During the process, many research issues were identified that prevent a comprehensive assessment of spatially resolved fleet characteristics. The data and research needed to further improve the capability to generate spatially resolved subfleet characteristics were identified.

Study of Participation Barriers in Family-Focused Prevention: Research Issues and Preliminary Results

1993 ◽  
Vol 13 (4) ◽  
pp. 365-388 ◽  
Author(s):  
Richard Spoth ◽  
Cleve Redmond
Keyword(s):  
Telephone Interview ◽  
Mail Survey ◽  
Prevention Research ◽  
Research Needs ◽  
Research Issues ◽  
Sample Representativeness ◽  
Participation Barriers ◽  
Survey Results ◽  
Project Participants ◽  
Reasons For Decisions

There is a growing body of literature which argues for more research on barriers to participation in family-focused interventions, particularly among at-risk families. Following a review of research needs and issues suggested by the literature, this article presents results from a study which 1) evaluates reasons for decisions against participation in a family-focused prevention intervention project and 2) compares characteristics of intervention project participants with those of non-participants. Data on reasons for refusing participation were collected from non-participants during a recruitment telephone interview and via a mail survey. Results indicated that the most frequent reasons given for decisions against participation concerned intervention time demands and research-related requirements such as videotaping. There were no significant differences between participants and non-participants on any sociodemographic variables. Analyses of the relationships between reasons for participation refusal and sociodemographic subgroupings of non-participants, however, suggested that variations exist among these subgroups. Overall, results highlight the feasibility and importance of data collection on intervention project non-participants, both to clarify potential participation barriers and to gather data on sample representativeness.

scholarly journals Designing On-Road Vehicle Test Programs for the Development of Effective Vehicle Emission Models

2005 ◽  
Vol 1941 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Theodore Younglove ◽  
George Scora ◽  
Matthew Barth
Keyword(s):  
Estimation Error ◽  
Vehicle Emission ◽  
Emission Measurement ◽  
Mobile Source ◽  
Emission Data ◽  
Data Set ◽  
Mobile Vehicle ◽  
Emission Models ◽  
Road Emission ◽  
Source Emission

Mobile source emission models for years have depended on laboratory-based dynamometer data. Recently, however, portable emission measurement systems (PEMS) have become commercially available and in widespread use, and make on-road real-world measurements possible. As a result, the newest mobile source emission models (e.g., U.S. Environmental Protection Agency's mobile vehicle emission simulator) are becoming increasingly dependent on PEMS data. Although on-road measurements are made under more realistic conditions than laboratory-based dynamometer test cycles, they introduce influencing variables that must be carefully measured for properly developed emission models. Further, test programs that simply measure in-use driving patterns of randomly selected vehicles will result in models that can effectively predict current-year emission inventories for typical driving conditions. However, when predicting more aggressive transportation operations than current typical operations (e.g., higher speeds, accelerations), the model predictions will be less certain. In this paper, various issues associated with on-road emission measurements and modeling are presented. Further, an example on-road emission data set and the reduction in estimation error through the addition of a short aggressive driving test to the in-use data are examined. On the basis of these results, recommendations are made on how to improve the on-road test programs for developing more robust emission models.

Communication Treatment for Adults With Dementia

1991 ◽  
Vol 34 (4) ◽  
pp. 831-844 ◽  
Author(s):  
Michelle S. Bourgeois
Keyword(s):  
Social Work ◽  
Communication Skills ◽  
Intervention Studies ◽  
Social Validity ◽  
Positive Outcomes ◽  
Research Needs ◽  
Speech Language Pathology ◽  
Research Issues ◽  
Language Pathology ◽  
Aging Adults

Intervention studies reporting improvements in communication skills in aging adults presumed to have dementia were identified and reviewed. Whereas the speech-language pathology journals have published only articles on the diagnosis and identification of communication deficits in adults with dementia, over 100 articles on treatments effecting changes in communicative deficiencies were found in psychology, social work, nursing, and gerontology journals. Much evidence supports the potential for positive outcomes from communication treatment with this population. Various design and methodological flaws, however, limit the extent to which these interventions should be applied without further research. Issues of ethics and social validity are discussed, and treatment and research needs are outlined.

scholarly journals Fuel Consumption and Vehicle Emission Models for Evaluating Environmental Impacts of the ETC System

2015 ◽  
Vol 7 (7) ◽  
pp. 8934-8949 ◽  
Author(s):  
Jiancheng Weng ◽  
Ru Wang ◽  
Mengjia Wang ◽  
Jian Rong
Keyword(s):  
Fuel Consumption ◽  
Environmental Impacts ◽  
Vehicle Emission ◽  
Emission Models

Use of Statewide Models as a Decision Tool for Zero-Emission Vehicles Deployment

2017 ◽  
Vol 2628 (1) ◽  
pp. 78-86 ◽  
Author(s):  
Wenbo Fan ◽  
Sevgi Erdogan ◽  
Timothy F. Welch ◽  
Frederick W. Ducca
Keyword(s):  
Travel Demand ◽  
Spatial Scales ◽  
Spatial Differentiation ◽  
Market Penetration ◽  
Effective Strategies ◽  
Decision Making Processes ◽  
Emission Models ◽  
Zero Emission ◽  
Mobile Emission ◽  
The Impact

Under worldwide environmental stress, zero-emission vehicles (ZEV) are rapidly coming to market. However, it is not clear how such vehicles reduce vehicular emissions at a spatially explicit level, which is crucial for developing specific policies. This study proposed a quantitative approach to estimate the effectiveness of ZEVs in reducing emissions to support investment decisions promoting the use of ZEVs. The approach uses existing statewide travel demand and mobile emission models in an integrated framework. Scenarios are designed to measure the emissions reduction effects of ZEVs at different spatial scales (statewide, county, and roadway) and characteristics (densely and sparsely populated counties) and with various levels of market penetration and driving range limits. Results show significant spatial differentiation of the impact of ZEV deployment from county to roadway levels. Offering greater spatial detail and new insights on decision-making processes, this study described an integrated tool for identifying effective strategies for ZEV implementation.

scholarly journals Vehicle Emission Computation Through Microscopic Traffic Simulation Calibrated Using Genetic Algorithm

2019 ◽  
Vol 9 (1) ◽  
pp. 67-80 ◽  
Author(s):  
Yun Wei ◽  
Ying Yu ◽  
Lifeng Xu ◽  
Wei Huang ◽  
Jianhua Guo ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Vehicle Emissions ◽  
Traffic Simulation ◽  
Urban Region ◽  
Vehicle Emission ◽  
Activity Data ◽  
Microscopic Traffic Simulation ◽  
Emission Models ◽  
Vehicle Activity

Abstract Vehicle emission calculation is critical for evaluating motor vehicle related environmental protection policies. Currently, many studies calculate vehicle emissions from integrating the microscopic traffic simulation model and the vehicle emission model. However, conventionally vehicle emission models are presented as a stand-alone software, requiring a laborious processing of the simulated second-by-second vehicle activity data. This is inefficient, in particular, when multiple runs of vehicle emission calculations are needed. Therefore, an integrated vehicle emission computation system is proposed around a microscopic traffic simulation model. In doing so, the relational database technique is used to store the simulated traffic activity data, and these data are used in emission computation through a built-in emission computation module developed based on the IVE model. In order to ensure the validity of the simulated vehicle activity data, the simulation model is calibrated using the genetic algorithm. The proposed system was implemented for a central urban region of Nanjing city. Hourly vehicle emissions of three types of vehicles were computed using the proposed system for the afternoon peak period, and the results were compared with those computed directly from the IVE software with a trivial difference in the results from the proposed system and the IVE software, indicating the validity of the proposed system. In addition, it was found for the study region that passenger cars are critical for controlling CO, buses are critical for controlling CO and VOC, and trucks are critical for controlling NOx and CO2. Future work is to test the proposed system in more traffic management and control strategies, and more vehicle emission models are to be incorporated in the system.

scholarly journals Towards Stable Principles of Collective Intelligence under an Environment-Dependent Framework

2020 ◽  
Author(s):  
Abdullah Almaatouq
Keyword(s):  
Group Composition ◽  
Collective Intelligence ◽  
Large Body ◽  
Open Science ◽  
Data Availability ◽  
Future Research ◽  
Individual Level ◽  
Registration Data ◽  
Virtual Lab ◽  
Structural Attribute

A large body of work has shown that a group of individuals can often achieve higher levels of intelligence than the group members working alone. Despite these expectations of group advantage, many examples of collective failure have been documented—from market crashes to the spread of false and harmful rumors. To reconcile these results, a major effort in the study of collective decision making has been focused on understanding the role of group composition and communication patterns in promoting the "wisdom of the crowd" or, conversely, leading to "madness of the mob." In the past decades, much of this effort has been devoted to inferring the importance of a particular attribute, in isolation, by its capacity to explain the accuracy of collective judgments. In this thesis, we argue that such a perspective can lead to inconsistent conclusions: an `incoherency problem.' We assert that the importance of an individual-level or structural attribute may change as a function of the environment in which the group is situated. Hence, we propose a research agenda to investigate the relative importance of the group composition and the structure of interaction networks under an environment-dependent framework. We show that under such a framework, we can reconcile previously conflicting claims from the collective intelligence literature and motivate a future research program to identify stable principles of collective performance. Although implementing such a program is logistically challenging, "virtual lab" experiments of the sort discussed in this thesis, in combination with emerging "open science" practices such as pre-registration, data availability, open code, and "many-labs" collaborations, offer a promising route forward.

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