Dynamic Routing Combined to Forecast the Behavior of Traffic in the City of Sao Paulo Using Neuro Fuzzy Network

The challenge of keeping and getting new customers drives the development of new practices to meet the consumption needs of increasingly tends to micro-segmentation of product and consumer market. The new consumption habits of brazilians brought new prospects for market. The objective of this paper is to develop of a dynamic vehicle routing system supported by the behavior of urban traffic in the city ofSao Paulo using Neuro Fuzzy Network. The methodology of this paper consists in the capture of relevant events that interfere with the flow of traffic of the city of Sao Paulo and implementation of a Fuzzy Neural Network trained with these events in order to foresee the traffic behavior. The system offers three labels of hierarchical routing, thus is possible to consider not only the basic factors of routing, but too external factors that directly influence on the flow of traffic and the disruption which may be avoided in large cities, through alternative routes （dynamic vehicle routing）. Predicting the behavior of traffic represents the strategic level routing, dynamic vehicle routing is the tactical level, and routing algorithms to the operational level. This paper will not be discussed the operational level.

Video-based measurement and data analysis of traffic flow on urban expressways

A new video-based measurement is proposed to collect and investigate traffic flow parameters. The output of the measurement is velocity-headway distance data pairs. Because density can be directly acquired by the reciprocal of headway distance, the data pairs have the advantage of better simultaneity than those from common detectors. By now, over 33 000 pairs of data have been collected from two road sections in the cities of Shanghai and Zhengzhou. Through analyzing the video files recording traffic movements on urban expressways, the following issues are studied：laws of vehicle velocity changing with headway distance, proportions of di0erent driving behaviors in the traffic system, and characteristics of traffic flow in snowy days. The results show that the real road traffic is very complex, and factors such as location and climate need to be taken into consideration in the formation of traffic flow models.

Nonlinear Dynamic Analysis of MPEG-4 Video Traffic

The main research motive is to analysis and to veiny the inherent nonlinear character of MPEG-4 video. The power spectral density estimation of the video trafiic describes its 1/f^β and periodic characteristics.The priraeipal compohems analysis of the reconstructed space dimension shows only several principal components can be the representation of all dimensions. The correlation dimension analysis proves its fractal characteristic. To accurately compute the largest Lyapunov exponent, the video traffic is divided into many parts.So the largest Lyapunov exponent spectrum is separately calculated using the small data sets method. The largest Lyapunov exponent spectrum shows there exists abundant nonlinear chaos in MPEG-4 video traffic. The conclusion can be made that MPEG-4 video traffic have complex nonlinear be havior and can be characterized by its power spectral density,principal components, correlation dimension and the largest Lyapunov exponent besides its common statistics.

Characteristics and risk of violation behavior of non-motorists at signalized intersections

Aiming at prevalent violations of non-motorists at urban intersections in China, this paper intends to clarify the characteristics and risks of non-motorist violations at signalized intersections through questionnaires and video recordings, which may serve as a basis for non-motorized vehicle management. It can help improve the traffic order and enhance the degree of safety at signalized intersections. To obtain the perception information, a questionaire survey on the Internet was conducted and 972 valid questionnaires were returned. It is found that academic degree contributes little to non-motorist violations, while electrical bicyclists have a relatively higher frequency of violations compared with bicyclists. The video data of 18 228 non-motorist behaviors indicate that the violation rate of all non-motorists is 26.5%; the number of conflicts reaches 1 938, among which violation conflicts account for 66.8%. The study shows that the violation rates and the violation behavior at three types of surveyed intersections are markedly different. It is also concluded that the conflict rates and the violation rates are positively correlated. Furthermore, signal violation, traveling in the wrong direction, and overspeeding to cross the intersection are the most dangerous among traffic violation behaviors.

Effects of traffic noise on pupils'behavior in classroom

Noise surveys in this country reported that a large number of classrooms in primary and secondary schools in the urban areas were disturbed by environmental noise, particularly by traffic noise. A series of psychological tests were conducted to identify pupils' behavior in a classroom under different noise levels within the range of 40 to 70 dBA. Statistical analysis results were obtained by using Relational Data Analysis System (RDAS) software. According to the t-test and single factor variance analysis of the results, significant differences of the pupils' behavior in the classroom have been observed when the percentile exceeded sound level either L50 exceeds 50 dBA or L10 exceeds 55 dBA, or the equivalent continuous sound level Leq exceeds 50 dBA. The same conclusion has been drawn from the average percentages of syllable articulation under different noise levels in a classroom which were the results of tests made in accordance with the procedure described in the National Standard. The maximum acceptable noise level in the classroom thus can be determined.

Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series Model

Time headway is an important index used in characterizing dangerous driving behaviors. This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence. An autoregressive（AR） time-series model is improved and adopted to describe the dynamic variations of average daily time headway. Based on the model, a simple approach for dangerous driving behavior recognition is proposed with the aim of significantly decreasing headway. The effectivity of the proposed approach is validated by means of empirical data collected from a medium-sized city in northern China. Finally, a practical early-warning strategy focused on both the remaining life and low headway is proposed to remind drivers to pay attention to their driving behaviors and the possible occurrence of crash-related risks.

Relationship between religion and school students＇ road behavior in southern Iran

Purpose： Unsafe behaviors are an important cause of accidents in adolescent age groups. This study was designed to examine the behaviors of adolescent pedestrians in southern Iran. Methods： This is a descriptive analytical cross-sectional study. The study population consisted of high school students in Shiraz, capital city of Fars Province, Iran. Five hundred and sixteen students were selected by multi-stage sampling. Data were collected by the use of three questionnaires, which included Persian copies of adolescent road user behavior questionnaire （ARBQ）, Duke University Religious Index （DUREL）, as well as the context and independent variables questionnaire. Results： The results showed that a decrease in dangerous behaviors on the road resulted in an increase in respondents＇ intrinsic religiosity. Also, engagement in unsafe crossing behavior in the road decreased with increasing respondents＇ intrinsic religiosity. Another finding showed that female students were less involved in dangerous play and planned protective behaviors on the road. Conclusion： Findings clearly indicate that intrinsic religiosity has a significant role in reducing the risky road behaviors of students. Hence, religion may improve road safety in school students＇ road behavior in Iran.