基于直线包络的交通标志快速定位方法

为了提高快速定位交通标志的准确性,通过对场景中复杂的直线信息以及颜色信息的融合,提出了一种基于直线包络的快速定位交通标志的方法。该方法首先利用颜色信息以及统计直线信息获取目标候选区域,将交通标志进行粗定位,然后利用形态学运算获取连通区域,再利用交通标志的纵横比和内部孔洞信息将交通标志从目标候选区域中准确定位出来。实验表明该方法可以提高交通标志在夜晚等复杂背景中定位的准确性。     

Traffic light recognition

Abstract

An automatic traffic light recognition system is proposed in this paper so that car drivers have sufficient information to make a correct decision. This in turn facilitates the construction of an ITS (Intelligent Transportation System). The proposed method can be applied to movable cameras, is adaptable to environmental variations and is proper for real‐time implementation. It consists of two phases: traffic light detection and classification. The two phases are based on color, region and border information. At the detection stage, the RGB color space is first converted into the HSI color space so as to find those regions with specific colors of traffic lights. The morphology technology is employed to remove holes and noise. Region labeling is then involved to detect candidate regions of traffic lights. At the classification stage, border detection is employed to obtain region borders which together with region colors are matching features. In this study, circle and arrow traffic lights can both be coped with. Moreover, our method is adaptable to environmental variations in numbers of lights, types of lights and time slots. Various experiments have been conducted to demonstrate the effectiveness and practicability of the proposed method.     

基于中小学生出行及认知特点的交通标志改进的探讨

目的从交通安全的角度出发,基于中小学生的出行特点和认知特点,提出现行交通标志设计改进方案。方法设计实验,抽样调查中小学生2400名,分析现有交通标志存在的缺陷。结果现有交通标志中,中小学生认知理解正确率为67.92%,注视时长885ms,红色标志认读正确率87.3%;现有交通标志存在部分不易理解、设计单调、静态交通标志高度欠合理、人性化不足等问题,针对交通标志的颜色、图案、材料、位置、高度等方面缺陷提出可行性改进方案,进一步提高交通标志的趣味性和可用性。结论结合中小学生的出行和认知特点来改进现有交通标志,可以改善现有交通标志成人化、有歧义、不具亲和力等缺陷,有利于中小学生的出行安全更进一步得到保障。     

Robust traffic sign shape recognition using geometric matching

A novel approach for recognising various traffic sign shapes in outdoor environments is presented.To reduce the influence of digital noise and extract the shape of each individual traffic sign, the external boundaries of traffic signs segmented based on colour information are simplified and decomposed through discrete curve evolution whose stop stage is determined by an arc similarity measure in tangent space. The recognition of a closed candidate shape is achieved through the direct matching with templates. An optimal enclosure is generated to minimise the geometric differences between the retrieved unclosed candidate shape and templates. The experimental results justify that the proposed algorithm is translation, rotation and scaling invariant, and gives reliable shape recognition in complex traffic scenes where clustering and partial occlusion normally occur.     

道路交通标志设计探析

针对道路交通标志在现实生活中传递特定交通信息的作用,分析了其在设计方面存在的典型性问题。通过总结道路交通标志要求视认性高、易读性好、通用性强的特点,结合存在的具体问题,从艺术设计的视角,在交通标志的图形语言、文字设计、色彩设计、版面设计以及标志的设置等方面,探讨了城市交通标志的合理化设计方法。     

中国城市道路指路标志典型版面布局导航绩效研究

目的对5款典型的省会城市指路标志导航绩效进行工效学评价,并确定其存在的问题。方法 34名大学生被试参与完成5款指路标志版面布局的道路关系判断与道路走向判断两类实验任务。结果 5款指路标志任务绩效无显著差异,任务正确率介于32%~38%,具体任务分析发现问题主要集中于版面两侧道路关系判断及道路走向判断,其平均正确率仅为10%和18%。结论 (1)现有5款典型版面布局导向绩效无显著差异,总体绩效均很低;(2)原因主要是路名(尤其是版面两侧路名)的布局方式对被试的道路走向判断及道路关系判读具有强烈的暗示诱导作用。     

New solution algorithms for asymmetric traffic assignment model

Abstract

The asymmetric traffic assignment model can improve the traditional traffic assignment model by adopting detailed network representation and more realistic asymmetric cost functions. The diagonalization, streamlined diagonalization, and projection methods are three widely mentioned solution algorithms for solving asymmetric traffic assignment models. The diagonalization and streamlined diagonalization methods have the advantage of requiring less computer memory but typically require greater computational time. The projection method has the advantage of converging more rapidly but requires a large computer memory. In order to balance computer memory and computational time, we propose two new algorithms; i.e., hybrid and streamlined hybrid methods. According to our case study, the proposed algorithms show their superiority over the diagonalization and streamlined diagonalization methods in terms of computational time, and over the projection method in terms of computer memory. Both new algorithms can handle small or medium networks sized asymmetric traffic assignment problems on personal computers.     

The power-saving mechanism for solar power LED traffic signal light system

This article proposes a mechanism to reduce the battery power consumed by an independent solar-powered light intensity detection (LED) used for auxiliary traffic sign lighting by means of special background light sensor detection and an LED brightness control. This kind of traffic sign is deployed in remote areas and public utilities, where workers find hard to reach. Symbols and signs shaped by LED lights can assist drivers in mountain areas, remote areas, roads and highways with indications of directions and/or speed limits such that traffic accidents can be reduced. LED lights are especially suitable for environments with poor lights.     

Traffic Sign Detection with Low Complexity for Intelligent Vehicles Based on Hybrid Features

Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians. Consequently, traffic signs have been of great importance for every civilized country, which makes researchers give more focus on the automatic detection of traffic signs. Detecting these traffic signs is challenging due to being in the dark, far away, partially occluded, and affected by the lighting or the presence of similar objects. An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues. This technique aimed to devise an efficient, robust and accurate approach. To attain this, initially, the approach presented a new formula, inspired by existing work, to enhance the image using red and green channels instead of blue, which segmented using a threshold calculated from the correlational property of the image. Next, a new set of features is proposed, motivated by existing features. Texture and color features are fused after getting extracted on the channel of Red, Green, and Blue (RGB), Hue, Saturation, and Value (HSV), and YCbCr color models of images. Later, the set of features is employed on different classification frameworks, from which quadratic support vector machine (SVM) outnumbered the others with an accuracy of 98.5%. The proposed method is tested on German Traffic Sign Detection Benchmark (GTSDB) images. The results are satisfactory when compared to the preceding work.     

Scale and skew‐invariant road sign recognition

A fast and robust method to detect and recognize scaled and skewed road signs is proposed in this paper. In the detection stage, the input color image is first quantized in HSV color model. Border tracing those regions with the same colors as road signs is adopted to find the regions of interest (ROI). The ROIs are then automatically adjusted to fit road sign shape models so as to facilitate detection verification even for scaled and skewed road signs in complicated scenes. Moreover, the ROI adjustment and verification are both performed only on border pixels; thus, the proposed road sign detector is fast. In the recognition stage, the detected road sign is normalized first. Histogram matching based on polar mesh is then adopted to measure the similarity between the scene and model road signs to accomplish recognition. Since histogram matching is fast and has high tolerance to distortion and deformation while contextual information can still be incorporated into it in a natural and elegant way, our method has high recognition accuracy and fast execution speed. Experiment results show that the detection rate and recognition accuracy of our method can achieve 94.2% and 91.7%, respectively. On an average, it takes only 4–50 and 10 ms for detection and recognition, respectively. Thus, the proposed method is effective, yet efficient. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 28–39, 2007     

The flux-flow hall effect in type II superconductors. An explanation of the sign reversal

We consider a time-dependent Ginzburg-Landau (TDGL) model modified to take into account two mechanisms responsible for the Hall voltage in superconductors: the usual effect of the magnetic field on the normal current, and the vortex traction by the superflow. For the BCS model of superconductivity, the contribution of the vortex traction is proportional to the energy derivative of the quasiparticle density of states. Our theory gives the correct order of magnitude for the Hall angle in the mixed state. It predicts that the vortex-traction mechanism results in a negative Hall angle for the quasiparticle spectrum with a positive energy derivative of the density of states averaged over the Fermi surface, and vice versa. For the Fermi surface with a complicated shape, the sign of the Hall effect in the mixed state can be different from that in the normal state. If the signs are opposite, the Hall angle changes its sign as a function of the magnetic field belowH _c2 .     

Drivers’ comprehension of traffic information on graphical route information panels

The concept of using signs to display graphical traffic information is now becoming increasingly popular. The main objective of this study was to design and undertake laboratory research to examine whether the content of traffic information displayed on graphical route information panel (GRIP) could be readily understood. Six kinds of GRIP signs that composed of three changeable information contents (road color only, road color with journey time, and road color with traffic speed) and two different road network types (triangle and tetragon) were proposed and tested in the experiment. Results showed that GRIP with road color only had the greatest optimum route choice percentage and the fastest response time compared to the other contents. On the contrary, GRIP with traffic speed had the slowest response time and the least optimum route choice percentage. Participants took less response time and greater optimum route choice percentage for triangle road network than for tetragon road network. Further, changeable information content interacted with road network type on response time and optimum route choice percentage. The road network type had little effect on response time and optimum route choice percentage under road color only, whereas under road color with journey time and road color with traffic speed, response times increased and optimum route choice percentage decreased significantly as road network complexity increased. Considering drivers’ comprehension and response, using road color only to present traffic condition on GRIP could be an applicable solution. Road color with traffic speed presented on GRIP was not recommended. Road color with journey time can be used for a simple road network. However, it was not suggested for a complex road network. The findings of this study could assist in displaying suitable traffic information on GRIP and in improving efficient driving for motorists.     

Image tracking of motorcycles and vehicles on urban roads and its application to traffic monitoring and enforcement

Abstract

Image tracking has increasingly gained attention for use in vision‐based traffic monitoring and surveillance applications. For many cities in Asia countries, it is desirable to detect multiple motorcycles as well as cars for urban traffic monitoring and enforcement. In this paper, a novel contour initialization and tracking algorithm is presented to track multiple motorcycles and vehicles at any position on the roadway. This method has the capability to detect moving vehicles of various sizes and to generate their initial contours for image tracking. The proposed method is not constrained by lane boundaries or vehicle size. To track vehicles on roadways, dynamic models are designed to predict the horizontal and vertical positions of vehicle contours. A Kalman filter is designed to update the prediction based on real‐time image measurement. Practical experimental studies using video clips are presented to evaluate the performance of the proposed method. Traffic parameters such as traffic flow, vehicle speeds and traffic density are obtained with satisfactory accuracy.     

Differential effects of traffic sign stimuli upon speeding in school zones following a traffic light interruption

Motorists whose journey has been interrupted by signalized traffic intersections in school zones resume their journey at a faster vehicle speed than motorists who have not been required to stop. Introducing a flashing “check speed” sign 70 m after the traffic intersections counteracts this interruptive effect. The present study examined which aspects of a reminder sign are responsible for reducing the speeding behavior of interrupted motorists. When a sign that combines both written text and flashing lights was introduced, interrupted motorists did not speed, traveling on average 0.82 km/h below the 40 km/h speed limit when measured 100 m from traffic intersections. Alternatively, when only the flashing lights were visible the interrupted motorists sped 3.36 km/h over the 40 km/h speed limit. Similar vehicular speeds were observed when only the written text was visible and when no sign was present (7.67 and 7.49 km/h over the 40 km/h speed limit, respectively). This indicates that static reminder signs add little value over the absence of a school zone reminder sign; the presence of both cues is necessary to fully offset the interruptive effect. This study also highlights the benefit of using exogenous visual cues in traffic signs to capture drivers’ attention. These findings have practical implications for the design and use of traffic signs to increase compliance with posted speed limits.     

Improved VGG Model for Road Traffic Sign Recognition

Road traffic sign recognition is an important task in intelligent transportation system. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, it presents a road traffic sign recognition algorithm based on a convolutional neural network. In natural scenes, traffic signs are disturbed by factors such as illumination, occlusion, missing and deformation, and the accuracy of recognition decreases, this paper proposes a model called Improved VGG (IVGG) inspired by VGG model. The IVGG model includes 9 layers, compared with the original VGG model, it is added max-pooling operation and dropout operation after multiple convolutional layers, to catch the main features and save the training time. The paper proposes the method which adds dropout and Batch Normalization (BN) operations after each fully-connected layer, to further accelerate the model convergence, and then it can get better classification effect. It uses the German Traffic Sign Recognition Benchmark (GTSRB) dataset in the experiment. The IVGG model enhances the recognition rate of traffic signs and robustness by using the data augmentation and transfer learning, and the spent time is also reduced greatly.     

An online triple-frequency color-encoded fringe projection profilometry for discontinuous object

Abstract

An online triple-frequency color-encoded fringe projection profilometry is proposed to measure the complex and discontinuous object at straight-line movement. N frames of color fringe patterns are specially designed. Three grayscale sinusoidal grating patterns with geometric progression frequency growth are encoded into red (R), green (G), and blue (B) channels separately to compose a color-encoded fringe pattern. If these three grayscale sinusoidal grating patterns are phase-shifted N steps with an equivalent shift phase of 2π/N, they can compose the corresponding N frames of color-encoded fringe patterns as above respectively. In order to avoid the movement’s interference to the phase shifting, position adjustment should be done to guarantee the phase-shifting direction to be perpendicular to the moving direction. While these N frames of specially designed color-encoded fringe patterns are projected onto the moving object one by one, the corresponding deformed color patterns are captured by a CCD camera in real time. By color separating, color crosstalk compensation, pixel matching, and phase calculation, three wrapped phase at different frequencies can be extracted. The unwrapped phase can be solved by a simplified algorithm based on temporal phase unwrapping method from the relationship of the three wrapped phase at the same pixel. Thus, it is very suitable to measure the online complex and discontinuous objects at straight-line movement. The experimental results show the feasibility and the validity of the proposed method.     

Fundaments in Luminance and Retroreflectivity Measurements of Vertical Traffic Signs Using a Color Digital Camera

This paper is a study of the influences of the different parameters which affect the photometric evaluation of light-emitting surfaces (due to reflection or self-emission) when a conventional color digital camera is used. The overall purpose of this paper is to evaluate the luminance and the reflectivity of the vertical traffic sign with the camera in order to provide an automatic recognition of deteriorated reflective sheeting material of which the traffic signs were made. This paper describes how the A/D converter output signal given by a pixel of the digital camera can be related to the luminance and the reflectivity of the corresponding surface element whose image is formed on a pixel. Thus, each surface element of the traffic sign's surface can be separately evaluated. By photometrically calibrating the camera, we have been able to prove this relationship in our experiments.     

Safety performance of traffic phases and phase transitions in three phase traffic theory

Crash risk prediction models were developed to link safety to various phases and phase transitions defined by the three phase traffic theory. Results of the Bayesian conditional logit analysis showed that different traffic states differed distinctly with respect to safety performance. The random-parameter logit approach was utilized to account for the heterogeneity caused by unobserved factors. The Bayesian inference approach based on the Markov Chain Monte Carlo (MCMC) method was used for the estimation of the random-parameter logit model. The proposed approach increased the prediction performance of the crash risk models as compared with the conventional logit model. The three phase traffic theory can help us better understand the mechanism of crash occurrences in various traffic states. The contributing factors to crash likelihood can be well explained by the mechanism of phase transitions. We further discovered that the free flow state can be divided into two sub-phases on the basis of safety performance, including a true free flow state in which the interactions between vehicles are minor, and a platooned traffic state in which bunched vehicles travel in successions. The results of this study suggest that a safety perspective can be added to the three phase traffic theory. The results also suggest that the heterogeneity between different traffic states should be considered when estimating the risks of crash occurrences on freeways.     

The cooperative shift change: an illustration using air traffic control

We define the cooperative shift change and consider it from the perspective of four phases identified in Grusenmeyer (International Journal of Human Factors in Manufacturing, 5, 163–176, 1995): end-of-shift, arrival, meeting, and taking post. We describe the differences expected for the phases for both outgoing and incoming operators, discuss various domains that differ in their shift-change profile, and consider why those profile differences obtain. With this framework as a backdrop, we explore in detail the shift change, or position relief briefing (PRB), of air traffic control. This theoretical framework has the potential to aid in the classification and comparison of the transfer of responsibility in a variety of industrial tasks. This study could aid in the implementation of changes for air traffic control PRBs.     

Active transportation: Do current traffic safety policies protect non-motorists?

Objective

This study investigated the impact that state traffic safety regulations have on non-motorist fatality rates.

Methods

Data obtained from the National Highway Traffic Safety Administration (NHTSA), the Federal Highway Administration (FHWA), and the National Institute on Alcohol Abuse and Alcoholism (NIAAA) were analyzed through a pooled time series cross-sectional model using fixed effects regression for all 50 states from 1999 to 2009. Two dependent variables were used in separate models measuring annual state non-motorist fatalities per million population, and the natural log of state non-motorist fatalities. Independent variables measuring traffic policies included state expenditures for highway law enforcement and safety per capita; driver cell phone use regulations; graduated driver license regulations; driver blood alcohol concentration regulations; bike helmet regulations; and seat belt regulations. Other control variables included percent of all vehicle miles driven that are urban and mean per capita alcohol consumption per year.

Results

Non-motorist traffic safety was positively impacted by state highway law enforcement and safety expenditures per capita, with a decrease in non-motorist fatalities occurring with increased spending. Per capita consumption of alcohol also influenced non-motorist fatalities, with higher non-motorist fatalities occurring with higher per capita consumption of alcohol. Other traffic safety covariates did not appear to have a significant impact on non-motorist fatality rates in the models.

Conclusion

Our research suggests that increased expenditures on state highway and traffic safety and the initiation/expansion of programs targeted at curbing both driver and non-motorist intoxication are a starting point for the implementation of traffic safety policies that reduce risks for non-motorists.