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51.
Collecting microscopic pedestrian behavior and characteristics data is important for optimizing the design of pedestrian facilities for safety, efficiency, and comfortability. This paper provides a framework for the automated classification of pedestrian attributes such as age and gender based on information extracted from their walking gait behavior. The framework extends earlier work on the automated analysis of gait parameters to include analysis of the gait acceleration data which can enable the quantification of the variability, rhythmic pattern and stability of pedestrian’s gait. In this framework, computer vision techniques are used for the automatic detection and tracking of pedestrians in an open environment resulting in pedestrian trajectories and the speed and acceleration dynamic profiles. A collection of gait features are then derived from those dynamic profiles and used for the classification of pedestrian attributes. The gait features include conventional gait parameters such as gait length and frequency and dynamic parameters related to gait variations and stability measures. Two different techniques are used for the classification: a supervised k-Nearest Neighbors (k-NN) algorithm and a newly developed semi-supervised spectral clustering. The classification framework is demonstrated with two case studies from Vancouver, British Columbia and Oakland, California. The results show the superiority of features sets including gait variations and stability measures over features relying only on conventional gait parameters. For gender, correct classification rates (CCR) of 80% and 94% were achieved for the Vancouver and Oakland case studies, respectively. The classification accuracy for gender was higher in the Oakland case which only considered pedestrians walking alone. Pedestrian age classification resulted in a CCR of 90% for the Oakland case study. 相似文献
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Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams.It is necessary to consider human-factors in CF modeling for a more realistic representation of CF behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of CF models available in the literature, none of these specifically focuses on the human factors in these models.This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area. 相似文献
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Estelle Chevallier Ludovic Leclercq 《Transportation Research Part B: Methodological》2007,41(10):1139-1150
The following paper presents a dynamic macroscopic model for unsignalized intersections which accounts for time-limited disruptions in the minor stream flow, even in free-flow conditions when the average flow demand is satisfied. It introduces a deterministic fictive traffic light to represent an average alternating sequence of available and busy time periods for insertion depending on the major stream flow. Two allocation schemes of the total outflow during green periods are developed to model the influence or non-influence of the minor stream over the major stream flow. The aggregation of the resulting dynamic flow variations gives relevant capacity values. Moreover, the model predicts accurate average vehicle delay and queue length estimates compared to theoretical and empirical data. It has three easy-to-measure parameters and can be integrated into a dynamic macroscopic simulation tool for urban networks. 相似文献
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An analysis of the determinants of children’s weekend physical activity participation 总被引:1,自引:0,他引:1
This paper examines the out-of-home, weekend, time-use patterns of children aged 5–17 years, with a specific emphasis on their
physical activity participation. The impact of several types of factors, including individual and household demographics,
neighborhood demographics, built environment characteristics, and activity day variables, on physical activity participation
is analyzed using a joint nested multiple discrete–continuous extreme value-binary choice model. The sample for analysis is
drawn from the 2000 San Francisco Bay Area Travel Survey. The model developed in the paper can be used to assess the impacts
of changing demographics and built environment characteristics on children’s physical activity levels. 相似文献
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沥青路面的结构行为方程为基于性能的沥青路面结构设计方法奠定了良好的理论基础,但先前的研究仅较好地考虑了荷载、环境和结构等因素对沥青路面使用性能的影响,而对材料因素的影响考虑得较为粗略。鉴于材料影响的复杂性,论文从较为宏观的角度通过改性沥青和普通沥青结构行为方程和现场疲劳方程的建立给出改性沥青影响系数与改性-普通沥青寿命比值的关系,从而利用此关系以及通过试验获得的改性沥青和普通沥青混凝土的疲劳方程即可确定结构行为方程中的材料影响系数。 相似文献