997 resultados para crash analysis
Resumo:
In 2010, 16.5 percent of all fatal vehicle crashes in Iowa involved large trucks compared to the national average of 7.8 percent. Only about 16 percent of these fatalities involved the occupants of the heavy vehicles, meaning that a majority of the fatalities in fatal crashes involve non-heavy-truck occupants. These statistics demonstrate the severe nature of heavy-truck crashes and underscore the serious impact that these crashes can have on the traveling public. These statistics also indicate Iowa may have a disproportionately higher safety risk compared to the nation with respect to heavy-truck safety. Several national studies, and a few statewide studies, have investigated large-truck crashes; however, no rigorous analysis of heavy-truck crashes has been conducted for Iowa. The objective of this study was to investigate and identify the causes, locations, and other factors related to heavy-truck crashes in Iowa with the goal of reducing crashes and promoting safety. To achieve this objective, this study used the most current statewide data of heavy-truck crashes in Iowa. This study also attempted to assess crash experience with respect to length of commercial driver’s license (CDL) licensure using the most recent five years of CDL data linked to the before mentioned crash data. In addition, this study used inspection and citation data from the Iowa Department of Transportation (DOT) Motor Vehicle Division and Iowa State Patrol to investigate the relationship between enforcement activities and crash experience.
Resumo:
The highway system in the State of Iowa includes many grade separation structures constructed to provide maximum safety and mobility to road users on intersecting roadways. However, these structures can present possible safety concerns for traffic passing underneath due to close proximity of piers and abutments. Shielding of these potential hazards has been a design consideration for many years. This study examines historical crash experience in the State of Iowa to address the advisability of shielding bridge piers and abutments as well as other structure support elements considering the offset from the traveled way. A survey of nine Midwestern states showed that six states had bridge pier shielding practices consistent with those in Iowa. Data used for the analyses include crash data (2001 to 2007) from the Iowa Department of Transportation (Iowa DOT), the Iowa DOT’s Geographic Information Management System (GIMS) structure and roadway data (2006) obtained from the Office of Transportation Data, and shielding and offset data for the bridges of interest. Additionally, original crash reports and the Iowa DOT video log were also utilized as needed. Grade-separated structures over high-speed, multilane divided Interstate and primary highways were selected for analysis, including 566 bridges over roadways with a speed limit of at least 45 mph. Bridges that met the criteria for inclusion in the study were identified for further analysis using crash data. The study also included economic analysis for possible shielding improvement.
Resumo:
Although many larger Iowa cities have staff traffic engineers who have a dedicated interest in safety, smaller jurisdictions do not. Rural agencies and small communities must rely on consultants, if available, or local staff to identify locations with a high number of crashes and to devise mitigating measures. However, smaller agencies in Iowa have other available options to receive assistance in obtaining and interpreting crash data. These options are addressed in this manual. Many proposed road improvements or alternatives can be evaluated using methods that do not require in-depth engineering analysis. The Iowa Department of Transportation (DOT) supported developing this manual to provide a tool that assists communities and rural agencies in identifying and analyzing local roadway-related traffic safety concerns. In the past, a limited number of traffic safety professionals had access to adequate tools and training to evaluate potential safety problems quickly and efficiently and select possible solutions. Present-day programs and information are much more conducive to the widespread dissemination of crash data, mapping, data comparison, and alternative selections and comparisons. Information is available and in formats that do not require specialized training to understand and use. This manual describes several methods for reviewing crash data at a given location, identifying possible contributing causes, selecting countermeasures, and conducting economic analyses for the proposed mitigation. The Federal Highway Administration (FHWA) has also developed other analysis tools, which are described in the manual. This manual can also serve as a reference for traffic engineers and other analysts.
Resumo:
Photographic documentation of crashed vehicles at the scene can be used to improve triage of crash victims. A U.S. expert panel developed field triage rules to determine the likelihood of occupants sustaining serious injuries based on vehicle damage that would require transport to a trauma center (Sasser et al., 2011). The use of photographs for assessing vehicle damage and occupant compartment intrusion as it correlates to increased injury severity has been validated (Davidson et al., 2014). Providing trauma staff with crash scene photos remotely could assist them in predicting injuries. This would allow trauma care providers to assess the appropriate transport, as well as develop mental models of treatment options prior to patient arrival at the emergency department (ED). Crash-scene medical response has improved tremendously in the past 20-30 years. This is in part due to the increasing number of paramedics who now have advanced life support (ALS) training that allows independence in the field. However, while this advanced training provides a more streamlined field treatment protocol, it also means that paramedics focused on treating crash victims may not have time to communicate with trauma centers regarding crash injury mechanisms. As a result, trauma centers may not learn about severe trauma patients until just a few minutes before they arrive. The information transmitted by the TraumaHawk app allows interpretation of injury mechanisms from crash scene photos at the trauma center, providing clues about the type and severity of injury. With strategic crash scene photo documentation, trained trauma professionals can assess the severity and patterns of injury based on exterior crush and occupant intrusion. Intrusion increases the force experienced by vehicle occupants, which translates into a higher level of injury severity (Tencer et al., 2005; Assal et al., 2002; Mandell et al., 2010). First responders have the unique opportunity to assess the damaged vehicle at the crash scene, but often the mechanism of injury is limited or not even relayed to ED trauma staff. To integrate photographic and scene information, an app called TraumaHawk was created to capture images of crash vehicles and send them electronically to the trauma center. If efficiently implemented, it provides the potential advantage of increasing lead-time for preparation at the trauma center through the crash scene photos. Ideally, the result is better treatment outcomes for crash victims. The objective of this analysis was to examine if the extra lead-time granted by the TraumaHawk app could improve trauma team activation time over the current conventional communication method.
Resumo:
This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.
Resumo:
Iowa features an extensive surface transportation system, with more than 110,000 miles of roadway, most of which is under the jurisdiction of local agencies. Given that Iowa is a lower-population state, most of this mileage is located in rural areas that exhibit low traffic volumes of less than 400 vehicles per day. However, these low-volume rural roads also account for about half of all recorded traffic crashes in Iowa, including a high percentage of fatal and major injury crashes. This study was undertaken to examine these crashes, identify major contributing causes, and develop low-cost strategies for reducing the incidence of these crashes. Iowa’s extensive crash and roadway system databases were utilized to obtain needed data. Using descriptive statistics, a test of proportions, and crash modeling, various classes of rural secondary roads were compared to similar state of Iowa controlled roads in crash frequency, severity, density, and rate for numerous selected factors that could contribute to crashes. The results of this study allowed the drawing of conclusions as to common contributing factors for crashes on low-volume rural roads, both paved and unpaved. Due to identified higher crash statistics, particular interest was drawn to unpaved rural roads with traffic volumes greater than 100 vehicles per day. Recommendations for addressing these crashes with low-cost mitigation are also included. Because of the isolated nature of traffic crashes on low-volume roads, a systemic or mass action approach to safety mitigation was recommended for an identified subset of the entire system. In addition, future development of a reliable crash prediction model is described.
Resumo:
This analysis examined data from a variety of sources to estimate the benefit of enhancing Iowa’s current law to require all passengers to use seat belts. In addition to assessing Iowans’ opinions about changing the law, a literature review, a legislative policy review, and analysis of Iowa crash data were completed. Currently 28 states enforce seat belt laws for all passengers. Belted passengers riding with an unbelted passenger are 2 to 5 times more likely to suffer fatal injuries in a crash relative to when all occupants are using seat belts. Iowans are highly compliant (90%-94%) with the current seat belt law for front seat occupants. Of more than 1000 Iowans surveyed, 85% said they always use a seat belt when riding in the front seat, but only 36% always do so when they ride in the back seat. The most common reasons given for not using seat belts in the back seat are forgetting to buckle up and because it is not the law. Iowans widely support strengthening Iowa’s seat belt law — 62% said Iowa law should require all rear seat passengers to use seat belts. Four out of five respondents said they would use seat belts more often when sitting in the rear seat if it was the law. It is estimated rear seat fatalities would decrease about 48%, from 13 to 7 fatalities annually, if an all-passenger law was implemented in Iowa.
Resumo:
The purpose of this study is to examine macroeconomic indicators‟ and technical analysis‟ ability to signal market crashes. Indicators examined were Yield Spread, The Purchasing Managers Index and the Consumer Confidence Index. Technical Analysis indicators were moving average, Moving Average Convergence-Divergence and Relative Strength Index. We studied if commonly used macroeconomic indicators can be used as a warning system for a stock market crashes as well. The hypothesis is that the signals of recession can be used as signals of stock market crash and that way a basis for a hedging strategy. The data is collected from the U.S. markets from the years 1983-2010. Empirical studies show that macroeconomic indicators have been able to explain the future GDP development in the U.S. in research period and they were statistically significant. A hedging strategy that combined the signals of yield spread and Consumer Confidence Index gave most useful results as a basis of a hedging strategy in selected time period. It was able to outperform buy-and-hold strategy as well as all of the technical indicator based hedging strategies.
Resumo:
Modern computer systems are plagued with stability and security problems: applications lose data, web servers are hacked, and systems crash under heavy load. Many of these problems or anomalies arise from rare program behavior caused by attacks or errors. A substantial percentage of the web-based attacks are due to buffer overflows. Many methods have been devised to detect and prevent anomalous situations that arise from buffer overflows. The current state-of-art of anomaly detection systems is relatively primitive and mainly depend on static code checking to take care of buffer overflow attacks. For protection, Stack Guards and I-leap Guards are also used in wide varieties.This dissertation proposes an anomaly detection system, based on frequencies of system calls in the system call trace. System call traces represented as frequency sequences are profiled using sequence sets. A sequence set is identified by the starting sequence and frequencies of specific system calls. The deviations of the current input sequence from the corresponding normal profile in the frequency pattern of system calls is computed and expressed as an anomaly score. A simple Bayesian model is used for an accurate detection.Experimental results are reported which show that frequency of system calls represented using sequence sets, captures the normal behavior of programs under normal conditions of usage. This captured behavior allows the system to detect anomalies with a low rate of false positives. Data are presented which show that Bayesian Network on frequency variations responds effectively to induced buffer overflows. It can also help administrators to detect deviations in program flow introduced due to errors.
Resumo:
Latin America has recently experienced three cycles of capital inflows, the first two ending in major financial crises. The first took place between 1973 and the 1982 ‘debt-crisis’. The second took place between the 1989 ‘Brady bonds’ agreement (and the beginning of the economic reforms and financial liberalisation that followed) and the Argentinian 2001/2002 crisis, and ended up with four major crises (as well as the 1997 one in East Asia) — Mexico (1994), Brazil (1999), and two in Argentina (1995 and 2001/2). Finally, the third inflow-cycle began in 2003 as soon as international financial markets felt reassured by the surprisingly neo-liberal orientation of President Lula’s government; this cycle intensified in 2004 with the beginning of a (purely speculative) commodity price-boom, and actually strengthened after a brief interlude following the 2008 global financial crash — and at the time of writing (mid-2011) this cycle is still unfolding, although already showing considerable signs of distress. The main aim of this paper is to analyse the financial crises resulting from this second cycle (both in LA and in East Asia) from the perspective of Keynesian/ Minskyian/ Kindlebergian financial economics. I will attempt to show that no matter how diversely these newly financially liberalised Developing Countries tried to deal with the absorption problem created by the subsequent surges of inflow (and they did follow different routes), they invariably ended up in a major crisis. As a result (and despite the insistence of mainstream analysis), these financial crises took place mostly due to factors that were intrinsic (or inherent) to the workings of over-liquid and under-regulated financial markets — and as such, they were both fully deserved and fairly predictable. Furthermore, these crises point not just to major market failures, but to a systemic market failure: evidence suggests that these crises were the spontaneous outcome of actions by utility-maximising agents, freely operating in friendly (‘light-touch’) regulated, over-liquid financial markets. That is, these crises are clear examples that financial markets can be driven by buyers who take little notice of underlying values — i.e., by investors who have incentives to interpret information in a biased fashion in a systematic way. Thus, ‘fat tails’ also occurred because under these circumstances there is a high likelihood of self-made disastrous events. In other words, markets are not always right — indeed, in the case of financial markets they can be seriously wrong as a whole. Also, as the recent collapse of ‘MF Global’ indicates, the capacity of ‘utility-maximising’ agents operating in (excessively) ‘friendly-regulated’ and over-liquid financial market to learn from previous mistakes seems rather limited.
Resumo:
Latin America has recently experienced three cycles of capital inflows, the first two ending in major financial crises. The first took place between 1973 and the 1982 ‘debt-crisis’. The second took place between the 1989 ‘Brady bonds’ agreement (and the beginning of the economic reforms and financial liberalisation that followed) and the Argentinian 2001/2002 crisis, and ended up with four major crises (as well as the 1997 one in East Asia) — Mexico (1994), Brazil (1999), and two in Argentina (1995 and 2001/2). Finally, the third inflow-cycle began in 2003 as soon as international financial markets felt reassured by the surprisingly neo-liberal orientation of President Lula’s government; this cycle intensified in 2004 with the beginning of a (purely speculative) commodity price-boom, and actually strengthened after a brief interlude following the 2008 global financial crash — and at the time of writing (mid-2011) this cycle is still unfolding, although already showing considerable signs of distress. The main aim of this paper is to analyse the financial crises resulting from this second cycle (both in LA and in East Asia) from the perspective of Keynesian/ Minskyian/ Kindlebergian financial economics. I will attempt to show that no matter how diversely these newly financially liberalised Developing Countries tried to deal with the absorption problem created by the subsequent surges of inflow (and they did follow different routes), they invariably ended up in a major crisis. As a result (and despite the insistence of mainstream analysis), these financial crises took place mostly due to factors that were intrinsic (or inherent) to the workings of over-liquid and under-regulated financial markets — and as such, they were both fully deserved and fairly predictable. Furthermore, these crises point not just to major market failures, but to a systemic market failure: evidence suggests that these crises were the spontaneous outcome of actions by utility-maximising agents, freely operating in friendly (light-touched) regulated, over-liquid financial markets. That is, these crises are clear examples that financial markets can be driven by buyers who take little notice of underlying values — investors have incentives to interpret information in a biased fashion in a systematic way. ‘Fat tails’ also occurred because under these circumstances there is a high likelihood of self-made disastrous events. In other words, markets are not always right — indeed, in the case of financial markets they can be seriously wrong as a whole. Also, as the recent collapse of ‘MF Global’ indicates, the capacity of ‘utility-maximising’ agents operating in unregulated and over-liquid financial market to learn from previous mistakes seems rather limited.
Resumo:
Deer-vehicle collisions (DVCs) impact the economic and social well being of humans. We examined large-scale patterns behind DVCs across 3 ecoregions: Southern Lower Peninsula (SLP), Northern Lower Peninsula (NLP), and Upper Peninsula (UP) in Michigan. A 3 component conceptual model of DVCs with drivers, deer, and a landscape was the framework of analysis. The conceptual model was parameterized into a parsimonious mathematical model. The dependent variable was DVCs by county by ecoregion and the independent variables were percent forest cover, percent crop cover, mean annual vehicle miles traveled (VMT), and mean deer density index (DDI) by county. A discriminant function analysis of the 4 independent variables by counties by ecoregion indicated low misclassification, and provided support to the groupings by ecoregions. The global model and all sub-models were run for the 3 ecoregions and evaluated using information-theoretic approaches. Adjusted R2 values for the global model increased substantially from the SLP (0.21) to the NLP (0.54) to the UP (0.72). VMT and DDI were important variables across all 3 ecoregions. Percent crop cover played an important role in DVCs in the SLP and UP. The scale at which causal factors of DVCs operate appear to be finer in southern Michigan than in northern Michigan. Reduction of DVCs will likely occur only through a reduction in deer density, a reduction in traffic volume, or in modification of sitespecific factors, such as driver behavior, sight distance, highway features, or speed limits.
Resumo:
1. A long-standing question in ecology is how natural populations respond to a changing environment. Emergent optimal foraging theory-based models for individual variation go beyond the population level and predict how its individuals would respond to disturbances that produce changes in resource availability. 2. Evaluating variations in resource use patterns at the intrapopulation level in wild populations under changing environmental conditions would allow to further advance in the research on foraging ecology and evolution by gaining a better idea of the underlying mechanisms explaining trophic diversity. 3. In this study, we use a large spatio-temporal scale data set (western continental Europe, 19682006) on the diet of Bonellis Eagle Aquila fasciata breeding pairs to analyse the predator trophic responses at the intrapopulation level to a prey population crash. In particular, we borrow metrics from studies on network structure and intrapopulation variation to understand how an emerging infectious disease [the rabbit haemorrhagic disease (RHD)] that caused the density of the eagles primary prey (rabbit Oryctolagus cuniculus) to dramatically drop across Europe impacted on resource use patterns of this endangered raptor. 4. Following the major RHD outbreak, substantial changes in Bonellis Eagles diet diversity and organisation patterns at the intrapopulation level took place. Dietary variation among breeding pairs was larger after than before the outbreak. Before RHD, there were no clusters of pairs with similar diets, but significant clustering emerged after RHD. Moreover, diets at the pair level presented a nested pattern before RHD, but not after. 5. Here, we reveal how intrapopulation patterns of resource use can quantitatively and qualitatively vary, given drastic changes in resource availability. 6. For the first time, we show that a pathogen of a prey species can indirectly impact the intrapopulation patterns of resource use of an endangered predator.
Resumo:
To protect motorists and avoid tort liability, highway agencies expend considerable resources to repair damaged longitudinal barriers, such as w-beam guardrails. With limited funding available, though, highway agencies are unable to maintain all field-installed systems in the ideal as-built condition. Instead, these agencies focus on repairing only damage that has a detrimental effect on the safety performance of the barrier. The distinction between minor damage and more severe performance-altering damage, however, is not always clear. This paper presents a critical review of current United States (US) and Canadian criteria on whether to repair damaged longitudinal barrier. Barrier repair policies were obtained via comprehensive literature review and a survey of US and Canadian transportation agencies. In an analysis of the maintenance procedures of 40 US States and 8 Canadian transportation agencies, fewer than one-third of highway agencies were found to have quantitative measures to determine when barrier repair is warranted. In addition, no engineering basis for the current US barrier repair guidelines could be found. These findings underscore the importance of the development of quantitative barrier repair guidelines based on a strong technical foundation.
Resumo:
The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.