bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-Acting Insulin Analogs Versus Insulin Pump Therapy for the Treatment of Type 1 and Type 2 Diabetes
Authors: Pickup John C. , Renard Eric
Published: January 2008

Insulin pump therapy (continuous subcutaneous insulin infusion [CSII]) is now an established form of intensive insulin treatment. It is pertinent to ask, however, if multiple daily injection (MDI) regimens based on new long-acting insulin analogs such as glargine and detemir have now replaced the need for CSII. In type 1 diabetes, CSII reduces the frequency of severe hypoglycemia compared with isophane-based MDIs, but the rate of severe hypoglycemia is usually similar on glargine- or detemir-based MDIs compared with isophane-based MDIs. CSII reduces A1C and glycemic variability compared with isophane-based MDIs; but glargine and detemir do not improve A1C or variability in many patients, particularly those who are prone to hypoglycemia. Head-to-head comparisons of CSII with MDI based on glargine indicate lower A1C, fructosamine, or glucose levels on CSII. It can be concluded that long-acting insulin analogs have not yet replaced the need for insulin pump therapy in type 1 diabetes, and CSII is the best current therapeutic option for some type 1 diabetic subjects. In type 2 diabetes, CSII and MDI produce similar glycemic control, although there is little study of MDI based on long-acting analogs compared with pumps. It is possible that CSII will be beneficial in selected patient groups with type 2 diabetes, but this requires further study.
Islet Inflammation in Type 2 Diabetes
Authors: Donath Marc Y. , Schumann Desiree M. , Faulenbach Mirjam , Ellingsgaard Helga , Perren Aurel , Ehses Jan A.
Published: January 2008

Decreases in both mass and secretory function of insulin-producing β-cells contribute to the pathophysiology of type 2 diabetes. The histology of islets from patients with type 2 diabetes displays an inflammatory process characterized by the presence of cytokines, apoptotic cells, immune cell infiltration, amyloid deposits, and eventually fibrosis. This inflammatory process is probably the combined consequence of dyslipidemia, hyperglycemia, and increased circulating adipokines. Therefore, modulation of intra-islet inflammatory mediators, in particular interleukin-1β, appears as a promising therapeutic approach.
Is Pancreatic Diabetes (Type 3c Diabetes) Underdiagnosed and Misdiagnosed?
Authors: Hardt Philip D. , Brendel Mathias D. , Kloer Hans U. , Bretzel Reinhard G.
Published: January 2008

Exocrine pancreatic insufficiency is frequently associated with diabetes, with high prevalence in both insulin-dependent or insulin-independent patients. Exocrine pancreatic failure has often been perceived as a complication of diabetes. In contrast, recent clinical observations lead to the notion that nonendocrine pancreatic disease is a critical factor for development rather than a sequel to diabetes. The incidence of diabetes caused by exocrine pancreatic disease appears to be underestimated and may comprise 8% or more of the general diabetic patient population. Nonendocrine pancreas disease can cause diabetes by multiple mechanisms. Genetic defects have been characterized, resulting in a syndrome of both exocrine and endocrine failure. Regulation of β-cell mass and physiological incretin secretion are directly dependent on normal exocrine function. Algorithms for diagnosis and therapy of diabetes should therefore address both endocrine and exocrine pancreatic function.
Possible Role of Oxidative Stress in the Pathogenesis of Hypertension
Authors: Ceriello Antonio
Published: January 2008

Recently oxidative stress has been proposed as the cause of hypertension. An imbalance in superoxide and nitric oxide production may account for reduced vasodilation, which in turn can favor the development of hypertension. In vitro and in human studies support this hypothesis. The supplementation of antioxidants, particularly in the form of fresh fruit and vegetables, reduces blood pressure, supporting a role for free radicals in hypertension.
NADPH Oxidases, Reactive Oxygen Species, and Hypertension
Authors: Paravicini Tamara M. , Touyz Rhian M.
Published: January 2008

Reactive oxygen species (ROS) influence many physiological processes including host defense, hormone biosynthesis, fertilization, and cellular signaling. Increased ROS production (termed “oxidative stress”) has been implicated in various pathologies, including hypertension, atherosclerosis, diabetes, and chronic kidney disease. A major source for vascular and renal ROS is a family of nonphagocytic NAD(P)H oxidases, including the prototypic Nox2 homolog-based NAD(P)H oxidase, as well as other NAD(P)H oxidases, such as Nox1 and Nox4. Other possible sources include mitochondrial electron transport enzymes, xanthine oxidase, cyclooxygenase, lipoxygenase, and uncoupled nitric oxide synthase. NAD(P)H oxidase-derived ROS plays a physiological role in the regulation of endothelial function and vascular tone and a pathophysiological role in endothelial dysfunction, inflammation, hypertrophy, apoptosis, migration, fibrosis, angiogenesis, and rarefaction, important processes underlying cardiovascular and renal remodeling in hypertension and diabetes. These findings have evoked considerable interest because of the possibilities that therapies against nonphagocytic NAD(P)H oxidase to decrease ROS generation and/or strategies to increase nitric oxide (NO) availability and antioxidants may be useful in minimizing vascular injury and renal dysfunction and thereby prevent or regress target organ damage associated with hypertension and diabetes. Here we highlight current developments in the field of reactive oxygen species and cardiovascular disease, focusing specifically on the recently identified novel Nox family of NAD(P)H oxidases in hypertension. We also discuss the potential role of targeting ROS as a therapeutic possibility in the management of hypertension and cardiovascular disease.
Abnormal Glomerular Permeability Characteristics in Diabetic Nephropathy
Authors: Lewis Edmund J. , Xu Xiulong
Published: January 2008

The physicochemical characteristics of the glomerular capillary filtration membrane restrict the passage of macromolecules on the basis of molecular weight, charge, and shape. The proposed ionic charge permselectivity characteristics of the glomerular basement membrane (GBM) are determined by its chemical composition, primarily the highly sulfated glycosaminoglycan heparan. In diabetic nephropathy, the heparan sulfate content of the GBM is diminished. It has been proposed that decreased GBM heparan sulfate content causes decreased permselectivity to negatively charged macromolecules such as albumin, allowing this protein to leak into the urinary space. One possible explanation for decreased GBM heparan sulfate content in diabetic nephropathy is the observation that heparanase, an enzyme capable of degrading heparan sulfate, is upregulated in the glomerular epithelial cell (GEC) in response to increased glucose. Increased GEC heparanase activity has been demonstrated in glomeruli in diabetic kidneys, and increased urine heparanase has been observed in diabetic nephropathy. In vitro studies have shown that GEC heparanase activity depends on the glucose concentration of the culture medium. GEC heparanase activity can be inhibited by heparin compounds. Sulodexide, an orally active low–molecular weight heparin, has been shown to lower urine albumin excretion. The working hypothesis that has emerged is that sulodexide may be an in vivo heparanase inhibitor that reaches the glomerular capillary wall and prevents heparan sulfate degradation, thus allowing reconstruction of heparan sulfate content and restoration of GBM ionic permselectivity. Two clinical trials are currently being carried out to determine whether sulodexide is renoprotective in diabetic nephropathy.
Should We Be More Aggressive in the Therapy Against Cardiovascular Risk Factors?
Authors: Stirban Alin O. , Tschoepe Diethelm
Published: January 2008

The reality of primary and secondary prevention of cardiovascular complications in people with diabetes is alarming, even in developed countries with a well-structured medical system. Even though therapeutic targets have been more clearly defined during the last decades, their implementation is still suboptimal. Financial and structural reasons, insufficient information of physicians and patients, along with a low compliance of the latter are only a few reasons that have been incriminated. To eliminate some of these inconveniences, attempts to standardize and simplify therapies have been made. Treatment with aspirin and statin for every patient with diabetes has been postulated. Some went even further, developing the concept of a “polypill,” an integrated pharmacological agent with up to six different compounds meant to prevent cardiovascular disease in the broad population. Likewise, the idea of a “polymeal” tries to implement healthy nutrients into the populations’ lifestyle in a standardized fashion. Our article highlights some of the advantages and pitfalls of these concepts and reflects our point of view with regard to some treatment aspects in people with diabetes. As part of a pro and contra discussion, our article is arguing against the use of statins in all patients with diabetes and especially against the indiscriminate use of a polypill.
Primary Prevention of Cardiovascular Disease in People With Dysglycemia
Authors: Bianchi Cristina , Miccoli Roberto , Penno Giuseppe , Del Prato Stefano
Published: January 2008

Cardiovascular disease accounts for a great majority of deaths in patients with type 2 diabetes. According to the World Health Organization, the prevalence of cardiovascular disease in diabetic patients ranges from 26 to 36%. Fatality rate after myocardial infarction is greater in diabetic patients, and overall prognosis after coronary heart disease is worse. Based on these observations, it has been proposed that diabetes should be considered as a coronary heart disease risk equivalent. If that is the case, prevention of diabetes and early intervention should be pursued. This view is supported by the notion that cardiovascular risk is already increased in people with impaired glucose tolerance. Moreover, higher-than-optimum blood glucose is a major cause of cardiovascular mortality in most world regions of the world. Whether dysglycemia is a marker for a more complex metabolic condition or may directly contribute to excess cardiovascular risk is still a matter of debate. However, experimental work has shown how increased glucose level can trigger multiple mechanisms of susceptibility to atherosclerosis, and diabetes prevention trials have indicated that along with reduction of the rate of conversion toward diabetes, significant improvement in cardiovascular risk factors occurs. Moreover, in the STOP-NIDDM trial, targeting postprandial glucose was associated with reduction in new cases of hypertension, myocardial infarction, and any cardiovascular events. In conclusion, dysglycemia should be included in the list of established cardiovascular risk factors and early treatment introduced in the attempt to improve cardiovascular morbidity and mortality.
Cardiovascular Complications in Diabetes
Authors: Stirban Alin O. , Tschoepe Diethelm
Published: January 2008

Cardiovascular complications are mainly responsible for the high morbidity and mortality in people with diabetes. The awareness of physicians for the importance of primary prevention increased lately and numerous strategies have been developed. The spectrum ranges from pharmacologic treatment to vitamins and dietetic interventions. Some interesting concepts such as focusing on exogenous advanced glycation end products have emerged, but definitive results on their clinical relevance are still lacking. A major problem of the primary prevention is the choice of the method applied for screening, the criteria used to classify risk patients, as well as the choice of therapy. Guidelines provide goals to be achieved and offer alternatives for treatment, but the medical decision has to be made on an individualized basis. In this overview, we will comprehensively focus on the most important pathomechanisms and clinically relevant approaches, aiming at the early diagnosis and treatment of diabetes along with coronary heart disease. When primary prevention fails, we advocate a more aggressive treatment of critically ill patients, followed by optimal secondary prevention meeting on-target goals precisely.
Is Weight Loss Beneficial for Reduction of Morbidity and Mortality?
Authors: Nilsson Peter M.
Published: January 2008

The increase of obesity and type 2 diabetes on a global scale has increased the interest in how to counteract this epidemic. Improved lifestyle in general is a fundamental approach, but other remedies such as specific weight reduction or diabetes preventive drugs and surgery have also been tested. One problem to understand is what really happens after weight loss. Ongoing studies will try to address this question, such as the Swedish Obese Subjects (SOS) surgery study, the Look AHEAD (Action for Health in Diabetes) trial in the U.S. (recruiting obese type 2 diabetic patients), and the Comprehensive Rimonabant Evaluation Study of Cardiovascular End Points and Outcomes (CRESCENDO) trial (by use of rimonabant versus placebo). This is very important, since previously, several observational studies in large population-based cohorts have indicated some detrimental effects of weight loss, even after intentional weight loss, with increased morbidity and mortality rates.
Can Gut Hormones Control Appetite and Prevent Obesity?
Authors: Chaudhri Owais B. , Wynne Katie , Bloom Stephen R.
Published: January 2008

The current obesity epidemic is fuelled by the availability of highly palatable, calorie-dense food, and the low requirement for physical activity in our modern environment. If energy intake exceeds energy use, the excess calories are stored as body fat. Although the body has mechanisms that act to maintain body weight over time, they primarily defend against starvation and are less robust in preventing the development of obesity. Knowledge of this homeostatic system that controls body weight has increased exponentially over the last decade and has revealed new possibilities for the treatment of obesity and its associated comorbidities. One therapeutic target is the development of agents based on the gastrointestinal hormones that control appetite. This review discusses the hormones oxyntomodulin, peptide YY, glucagon-like peptide 1, pancreatic polypeptide, and ghrelin and their emerging potential as anti-obesity treatments.
Metabolic Complications of Childhood Obesity
Authors: Weiss Ram , Kaufman Francine Ratner
Published: January 2008

The growing number of obese children and adolescents across the world creates a diagnostic challenge to caregivers. The early clinical manifestations of abnormalities related to childhood obesity, attributed to obesity-driven insulin resistance, are impaired glucose metabolism and nonalcoholic fatty liver disease. Both have no symptoms and demand a high index of suspicion and the proper choice of tests for establishing the diagnosis. The clinician should gather information derived from thoroughly taken history and a focused physical examination to stratify patients by their risk. Focused lifestyle modification–aimed interventions are showing promising results in improving the metabolic profile of obese children. Early diagnosis may help allocate resources for intensive interventions that may benefit individuals at greatest risk for early obesity-related morbidity.
The Umpires Strike Back: Canadian Judicial Experience with Risk-Assessment Instruments
Authors: Cole Justice David P.
Published: January 2008

As Canadian correctional policy makers have begun to embed usage of risk-assessment instruments in various forms of penal and probation decision making, judges are frequently being asked to rule upon their admissibility and evidentiary relevance in a variety of contexts, most particularly sentencing. Judges have commented in a number of contexts to date: non-disclosure (by counsel or by correctional officials) of the fact that a risk-assessment instrument is being used; the use of “ministry override” policies for certain offences; the qualifications of the assessor; and the information used to formulate the assessment. At a broader level, judges have joined academic commentators in expressing concerns that over-reliance on risk assessment may trump proportionality.
Modeling Learning in Route Choice
Authors: Bogers Enide A. I. , Bierlaire Michel , Hoogendoorn Serge P.
Published: January 2008

Performing the same trip many times, travelers can learn about available routes from their experiences. Two types of learning found in psychological learning theory appear to play a role in day-to-day route choice: implicit (reinforcement-based) and explicit (belief-based). Memory decay also plays a major role. Although much progress had been made in modeling learning in route choice, a model that captures both learning types and for which the parameters are empirically underpinned was not found. Such a model thus is developed, and a large data set from experimental research is used to validate it and to estimate its parameters. The developed model uses a Markov formulation for the day-to-day updating of a person's belief about travel time (i.e., perceived travel time) on a route. Reinforcement (and inertia) is modeled by including the latest 10 route choices in the model. Results indicate that 20% of perceived travel time is from the most recent experience; therefore, formulations that use either the mathematical mean of all past experienced travel times or only the most recent travel times are not accurate. Furthermore, the reinforcement–inertia part of the model can make up a significant part of the route utility and therefore should be a standard component in route choice models. In sum, the results validate the theoretical and mathematical model.
Nonlinearity and Specification of Attitudes toward Risk in Discrete Choice Models
Authors: Liu Xiang , Polak John W.
Published: January 2008

Recent work in travel demand modeling has sought to address decision making under risk and uncertainty by bringing together elements of expected utility theory (EUT) and random utility theory (RUT). The aims are to identify and discuss the key theoretical issues associated with the merging of EUT and RUT in a transport context and then to explore the many empirical issues associated with the specification of attitudes to risk. Specifically, the performance of the alternative specification of attitudes to risk is investigated with the use of data from a large stated-preference exercise in which respondents were faced with a series of choices between alternative unreliable train services.
Defining Sampling Districts for Household Travel Surveys
Authors: Nuworsoo Cornelius
Published: January 2008

The character of land development affects the trip-making behavior of residents. The case is made for the careful demarcation of survey sampling districts from which to collect household travel data for forecasting travel demand. Household travel survey data from the Baltimore, Maryland, metropolitan area indicate that trip generation rates derived from areas with similar intensities of land development are more consistent than those derived according to political jurisdictions. Additional data from the Portland, Oregon, metropolitan area support this hypothesis. In light of current and previous findings, trip rates for metropolitan areas clearly should be derived from and applied to areas of homogeneous character in recognition of the effects of density and mixture of land uses on trip making. This assertion is illustrated with empirical data from the Baltimore metropolitan area. Conceptually, area type is more appealing than demarcations by political jurisdictions. Results of visual plots and numerical analyses show distinctive differences between the density classes but not as much between jurisdictions. A comparison of these results indicates that area type is the more superior form of stratification. Defining area type by density can reasonably capture future changes in land-use and activity patterns. The refinement suggested for the demarcation of sampling districts in the conduct of travel surveys is widely applicable to metropolitan areas around the country.
Catching the Next Big Wave
Authors: Goulias Konstadinos G. , Blain Larry , Kilgren Neil , Michalowski Timothy , Murakami Elaine
Published: January 2008

The aging of American baby boomers creates various new policy contexts and problems. Depending on institutional preparedness and baby boomers’ behavior, the changing demand for transportation services by this group may be positive or negative. This potential change in demand is described through an analysis of individual longitudinal histories over a long period (1989 to 2003) that explores the effects of personal changes (e.g., entry to and exit from the labor force), household changes (e.g., relocation and dissolution), and changes in land use characteristics. The Puget Sound Transportation Panel (PSTP)—a record of approximately 20,000 travel diaries of Seattle residents, each of whom provided 2-day reports for 10 repeated contacts (waves)—was used. Within-household dynamics and the effect of within-household change on individual and household behavior are studied. Focus groups are used to extract behavioral themes, latent class cluster analysis is used to identify groups of behavior, and an array of regression models of change is used to identify the key determinants that underlie behavioral dynamics. Findings include a need to focus on employment, heterogeneity in land use impact, and the significant effect of household composition. Together, the findings imply the need for models that can handle more diverse behavior and the need to accommodate employment status and within-household demographics in forecasting models.
Creating Synthetic Household Populations
Authors: Arentze Theo , Timmermans Harry , Hofman Frank
Published: January 2008

A method based on iterative proportional fitting (IPF) is developed for generating synthetic populations for the application of Albatross, a rule-based and activity-based model of travel demand. The Dutch Travel Survey (OVG) provides sample data for populations to be synthesized by zone. A method is proposed to generate synthetic households on the basis of data on distributions of individuals. This method uses the concept of relation matrices to convert distributions of individuals to distributions of households in a preprocessing step. Furthermore, a method is proposed to address differences in populations that relate to locational characteristics.
Developing Indicators for Comprehensive and Sustainable Transport Planning
Authors: Litman Todd
Published: January 2008

This paper discusses the selection of indicators for comprehensive and sustainable transportation planning. It discusses the concept of sustainability and the role of indicators in planning, describes factors to consider in selecting indicators, identifies potential problems with conventional indicators, describes examples of indicators, and provides recommendations for selecting indicators for use in a particular situation.
Using Global Positioning System Travel Data to Assess Real-World Energy Use of Plug-In Hybrid Electric Vehicles
Authors: Gonder Jeffrey , Markel Tony , Thornton Matthew , Simpson Andrew
Published: January 2008

Plug-in hybrid electric vehicles (PHEVs) have received considerable recent attention for their potential to reduce petroleum consumption significantly and quickly in the transportation sector. Analysis to aid the design of such vehicles and predict their real-world performance and fuel displacement must consider the driving patterns the vehicles will typically encounter. This paper goes beyond consideration of standardized certification cycless by leveraging state-of-the-art travel survey techniques that use Global Positioning System (GPS) technology to obtain a large set of real-world drive cycles from the surveyed vehicle fleet. This study specifically extracts 24-h, second-by-second driving profiles from a set of 227 GPS-instrumented vehicles in the St. Louis, Missouri, metropolitan area. The performance of midsize conventional, hybrid electric, and PHEV models is then simulated over the 227 full-day driving profiles to assess fuel consumption and operating characteristics of these vehicle technologies over a set of real-world usage patterns. In comparison to standard cycles used for certification procedures, the travel survey duty cycles include significantly more aggressive acceleration and deceleration events across the velocity spectrum, which affect vehicle operation and efficiency. Even under these more aggressive operating conditions, PHEVs using a blended charge-depleting energy management strategy consume less than 50% of the petroleum used by similar conventional vehicles. Although true prediction of the widespread real-world use of these vehicles requires expansion of the vehicle sample size and a refined accounting for the possible interaction of several variables with the sampled driving profiles, this study demonstrates a cutting-edge use of available GPS travel survey data to analyze the (highly drive cycle–dependent) performance of advanced technology PHEVs. This demonstration highlights new opportunities for using innovative GPS travel survey techniques and sophisticated vehicle system simulation tools to guide vehicle design improvements and to maximize the benefits offered by energy efficiency technologies.
Diesel and Hybrids Don't Mix
Authors: Gerard David , Fischbeck Paul S. , Mathews H. Scott
Published: January 2008

Hybrid gasoline–electric and fuel-efficient, low-emission diesels are becoming more popular as these technologies improve and fuel prices increase. In Europe, light-duty diesels are the technology of choice for many consumers (“good, clean, green fun”), while in the United States, diesels face significant regulatory certification hurdles. Moreover, U.S. consumers are more interested in hybrids as a solution for improving fuel efficiency and reducing CO2 emissions. The objective of this paper is to assess U.S. attitudes about hybrid and diesel technologies and behavior of those who purchase these technologies. With survey research, the attitudes of likely diesel and hybrid new car buyers are compared, and the actual driving behavior of new owners of diesels and hybrids is examined. Significant differences were found in both cases. Significant attitudinal differences exist across 20 questions spanning regulatory and environmental issues, with likely hybrid buyers being more environmentally concerned and willing to accept tougher regulatory standards. Hybrid drivers logged fewer annual miles and had a higher percentage of in-city driving. Hybrid buyers generally traded in vehicles that were newer, had better fuel economy, and had smaller engines than did diesel buyers. Both hybrid and diesel drivers saw significant fuel savings with their new vehicles. Because of the bigger improvement from their previous cars and the greater number of miles per year that they drove, however, diesel owners saved more fuel than did new hybrid owners (420 gal per year compared with 275 gal). Acknowledging these differences in public attitudes and behavior is a necessary first step in the development of strategies to reduce mobile source greenhouse gas emissions.
Macroeconomic Effects of Climate Policies on Road Transport
Authors: Barker Terry , Rubin Jonathan
Published: January 2008

This paper reports a study modeling climate policies in the United Kingdom for road transportation over the period 2000 to 2010. Estimates of the effects of fuel-economy policies are introduced into the energy-demand equation for transport in a top-down dynamic econometric model of the UK economy with 50 industrial sectors, MDM-E3. This allows estimation of the effects of the reduced energy use for the transport sector on demand (both in the United Kingdom and in the export markets). The model is solved as a counterfactual for 2000 to 2005 and as a projection for 2005 to 2010 in a series of scenarios that compare voluntary agreements in fuel economy improvements with UK fuel taxes giving the same reduction in CO2 emissions. The systemwide final energy reductions are estimated to be 2.9 million tons of oil equivalent, or 1.8%, of total final demand for energy by 2010. Voluntary agreements (VAs) were found to yield positive macroeconomic effects, with small increases in GDP and employment and small reductions in general inflation. In contrast, fuel taxes set at a level to achieve the same amount of CO2 reductions raise prices and lower gross domestic product (GDP) and employment. If fuel duties are recycled in the economy, reducing income taxes, then the undesirable macroeconomic impacts of fuel duties can be largely eliminated. To the extent that VAs are viewed by vehicle manufacturers as a substitute for mandated fuel economy improvements, it is possible to compare the relative effects of standards and taxes in the light-duty transport sector in reducing CO2 emissions.
Nonintrusive Detection of Driver Cognitive Distraction in Real Time Using Bayesian Networks
Authors: Liang Yulan , Lee John D. , Reyes Michelle L.
Published: January 2008

Driver distraction has become an important and growing safety concern as the use of in-vehicle information systems (IVISs), such as cell phones and navigation systems, continues to increase. One approach to allowing people to benefit from IVISs without compromising safety is to create adaptive IVISs that adjust their functions according to driver and roadway state. A critical element of adaptive IVISs involves monitoring driver distraction in real time; with such a monitoring function it is possible to mitigate that distraction. This study applied Bayesian networks (BNs), a data mining method, to develop a real-time approach to detecting cognitive distraction using drivers’ eye movements and driving performance. Data were collected in a simulator experiment involving 10 participants who interacted with an IVIS system while driving. BN models were trained and tested to investigate the influence of three model characteristics on distraction detection: time history of driver behavior, inclusion of hidden nodes in the model structure, and how data are summarized and the length of training sequences. Results showed that BNs could identify driver distraction reliably with an average accuracy of 80.1%. Dynamic BNs (DBNs) that consider time dependencies of driver behavior produced more sensitive models than static BNs (SBNs). Longer training sequences improved DBN model performance. Blink frequency and fixation measures were particularly indicative of distraction. These results demonstrate that BNs, especially DBNs, can detect driver cognitive distraction by extracting information from complex behavioral data. Potential applications include the design of adaptive in-vehicle systems and the evaluation of driver distraction.
Driving without a Clue
Authors: Muttart Jeffrey W. , Fisher Donald L. , Knodler Mike , Pollatsek Alexander
Published: January 2008

Crashes continue to be a problem in work zones. Analyses have indicated that rear-end and sideswipe crashes are the most frequent. Investigators have hypothesized that distractions are often the cause of both types of crashes. These distractions will only increase as more drivers attend to other tasks, such as cell phone conversations. To address this issue, virtual worlds that reflect various work zone geometries were developed for an advanced driving simulator. The worlds contained 32 virtual work zones; 38 drivers navigated through these worlds. On one portion of a trip, drivers were asked to respond to a series of short sentences that mimicked a hands-free cell phone conversation. A lead vehicle ahead of the participant driver braked occasionally in the work zone activity area. Braking scenarios involved either the lead vehicle stopping after an advanced clue that traffic ahead would stop or the lead vehicle stopping for no apparent reason, most often after passing a roadside obstacle (potential distraction). Drivers not engaged in a cell phone task were able to reduce their speed earlier in response to a slowing lead vehicle than were drivers engaged in the cell phone task. The drivers not engaged in a cell phone task were also less likely to brake hard and more likely to make a mirror glance when changing lanes. Finally, they scanned almost twice as far to the left and right. Results strongly suggest that cell phone use reduces driver awareness and may increase the likelihood of a crash in work zone activity areas.
Influence of Roadside Infrastructure on Driving Behavior
Authors: van der Horst Richard , de Ridder Selma
Published: January 2008

This paper describes the results of a driving simulator study that focused on the influence of roadside infrastructure on drivers’ speed choice and the lateral placement of their vehicles. A review of the Roadside Infrastructure for Safer European Roads detailed accident database revealed that lateral positioning and speed of the vehicle were two of the primary factors leading to crashes. The driving simulator study served as a means to include human factor principles into roadside infrastructure guidelines. Roadside features studied included trees, guardrails, barriers, panels, and emergency lanes. It was found that drivers tended to move away laterally from safety barriers when they first approached them and that they slightly slowed down. The type and size of a safety barrier appeared to be less important; only its presence had an effect. Trees were not found to affect the speed of the driver unless they were close (2 m) to the road edge on a rural road with an 80-km/h speed limit, and this effect faded rather quickly. There was no influence on speed if the trees were more than 4.5 m from the lane edge. The fact that trees along the road are not considered to be a hazard, with drivers not adjusting their behavior, makes trees even more dangerous.
Evaluating Effect of Two Allowable Permissive Left-Turn Indications
Authors: Knodler Michael A. , Noyce David A. , Fisher Donald L.
Published: January 2008

NCHRP Report 493 recommended that a flashing yellow arrow (FYA) permissive indication be included in the Manual on Uniform Traffic Control Devices as an alternative option to the circular green (CG). However, as implementation of the FYA permissive indication proceeds, there will be two permissive indications for practitioners to consider at protected–permissive left-turn applications. Using two signal indications that provide drivers with the same message has the potential to increase driver error. Specifically, once drivers are exposed to and understand the meaning of the FYA, it is unclear as to expectancy violations and the likelihood of incorrect interpretation of the CG as a protected left-turn indication. This research employed a multifaceted behavioral experiment, including a dynamic driving simulator experiment and computer-based static evaluations, to quantify any change in driver comprehension of CG indications resulting from the FYA permissive indication. In the simulator, comprehension of the CG permissive indication following exposure to the FYA permissive indication did not differ significantly from driver comprehension of the CG before exposure to the FYA. In a follow-up static evaluation, drivers exposed to the FYA permissive indication were actually more likely to give yield (correct) responses to the CG permissive indication. In a separate independent static evaluation of 100 drivers, the breakdown of responses did not differ statistically from responses collected before and after exposure to the FYA. Results provide little evidence to suggest that the FYA implementation will affect driver comprehension of the CG.
Drivers’ Preferences for Traffic Information for Nonrecurrent Traffic Situations
Authors: Muizelaar Thijs J. , van Arem Bart
Published: January 2008

The field of advanced traveler information systems (ATIS) has seen many improvements in the past years. These systems are developed to allow drivers or travelers to make better travel choices about travel time reduction or route choice. If such a system is to be generally accepted by drivers, it is necessary to know drivers’ preferences for traffic information content, as well as the characteristics of the information the system provides. These preferences should be known for all types of drivers and for all kinds of situations. This paper presents results of a study of these preferences. Although several studies have addressed the subject, little is known about preferences in nonrecurrent traffic situations. By means of an Internet survey, Dutch drivers were asked for their preferences concerning the content of traffic information for different nonrecurrent traffic situations. Statistical testing shows that drivers’ preferences differ according to the situation. Important driver characteristics influencing these preferences are current use of the information, driver type, and driver age. Drivers were also asked to choose between different information types, with different characteristics for a generic situation. Results were analyzed with a multinomial logit model. The most important characteristic of the information was cost; however, reliability and timeliness also contributed significantly to the utility of traffic information. Findings indicate that ATIS should be strongly adaptive to the driver and to the traffic situations at hand.
Empirical Evaluation of Hazard Anticipation Behaviors in the Field and on Driving Simulator Using Eye Tracker
Authors: Fisher Donald L. , Pradhan Anuj K. , Pollatsek Alexander , Knodler Michael A.
Published: January 2008

Eye behaviors have been used with driving simulators to evaluate the effectiveness of novice and older driver training programs. Driving simulators are often favored when drivers must be placed in risky situations. Because there was no study of whether eye behaviors observed on a driving simulator in risky scenarios were also observed in the field, the authors had both trained and untrained novice drivers maneuver a controlled set of 10 scenarios on a driving simulator. The scenarios were similar to a set of scenarios that a different, matched set of trained and untrained drivers had navigated in the field. Drivers in this simulator study were trained with the same PC program used by drivers in the field study. Five of the scenarios that the trained drivers saw on the simulator and in the field were similar to those seen in training on a PC (near transfer); the other five were similar in concept to those in training but different in surface features (far transfer). A fixation on the region of a scenario that had information relevant to identifying a risk was scored as recognizing the risk. On the simulator, trained drivers recognized the risk 41.7% more often than untrained drivers in the near-transfer scenarios and 32.6% more often in the far-transfer scenarios. In the field, trained drivers recognized the risk 38.8% more often in the near-transfer and 20.1% more often in the far-transfer scenarios. Both effects were highly significant, and the difference between them was not close to significant. Thus results from tests on a simulator have a close correspondence with those in the field.
Statistical Analysis of Driver Behavior Data in Different Regimes of the Car-Following Stage
Authors: Ma Xiaoliang , Andréasson Ingmar
Published: January 2008

An instrumented vehicle has been used to study car-following behavior on Swedish motorways. In this study, the previous data collection and preprocessing work were briefly reviewed. To understand the driving behavior in the car-following stage more clearly, the collected time series were classified into a number of regimes using unsupervised fuzzy clustering methods. Then, the statistical relations between the driver acceleration response and the perceptual variables in each regime were analyzed using correlation and regression methods. It was found that regime classification helps discern the behavioral variance between those regime clusters. According to the data analysis, some of the car-following regimes, for example, opening and braking, can be described adequately in the statistical sense by a linear regression model (Helly's model). Therefore, a multiple regime car-following model with simple model forms, for example, linear models, has the potential to robustly represent the general car-following behavior in most regimes.
Wide-Area, Four-Dimensional, Real-Time Interactive Transportation System Visualization
Authors: Pack Michael L. , Weisberg Phillip , Bista Sujal
Published: January 2008

The four-dimensional (4-D), wide-area traffic visualization tool provides incident management personnel, emergency management personnel, and the general public with the means to achieve situational awareness in as close to a real-world setting as possible. This research developed a system for visualizing 4-D (in which the fourth dimension is time), real-time transportation data for the entire Earth, although only data for the road networks of Washington, D.C.; Northern Virginia; and the entire state of Maryland are currently in the system. This effort employed a combination of technologies including OpenGL and various modeling techniques to develop a scalable, highly interactive 4-D model using available geographic information system (GIS) and transportation infrastructure data in conjunction with real-time traffic management center data. The prototype system interacts with real-time traffic databases to show animations of real-time traffic data (volume and speed) along with incident data (accident locations, lane closures, responding agencies, etc.) and weather data. A user can “fly” or “drive” through the region to inspect conditions at an infinite number of angles and distances. The program also allows users to monitor the status of and interact with traffic control devices such as dynamic message signs, closed circuit television feeds, and traffic sensors; users can even view the location of a fleet of vehicles equipped with Global Positioning System transponders. Because the system uses standard GIS data and relatively standard transportation databases to derive traffic measures, the system can be scaled to incorporate other states, agencies, or countries.
Data Collection Based on Global Positioning System for Travel Time and Delay for Arterial Roadway Network
Authors: Pan Changxuan , Lu Jiangang , Wang Dawei , Ran Bin
Published: January 2008

This paper proposes a Global Positioning System (GPS) based method for collecting historical travel time data, including link travel time and intersection signal delay information, for an arterial roadway network. A posttrip map-matching algorithm is introduced to project GPS data onto an existing arterial roadway network. A model is formulated by analyzing the three critical factors–minimum distance, direction similarity, and speed comparison error–in the map-matching decision to detect the critical points needed to obtain the intersection delay information. Two GPS data sets with different GPS accuracy–from Shanghai, China, and Aachen, Germany–are used in the study to calibrate and verify the posttrip map-matching algorithm. Then, through the model proposed, travel time and intersection delay information is extracted from the GPS data sets. By a comparison with results from electronic distance-measuring instrument data, the results of the experiment are shown to be satisfactory and compelling.
Bayesian Approach Based on Geographic Information System to Identify Hazardous Roadway Segments for Traffic Crashes
Authors: Li Linhua , Zhang Yunlong
Published: January 2008

This paper presents a Bayesian approach based on a geographic information system (GIS) for areawide identification of hazardous roadway segments for traffic crashes. The conventional observed relative crash risks of roadway segments are based on the observed crash count data and often feature very small or very large outlying relative risks in segments with low traffic volumes or short segment lengths; thus the risk maps based on observed crash risks show a high uncertainty. The Bayesian approach can incorporate both the variability in the observed risks and spatial autocorrelation and use the typical Bayesian “borrow of strength” from adjacent segments to filter out the uncertainties, smooth the relative risks, and accurately identify and rank roadway segments with potentially high relative risks for crashes. To capture the real safety indications better, this paper also disaggregates different road segment types and utilizes GIS to analyze the crash data and visualize the spatial relative crash risks in three-dimensional views. Houston, Texas, is chosen as the study area, and three crash data sets (all KAB crashes: crashes with fatality [K], incapacitating injury [A], and nonincapacitating injury [B]; KAB crashes under unsafe speeding; and KAB crashes under the influence of alcohol) in year 2000 are analyzed. Results demonstrate that the approach is effective in spatially smoothing the relative crash risks and eliminating the instability of estimates, while maintaining real safety trends, especially for data with a small sample size and large variance. The result provides a sound basis for implementing preventive actions to reduce crashes on high-risk segments.
Wavelet-Based Pavement Distress Image Edge Detection with À Trous Algorithm
Authors: Wang Kelvin C. P. , Li Qiang , Gong Weiguo
Published: January 2008

Edge detection is an alternative method in the process for identifying and classifying pavement cracks for automated pavement evaluation systems. A number of edge detectors are widely used in image processing; most specify only a spatial scale for detecting edges. However, pavement surface images frequently have various details at different scales. Therefore, wavelet-based multiscale technique can be a candidate to extract edge information from pavement surface images. Instead of detecting edges in the space domain, wavelet analysis has the ability to describe both domains in time and in frequency. It was first applied in image edge detection in 1992, using the local maximum of the magnitude of the gradient to obtain edge representation. Nevertheless, this subsampling algorithm leads to a loss of translation variance and may produce many artifacts. In this paper, wavelet edge detection based on à trous algorithm (holes algorithm) is used in pavement distress segmentation. This algorithm is an undecimated wavelet transform executed via a filter bank without subsampling process. Translation invariance is one of its most important advantages. Therefore, the algorithm can minimize the artifact in the denoised data. Results of experiments on images are discussed in the paper. By comparisons with the results derived from five other traditional edge detectors, the study demonstrates the validity and effectiveness of this method for edge detection of pavement surface distresses.
Forecasting of Short-Term Freeway Volume with v-Support Vector Machines
Authors: Zhang Yunlong , Xie Yuanchang
Published: January 2008

Predictions for short-term traffic volume provide important inputs for traveler information and traffic management. Traffic volumes in the near future are often estimated based on historical volumes. Because of the complicated nonlinear relationship between historical and future traffic volume data, many previous studies used neural networks to predict short-term traffic volumes. In this research, a v-support vector machine (v-SVM) model, which has the particular strength of overcoming local minima and overfitting common to neural network models, is proposed for short-term traffic volume prediction. The v-SVM model is compared with a widely used multilayer feed-forward neural network (MLFNN) model using four data sets collected from three interstate freeways. Testing results show that for both one-step and two-step forecasting, the v-SVM model outperforms the MLFNN model for all data sets in terms of mean absolute percentage error and root-mean-square error. Key issues in applying both models are also discussed in this article.