998 resultados para Speed signs.


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Federal Highway Administration, Office of Research, Washington, D.C.

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Federal Highway Administration, Washington, D.C.

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The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

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Federal Highway Administration, Traffic Systems Division, Washington, D.C.

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Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

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Federal Highway Administration, Office of Research and Development, Washington, D.C.

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Roadworks are essential to a safe and efficient road network, yet somewhat paradoxically the necessary work is often associated with increased risk to motorists and workers, as well as with traffic flow disruptions. A major source of increased crash risk at roadwork sites (work zones) is poor speed limit compliance. Speeding in work zones is examined in existing literature to the extent that major issues are known and some effective countermeasures are identified. However, as speeding remains a major problem in work zones, influences on driver behaviour arguably need to be better understood to achieve greater compliance and thus realise further gains in road safety. Current research on safety at Queensland roadwork sites has examined the views of workers, measured work zone speed profiles, and conducted an online survey of drivers (N=410). This paper focuses on survey participants’ ratings of 12 specific work zone items (including traffic control measures) in terms of their influence on speed choice. Repeated measures ANOVA revealed statistically significant differences (p<0.001) in the ratings of these items, with the most influential including visible presence of workers, visible police presence, and speed feedback displays. Those rated least influential included ’roadwork speed limits are enforced’ and ‘reduce speedsigns and increased fines for speeding in work zones. The paper considers the alignment of these findings with those from other sources, including worker interviews and the literature, to provide a consolidated assessment of the influence of work zone items on driver speeds.

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Objectives In China, “serious road traffic crashes” (SRTCs) are those in which there are 10-30 fatalities, 50-100 serious injuries or a total cost of 50-100 million RMB ($US8-16m), and “particularly serious road traffic crashes” (PSRTCs) are those which are more severe or costly. Due to the large number of fatalities and injuries as well as the negative public reaction they elicit, SRTCs and PSRTCs have become great concerns to China during recent years. The aim of this study is to identify the main factors contributing to these road traffic crashes and to propose preventive measures to reduce their number. Methods 49 contributing factors of the SRTCs and PSRTCs that occurred from 2007 to 2013 were collected from the database “In-depth Investigation and Analysis System for Major Road traffic crashes” (IIASMRTC) and were analyzed through the integrated use of principal component analysis and hierarchical clustering to determine the primary and secondary groups of contributing factors. Results Speeding and overloading of passengers were the primary contributing factors, featuring in up to 66.3% and 32.6% of accidents respectively. Two secondary contributing factors were road-related: lack of or nonstandard roadside safety infrastructure, and slippery roads due to rain, snow or ice. Conclusions The current approach to SRTCs and PSRTCs is focused on the attribution of responsibility and the enforcement of regulations considered relevant to particular SRTCs and PSRTCs. It would be more effective to investigate contributing factors and characteristics of SRTCs and PSRTCs as a whole, to provide adequate information for safety interventions in regions where SRTCs and PSRTCs are more common. In addition to mandating of a driver training program and publicisation of the hazards associated with traffic violations, implementation of speed cameras, speed signs, markings and vehicle-mounted GPS are suggested to reduce speeding of passenger vehicles, while increasing regular checks by traffic police and passenger station staff, and improving transportation management to increase income of contractors and drivers are feasible measures to prevent overloading of people. Other promising measures include regular inspection of roadside safety infrastructure, and improving skid resistance on dangerous road sections in mountainous areas.

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Texas Department of Transportation, Austin

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The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

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Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

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Federal Highway Administration, Washington, D.C.

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Noncompliance with speed limits is one of the major safety concerns in roadwork zones. Although numerous studies have attempted to evaluate the effectiveness of safety measures on speed limit compliance, many report inconsistent findings. This paper aims to review the effectiveness of four categories of roadwork zone speed control measures: Informational, Physical, Enforcement, and Educational measures. While informational measures (static signage, variable message signage) evidently have small to moderate effects on speed reduction, physical measures (rumble strips, optical speed bars) are found ineffective for transient and moving work zones. Enforcement measures (speed camera, police presence) have the greatest effects, while educational measures also have significant potential to improve public awareness of roadworker safety and to encourage slower speeds in work zones. Inadequate public understanding of roadwork risks and hazards, failure to notice signs, and poor appreciation of safety measures are the major causes of noncompliance with speed limits.

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This research project examined objective measures of driver behaviour and road users' perceptions on the usefulness and effectiveness of three specific VMS (Variable Message Signs) interventions to improve speeding and headway behaviours. The interventions addressed speeding behaviour alone (intervention 1), headway behaviour alone (intervention 2) and a combination of speeding and headway behaviour (intervention 3). Six VMS were installed along a segment of the Bruce Highway, with a series of three signs for each of the northbound and southbound traffic. Speeds and headway distances were measured with loop detectors installed before and after each VMS. Messages addressing speeding and headway were devised for display on the VMS. A driver could receive a message if they were detected as exceeding the posted speed limit (of 90km/hr) or if the distance to the vehicle in front was less than 2.0s. In addition to the on-road objective measurement of speeding and headway behaviours, the research project elicited self-reported responses to the speeding and headway messages from a sample of drivers via a community-based survey. The survey sought to examine the drivers' beliefs about the effectiveness of the signs and messages, and their views about the role, use, and effectiveness of VMS more generally.

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The use of intelligent transport systems is proliferating across the Australian road network, particularly on major freeways. New technology allows a greater range of signs and messages to be displayed to drivers. While there has been a long history of human factors analyses of signage, no evaluation has been conducted on this novel, sometimes dynamic, signage or potential interactions when co-located. The purpose of this driving simulator study was to investigate drivers’ behavioural changes and comprehension resulting from the co-location of Lane Use Management Systems with static signs and (Enhanced) Variable Message Signs on Queensland motorways. A section of motorway was simulated, and nine scenarios were developed which presented a combination of signage cases across levels of driving task complexity. Two higher-risk road user groups were targeted for this research on an advanced driving simulator: older (65+ years, N=21) and younger (18-22 years, N=20) drivers. Changes in sign co-location and task complexity had small effect on driver comprehension of the signs and vehicle dynamics variables, including difference with the posted speed limit, headway, standard deviation of lane keeping and brake jerks. However, increasing the amount of information provided to drivers at a given location (by co-locating several signs) increased participants’ gaze duration on the signs. With co-location of signs and without added task complexity, a single gaze was over 2s for more than half of the population tested for both groups, and up to 6 seconds for some individuals.