Regulatory Signs Research Articles

Embedded real-time speed limit sign recognition using image processing and machine learning techniques

The number of traffic accidents in Brazil has reached alarming levels and is currently one of the leading causes of death in the country. With the number of vehicles on the roads increasing rapidly, these problems will tend to worsen. Consequently, huge investments in resources to increase road safety will be required. The vertical R-19 system for optical character recognition of regulatory traffic signs (maximum speed limits) according to Brazilian Standards developed in this work uses a camera positioned at the front of the vehicle, facing forward. This is so that images of traffic signs can be captured, enabling the use of image processing and analysis techniques for sign detection. This paper proposes the detection and recognition of speed limit signs based on a cascade of boosted classifiers working with haar-like features. The recognition of the sign detected is achieved based on the optimum-path forest classifier (OPF), support vector machines (SVM), multilayer perceptron, k-nearest neighbor (kNN), extreme learning machine, least mean squares, and least squares machine learning techniques. The SVM, OPF and kNN classifiers had average accuracies higher than 99.5 %; the OPF classifier with a linear kernel took an average time of 87 $$\upmu$$ s to recognize a sign, while kNN took 11,721 $$\upmu$$ s and SVM 12,595 $$\upmu$$ s. This sign detection approach found and recognized successfully 11,320 road signs from a set of 12,520 images, leading to an overall accuracy of 90.41 %. Analyzing the system globally recognition accuracy was 89.19 %, as 11,167 road signs from a database with 12,520 signs were correctly recognized. The processing speed of the embedded system varied between 20 and 30 frames per second. Therefore, based on these results, the proposed system can be considered a promising tool with high commercial potential.

車両通行の多い街路空間での探索歩行時の注視傾向について

This article is a continuation of a study on eye fixation during a wayfinding walk of downtown Rome, which has heavy traffic. The first part reported on the state of route selection and wayfinding behavior in an unfamiliar overseas city, from a walking experiment that covers all the major tourist spots in Rome. This article will focus on “eye-fixation tendencies during the wayfinding walk.” In other words, the main purposes of this article are to 1) clarify the relationship between eye-fixation tendencies and wayfinding behavior between participants with different degrees of spatial cognition and walking routes, 2) examine the relationship between attentional tendencies and city space characteristics, 3) clarify the relationship between participant attributes and eye-fixation attributes by “object of eye fixation” and by “building façade site, ” 4) clarify the setup of “textual information” (particularly “storefront signs” and “road signs”) and eye-fixation tendencies in downtown Rome, which has heavy traffic, and 5) analyze the participants' eye movement patterns. As a result, the following points were found: 1) The frequency of eye fixation over walking distance by attribute was fewer during the initial wayfinding walk, and mean frequency of eye fixation was overwhelmingly greater during “head-turning behavior, ” and by nodes, most marked in the “square.” 2) The mean rate of eye fixation by object of eye fixation during the wayfinding walk overall was highest for the “buildings' façades, ” and extremely low for “storefront signs” and “road signs, ” which were assumed to be prominent sources of information. By attribute, the group with a higher degree of spatial cognition apprehended subjects such as “buildings' façades, ” which were the clues for the wayfinding walk. 3) Mean time of eye fixation by attribute was rather short for the group with a low degree of spatial cognition, and by object of eye fixation, longest for “road signs.” 4) While the mean eye fixation distance during the wayfinding walk overall was 16.6m, it was somewhat shorter during “head-turning behavior” and “stopping/staying, ” and by attribute, was shortest for the group with a low degree of spatial cognition. 5) Mean height of eye fixation for all sections tended to increase for longer eye fixation distances. 6) The most frequent storefront signs installed on the route of the participants' wayfinding walk were “wall-mounted signs, ” followed by “channel lettering signs” and “window lettering signs, ” and there were extremely few “protruding signs” that are frequently seen in Japan. Similarly, among the types of “road signs” installed, there were overwhelmingly many “regulatory signs, ” such as “no parking signs, ” and of the “directional signs” that are helpful in wayfinding walks, there were few “road names” and “facility/directional signs.” 7) Of the frequency of eye fixation to “traffic” by vehicle type, automobiles accounted for 70.1% of the whole, followed by motorbikes (19.3%), and by mode, “parked vehicles” stood out regardless of section. 8) In terms of eye movement patterns over the entire wayfinding walk, “fixed eye fixation” and “fluid eye fixation” stood out for all attributes.

Detection, classification, and mapping of U.S. traffic signs using google street view images for roadway inventory management

Abstract Background Maintaining an up-to-date record of the number, type, location, and condition of high-quantity low-cost roadway assets such as traffic signs is critical to transportation inventory management systems. While, databases such as Google Street View contain street-level images of all traffic signs and are updated regularly, their potential for creating an inventory databases has not been fully explored. The key benefit of such databases is that once traffic signs are detected, their geographic coordinates can also be derived and visualized within the same platform. Methods By leveraging Google Street View images, this paper presents a new system for creating inventories of traffic signs. Using computer vision method, traffic signs are detected and classified into four categories of regulatory, warning, stop, and yield signs by processing images extracted from Google Street View API. Considering the discriminative classification scores from all images that see a sign, the most probable location of each traffic sign is derived and shown on the Google Maps using a dynamic heat map. A data card containing information about location and type of each detected traffic sign is also created. Finally, several data mining interfaces are introduced that allow for better management of the traffic sign inventories. Results The experiments conducted on 6.2 miles of I-57 and I-74 interstate highways in the U.S. –with an average accuracy of 94.63 % for sign classification– show the potential of the method to provide quick, inexpensive, and automatic access to asset inventory information. Conclusions Given the reliability in performance shown through experiments and because collecting information from Google Street View imagery is cost-effective, the proposed method has potential to deliver inventory information on traffic signs in a timely fashion and tie into the existing DOT inventory management systems. Such spatio-temporal representations provide DOTs with information on how different types of traffic signs degrade over time and further provides useful condition information necessary for predicting sign replacement plan.

Evaluation of Multiclass Traffic Sign Detection and Classification Methods for U.S. Roadway Asset Inventory Management

Frequent analysis and updating the condition of traffic signs and mile markers are among the most important aspects of a highway asset management system. Today’s practices mainly involve manual data collection and analysis, which have to be done for millions of miles of roads and the practice needs to be repeated regularly. While significant progress has been made on improving the data collection practice by leveraging video streams collected from car-mounted cameras, the analysis has primarily remained a manual and labor-intensive process. Automating the analysis from the collected videos is also challenging due to the interclass variability of traffic signs, expected changes in illumination, occlusion, sign position, and orientation. To address these challenges, this paper presents and evaluates the performance of three computer vision algorithms for detection and classification of traffic signs in presence of cluttered backgrounds and static and dynamic occlusions. The task particularly focuses on (1) extracting two-dimensional (2D) candidate windows from already collected video streams that potentially contain traffic signs–without making any prior assumption about their locations; (2) detecting the presence of signs in these 2D candidate windows; and (3) classifying them into warning, regulatory, stop, and yield sign categories based on their shape and color. For validation, a new comprehensive benchmark data set of over 11,000 annotated U.S. traffic sign images with a large range of pose, scale, background, illumination, and occlusion variation is introduced. Experimental results show an average accuracy of 76.20%, 89.31%, and 94.83% for the methods of (1) Haar-like features with Cascade classifiers, (2) histograms of oriented gradients (HOG) with multiple one-versus-all support vector machine (SVM) classifiers, and (3) HOG+C with the SVM classifiers, a variant of the second method with histograms of colors concatenated to HOG. The experimental results demonstrate the potential of leveraging joint representation of texture and color in HOG+C together with SVM discriminative classifiers as a viable solution for creating up-to-date and complete inventories of traffic signs for U.S. roadways.

Structural features and regulatory signs of plant nuclease TBN1

Structural features and regulatory signs of plant nuclease TBN1

Intelligent Road Sign Inventory (IRSI) with Image Recognition and Attribute Computation from Video Log

Abstract: Road signs are infrastructure assets crucial for transportation safety. Transportation agencies need to inventory signs regularly, e.g., annually or every 2 years, for asset management. This article proposes a framework of intelligent road sign inventory (IRSI) to enhance sign data collection, compared with existing manual or semiautomatic methods. The two key technical problems of sign recognition and attribute computation are addressed for IRSI. Because sign colors are important for both image segmentation and color features analysis, a novel kernel‐density‐estimation‐based statistical color model (KDE‐SCM) is proposed to describe the widespread and multimodel sign color distributions. The KDE‐SCM is embedded into a sign recognition algorithm by integrating sign shapes, textures, and other features. Furthermore, sign attributes, including the distance, local position, global positioning system (GPS) position, height, tilt angle, etc., are computed from image and GPS data. The proposed algorithms have been tested with the actual video log images collected on 35 km road segments in Kyoto City, Japan. For the KDE‐SCM color models, the false positive rates for the red and blue colors are 0.9% and 0.7%, while the false negative rates are 0.8% and 0.5%, respectively. The sign recognition algorithm was configured and applied to recognize three regulatory sign types of stop, no‐crossing, and no‐parking signs with 92.6% precision and 91.9% recall on average. The sign attribute computation model was also tested with the actual video log. The computation errors for distance, position, tilt angle, and height, etc., increase with the measurement distances. The sign‐to‐camera distances have the computation errors of less than 22 cm if the measurement distances are less than 15 m. The proposed algorithms demonstrate good potential for developing IRSI to enhance road asset data collection and processing.

The significance of sleep in disorders of consciousness

Event Abstract Back to Event The significance of sleep in disorders of consciousness Nicole Chwala-Schlegel1*, Julia Lechinger1, Theresa Stemeseder1, Katharina Weilhart1, Victor Cologan2, Steven Laureys2, Silvia Parapatics3, Georg Gruber3 and Manuel Schabus1 1 Lab for Sleep&Consciousness, Univ. of Salzburg, Germany 2 Cyclotron Research Centre, Univ. of Liège, Belgium 3 The Siesta Group, Vienna & Medical University of Vienna, Department of Psychiatry and Psychotherapy, Austria It is well known that abnormalities of sleep are extremely common in patients suffering from clinical disorders of consciousness. These patients exhibit more arousals and awakenings than healthy individuals and decreases in rapid eye movement (REM) and slow wave sleep (SWS) are common. Previous studies report that the reappearance of organized sleep elements, like stage 2 sleep spindles or K-complexes have predictive value for a good outcome. A better characterization of sleep timing and sleep architecture in this group of patients might therefore be of foremost ethical relevance. However, it appears that the very existence of sleep is a challenging issue as these patients do not show the normal behavioural, physiological and regulatory signs of sleep. Up to now we performed 24h polysomnographies in 34 patients being either in a vegetative (VS, i.e., unresponsive wakefulness) or minimally conscious state (MCS, i.e., inconsistent but discernible evidence of consciousness) following brain injury. Coma state was classified using the Coma Recovery Scale-Revised (CRS-R). Results: First analysis indicates that VS and MCS patients differ especially in REM sleep, sleep spindles and cortical desynchronization arousals. More complex sleep architecture (presence of SWS and/or REM) appears to be present in MCS as compared to VS patients (Chi² = 5.87, p = .053). Furthermore, CRS-R is associated with sleep onset latency (r16 = .58, p < .001), and spindle intensity at central and frontal recordings sites (e.g. C4, r32 = .34, p < .05). Finally the arousal index indicates to be higher in MCS than VS patients (t14 = -1.86; p = .084). Conclusion: 24hr polysomnographies should allow the identification of EEG markers which can help in assisting diagnostic processes and prognostic statements. Keywords: Neuropsychiatry, rem Conference: XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011. Presentation Type: Poster Presentation Topic: Poster Sessions: Neuropsychiatric Applications Citation: Chwala-Schlegel N, Lechinger J, Stemeseder T, Weilhart K, Cologan V, Laureys S, Parapatics S, Gruber G and Schabus M (2011). The significance of sleep in disorders of consciousness. Conference Abstract: XI International Conference on Cognitive Neuroscience (ICON XI). doi: 10.3389/conf.fnhum.2011.207.00236 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Nov 2011; Published Online: 28 Nov 2011. * Correspondence: Dr. Nicole Chwala-Schlegel, Lab for Sleep&Consciousness, Univ. of Salzburg, Salzubrg, Germany, nicole.chwala2@sbg.ac.at Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Nicole Chwala-Schlegel Julia Lechinger Theresa Stemeseder Katharina Weilhart Victor Cologan Steven Laureys Silvia Parapatics Georg Gruber Manuel Schabus Google Nicole Chwala-Schlegel Julia Lechinger Theresa Stemeseder Katharina Weilhart Victor Cologan Steven Laureys Silvia Parapatics Georg Gruber Manuel Schabus Google Scholar Nicole Chwala-Schlegel Julia Lechinger Theresa Stemeseder Katharina Weilhart Victor Cologan Steven Laureys Silvia Parapatics Georg Gruber Manuel Schabus PubMed Nicole Chwala-Schlegel Julia Lechinger Theresa Stemeseder Katharina Weilhart Victor Cologan Steven Laureys Silvia Parapatics Georg Gruber Manuel Schabus Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Proportion-Based Format System for Freeway and Expressway Guide Signs

The Manual on Uniform Traffic Control Devices has grown much more complex since 1961, the year that a section on signs for freeways and expressways was added to the manual. Yet that growth has been reflected primarily in the addition of more regulatory signs and a great deal of qualifying language. The standards for sign legibility and layout have changed little; however, the complexity of the roadway environments and the demand placed on the system has changed substantially. This paper builds upon previous work by the writers, which proposed similar formatting for conventional road guide signing. The intent of the system proposed in this new work is to improve the consistency and uniform readability of freeway and expressway guide signs based on defined proportions for key dimensions including: border, figure and field relationship, and line space. This design scheme rests on a foundation of proportional relationships made uniform for all common applications based on the common dimension (“ X ”) of the h...

Motorist Understanding of Alternative Displays for Speed Limits in Work Zones

In Texas, speed limits for short-term work zones are reduced speed limits that are posted only when work activity is present. When work activity is not present, the reduced speed limit signs are to be removed or covered; the legal speed limit for that segment reverts to the normal zone speed limit. The major challenge of speed limits for short-term work zones is the daily process of installing and removing, or uncovering and covering, signs. In this study, researchers conducted a laptop-based laboratory survey to determine (a) motorists' understanding and opinions of alternative short-term signs for speed limits in work zones and the enforceability of limits, (b) the success of the orange or white light-emitting diode (LED) color used on electronic speed limit (ESL) signs and portable changeable message signs (PCMSs) in indicating to motorists that they were advisory or regulatory signs, and (c) motorists' preference for short-term speed limit displays. The four categories of signs included in the survey were static work zone signs, ESL signs, speed limits displayed on PCMSs, and “Your Speed” signs (distracters). On the basis of the results obtained from this survey, researchers recommend the use of ESL signs and flexible roll-up signs for speed limits in static work zones for displaying speed limits in short-term work zones. To ensure that the speed limit displayed on ESL signs is considered a regulatory speed limit, the changeable display should be composed of white LEDs.

Network Inference by Combining Biologically Motivated Regulatory Constraints with Penalized Regression

Reconstructing biomolecular networks from time series mRNA or protein abundance measurements is a central challenge in computational systems biology. The regulatory processes behind cellular responses are coupled and nonlinear, leading to rich dynamical behavior. One class of reconstruction algorithms uses regression and penalized regression to impose sparseness on the solution, as requested biologically. Motivated by the five-gene challenge in the Dialogue for Reverse Engineering Assessments and Methods 2 (DREAM2) contest, we extend and test penalized regression schemes both on data from simulations and real qPCR measurements. The methods showing best performance are the Adaptive Ridge (AR) regression and a new extension thereof, in which we impose a biological constraint to the reconstructed network. Specifically, we request from the solutions that the outgoing links have the same regulatory sign, which is a reasonable approximation for most prokaryotic transcriptional networks. In other words, a given regulator must be either an activator or a repressor but not both. The constraints can be implemented with quadratic programming, and we show that this improves the reconstruction performance significantly. While linear models are not sufficiently general to encompass most complex behaviors, they offer powerful tools for network reconstruction, particularly for systems operating near a steady state. In particular, the optimization problems are well behaved and methodologies allow finding global optima efficiently. Adding constraints reflecting biological circuit designs is one of the most important aspects of network inference. We propose one such constraint, namely the consistency in the signs of outgoing links, which will facilitate the inference of transcriptional regulatory networks.

Traffic Sign Comprehensibility in an Aging Society

This paper analyzes the comprehensibility of current and experimental signs to indicate a photo-enforced traffic signal ahead. In Arnold, Missouri, four signalized intersections are photo enforced and have been indicated with the text-only “photo-enforced” regulatory sign posted below the traditional “signal ahead” warning sign. These signs were replaced with an experimental sign that indicates a photo-enforced traffic signal ahead with a single regulatory sign. The evaluation is performed by using three surveys: one for the currently approved signage and two for the experimental sign. The second survey was conducted shortly after installation of the experimental sign, and the third survey was conducted about 9 months after installation. The study found that older drivers (age 65+ years) have greater difficulty in comprehending both the current and experimental photo-enforced signage compared with younger drivers. However, older drivers’ comprehension of the experimental sign improved more over time than other drivers’ comprehension (62.5% to 75.8% correct comprehension for older versus 79.8% to 81.2% for others). The results indicate that the experimental sign has the potential to improve safety by better delivering its intended meaning, particularly to older drivers, but also that it may take older drivers more time than other drivers to learn about and comprehend new signs.

Field Evaluations of Warning and Regulatory Signs with Enhanced Conspicuity Properties

Researchers examined the impacts of various sign conspicuity enhancements on traffic operations and driver behavior in Texas. Eight types of applications were evaluated: fluorescent yellow chevrons, fluorescent yellow chevron posts, fluorescent yellow curve signs, fluorescent yellow ramp advisory speed signs, fluorescent yellow stop ahead signs, fluorescent red stop signs, flashing red light-emitting diode (LED) stop signs, and a standard red border on speed limit signs. Fourteen sites were used for the evaluations. Traffic operations data collected before and after the sign upgrades included vehicle speeds, edge line encroachments, and stopping compliance. Many statistically significant beneficial results occurred, including the following: fluorescent yellow chevron signs produced a significant reduction in curve speeds and edge line encroachments, both the fluorescent red and LED stop sign treatments reduced the number of vehicles not fully stopping, and the standard red reflectorized border on the speed limit sign produced a significant improvement in speed limit compliance. The data showed no undesirable impacts for the measures of effectiveness for any of the signing treatments. On the basis of the findings, the researchers recommend fluorescent yellow chevrons for full implementation. The other fluorescent yellow signs evaluated in the research are recommended for implementation on an as-needed basis. Microprismatic stop signs and flashing LED stop signs are also recommended for implementation on an as-needed basis. Although found to be effective, the red border speed limit sign currently should be limited to experimental implementation, as permission is required from FHWA to install these signs. The fluorescent red stop sign is not commercially available at this time.

Role of drivers’ personal characteristics in understanding traffic sign symbols

This study investigated the role of age, marital status, gender, nationality, educational background and monthly income in drivers’ comprehension of traffic signs. The populations sampled here were from five Arabian Gulf Countries. A total of 28 symbolic warning and regulatory signs were investigated. A questionnaire specially prepared to collect the necessary data was distributed to over 9000 drivers in the five countries; 4774 responded (53%). The results indicated substantial problems with the level of comprehension among the drivers about the traffic signs. The percentages of drivers who correctly identified the regulatory signs and warning signs were around 55 and 56%, respectively. Age, gender, education and income played major roles in determining drivers’ comprehension of signs, whereas marital status showed no significant effect. Drivers who are young, female, those with lower levels of education or lower incomes understand the signs significantly worse than drivers who are older, male, with higher levels of education or higher incomes. Drivers from Europe and USA are significantly better than Asian and Arab drivers. These findings are believed to be important for the designers of road signs for international applications.

Factors Affecting Driver Recognition of Regulatory Signs

The purpose of this paper is to explore the factors that determine conspicuity of regulatory signs, and to investigate how to install regulatory signs to increase the chances of attracting attention. Factors under consideration were types of signs, lateral clearance, location, roadside or overhead signs, the number of plates attached to one post and the road environment. The main results are as follows. The recognition rate for elderly drivers was similar to that of younger drivers. Overhead signs have higher recognition rates than conventional roadside signs. Signs were less conspicuous in arterial roads than in residential roads. The outcome of the quantification method shows that the most effective action to enhance recognition rates is to use overhead signs.

Teenage Drivers’ Understanding of Traffic Control Devices

Teenage drivers are involved in traffic crashes more often than any other driver group, and their fundamental knowledge of traffic control devices and rules of the road is extremely important in safe driving. Only limited data exist, however, on teenage drivers’ understanding of traffic control devices, and little research has been done on determining their comprehension thereof. Research was performed to document teenage drivers’ ability to understand 53 traffic control devices. These traffic control devices included 6 combinations of sign shape and color; 8 regulatory signs; 14 warning signs; 7 school, highway–railroad grade crossing, and construction warning signs; 7 pavement markings; and 11 traffic signals. Research results were then compared with previous comprehension studies to identify specific traffic control devices that the driving public continually misunderstands. In general, the results indicated that surveyed teenage drivers understood the traffic control devices to some degree. Only nine devices were understood by more than 80 percent of the respondents. The devices found problematic to teenage drivers include combinations of sign shape and color, warning-symbol signs, white pavement markings, flashing intersection beacons, and circular red/green arrow left-turn-signal displays. Recommendations include revising states’ drivers handbooks and increasing emphasis in the driver education curriculum to clarify the meaning and intent of problematic traffic control devices.

The medical dictionary for regulatory activities (MedDRA).

The International Conference on Harmonisation has agreed upon the structure and content of the Medical Dictionary for Regulatory Activities (MedDRA) version 2.0 which should become available in the early part of 1999. This medical terminology is intended for use in the pre- and postmarketing phases of the medicines regulatory process, covering diagnoses, symptoms and signs, adverse drug reactions and therapeutic indications, the names and qualitative results of investigations, surgical and medical procedures, and medical/social history. It can be used for recording adverse events and medical history in clinical trials, in the analysis and tabulations of data from these trials and in the expedited submission of safety data to government regulatory authorities, as well as in constructing standard product information and documentation for applications for marketing authorisation. After licensing of a medicine, it may be used in pharmacovigilance and is expected to be the preferred terminology for international electronic regulatory communication. MedDRA is a hierarchical terminology with 5 levels and is multiaxial: terms may exist in more than 1 vertical axis, providing specificity of terms for data entry and flexibility in data retrieval. Terms in MedDRA were derived from several sources including the WHO's adverse reaction terminology (WHO-ART), Coding Symbols for a Thesaurus of Adverse Reaction Terms (COSTART), International Classification of Diseases (ICD) 9 and ICD9-CM. It will be maintained, further developed and distributed by a Maintenance Support Services Organisation (MSSO). It is anticipated that using MedDRA will improve the quality of data captured on databases, support effective analysis by providing clinically relevant groupings of terms and facilitate electronic communication of data, although as a new tool, users will need to invest time in gaining expertise in its use.

Impacts of Maintaining Traffic Signs Within Minimum Retroreflectivity Guidelines

The Federal Highway Administration has developed guidelines for minimum levels of retroreflectivity for four groups of signs: ( a) black-on-yellow/orange warning signs, ( b) black-on-white regulatory or guide signs, ( c) white-on-red regulatory signs, and ( d) white-on-green guide signs. The impact of implementing these guidelines was assessed by estimating the percentage of signs not meeting the proposed minimum levels and the cost of replacing such signs. Various state and local highway agencies assisted in the study by measuring the retroreflectivity of a sample of in-use signs, providing data on sign replacement costs, and commenting on the practicality of maintaining signs at minimum retroreflectivity levels. In general, the local agencies will have a higher percentage of signs needing replacement due to noncompliance with the minimum retroreflectivity guidelines than the state agencies, primarily due to a higher percentage of older and engineering-grade sheeting signs in service under their jurisdiction than the states. Overall, about 5.5 percent of the nation’s signs will not meet the minimum guidelines. About 8 percent of the local signs and about 4.5 percent of those under state jurisdictions will need replacement. Although warning signs will be the most critical signs for local agencies, the guide signs will be most critical for the states, each group requiring over 9.5 percent of the signs replaced. If all the signs not meeting the minimum guidelines are replaced, it would cost about $32 million to all the state agencies combined and about $144 million to the local agencies.

Stripe forming architecture of the gap gene system.

In this report, we show that gap genes encode exactly one set of pair-rule stripes, which occur in the native even-skipped position. The core of this work is a detailed analysis that shows how this conclusion follows from the arrangement of gap domains in the embryo. This analysis shows that: (1) pattern forming information is transmitted from gap to pair-rule genes by means of a nonredundant set of morphogenetic gradients, and (2) the stripe forming capability of the gap genes is constrained by the arrangement of these gradients and by the fact that each gap domain consists of a pair of correlated gradients. We also show that in the blastoderm, the regulatory sign of a transcriptional regulator is unlikely to change in a concentration dependent manner. The principal analytic tool used to establish these results is the gene circuit method. Here, this method is applied to examine hybrid data sets consisting of real gene expression data for four gap genes and hypothetical pair-rule expression data generated by translating native even-skipped data along the anterior-posterior axis. In this way, we are able to investigate the stripe forming capabilities of the gap gene system in the complete absence of pair-rule cross regulation. We close with an inference about evolutionary development. It is argued that the constraints on gap gene architecture identified here are a consequence of selective pressures that minimize the number of gap genes required to determine segments in long-germ band insects.

Official Graffiti of the Everyday

This article focuses attention on “official graffiti” or regulatory signs typified by highway signs and the most invasive and emblematic piece of official graffiti, the prohibition circle with its diagonal red slash used in the iconic representation No Smoking. Establishing the range and pervasiveness of official graffiti in everyday life (as prohibitions, warnings, advisories, instructions, etc.), the authors approach these visual manifestations from the standpoint of the sociology of governance and analyze them as important instances of government at a distance. They explore the varieties and forms of such regulation and trace their expansion from public space to quasi-public space and to the private realm. Locating the texts and icons of official graffiti within implied or express discursive frameworks, the authors point to the construction of objects and subjects of regulation and to regulatory agents as “absent experts” and address the key role of the construction of danger and the link to insurance principles in a “risk society.” They also examine resistance through actions of defacement and avoidance that result in the complex order and disorder of surfaces and spaces. Official graffiti manifests a distinctive form of hegemony that is exercised through the small, daily acts of everyday governance.

Traffic signs in complex visual environments

The effects of sign luminance on detection and recognition of traffic control devices is mediated through contrast with the immediate surround. Additionally, complex visual scenes are known to degrade visual performance with targets well above visual threshold. A laboratory study was conducted to determine ways of measuring visual complexity and to assess the capability of changes in sign luminance to offset decrements in performance resulting from added complexity. Positive results were found for yellow warning, construction, and stop signs but not for the black on white regulatory sign. Regression equations using complexity factors, contrast, and target variables suggested that in complex scenes, complexity is a more significant determinant of sign detection than brightness or contrast. A field study also was conducted to determine if these findings could be observed in real world driver performance. The effects of visual complexity were observed in the field and increasing sign brightness improved sign recognition under specific conditions. (FHWA)