Pedestrian Features Research Articles

Modeling bi-direction pedestrian flow by cellular automata and complex network theories

In this paper the experiment to study the features of pedestrians' walking preference is designed. Then the cellular automata model which considering pedestrians' walking preference features is built, in which the forward-parameter, right-parameter, surpass-parameter and the correction-parameters are included to mend the probability of the pedestrian getting to each neighboring cell. Based on this model and k-nearest-neighbor interaction pattern, the complex network of pedestrians is modeled. The simulation results obtained from the model well illustrate the density-speed curve and density-volume curve. Meanwhile the self-organization phenomena of the bi-direction pedestrian flow can be observed from the model simulation. In the further analysis of the pedestrian flow's basic parameter and the main feature parameters of pedestrians' complex network, it is found out that the average speed and the average path length are changed with the state of the flow. Finally it can be concluded that there is a linear negative correlation between these two parameters by fitting the data; in other words, pedestrian flow with shorter average-path length has a higher average speed.

Neighborhood and PA: Neighborhood Factors and Physical Activity in African American Public Housing Residents

In the US, public housing developments are typically located in lower socioeconomic status neighborhoods that may have poorer quality street level conditions, placing residents in neighborhoods that are less supportive for physical activity (PA). This study investigated the relationship of detailed, objectively assessed street-level pedestrian features with self-reported and measured PA in African American public housing residents. Every street segment (N = 2093) within an 800 m radius surrounding each housing development (N = 12) was systematically assessed using the Pedestrian Environment Data Scan (PEDS). Participants completed an interviewer administered International Physical Activity Questionnaire (IPAQ) Short Form and wore a pedometer for 1 week. Women reported significantly less vigorous (mean = 1955 vs. 2896 METs), moderate (mean = 733 vs. 1309 mets), walking (mean = 1080 vs. 1376 METs), and total (mean = 3768 vs. 5581 METs) PA on the IPAQ compared with men (all P <.05). Women took fewer pedometer steps per day (M = 3753 vs. 4589) compared with men, but this was not statistically significant. Regression analyses showed that for women, lower speed limits were associated with vigorous; higher street segment density was associated with more moderate PA; lower speed limits, fewer crossing aids, and more lanes were associated with more walking; and, fewer lanes was associated with more overall PA. For men, fewer sidewalk connections were associated with more moderate PA; lower speed limits were associated with more walking; and, lower speed limits was associated with more overall PA. Neighborhood factors influence physical activity; in particular, lower speed limits appear most commonly linked with increased physical activity in both men and women.

Feature subset selection based on co-evolution for pedestrian detection

An appropriate subset of features is needed for a classification-based pedestrian detection system since its performance is greatly affected by the features adopted. Moreover, the combination of different types of features (eg, grey-scale, colour) could improve the detection accuracy, so it is helpful to obtain a feature subset and the proportion of each type simultaneously for the classifier. However, because a larger number and various types of features are generally extracted to represent pedestrians better, it is difficult to achieve this. This paper proposed a co-evolutionary method to solve this problem. In the feature subset selection method, each sub-population mapped to one type of pedestrian feature, and then all sub-populations evolved co-operatively to obtain an optimal feature subset. Moreover, a strategy was specially designed to adjust the sub-population size adaptively in order to improve the optimizing performance. The proposed method has been tested on pedestrian detection applications and the experimental results illustrate its better performance compared with other methods such as genetic algorithm and AdaBoost.

Pedestrian detection and tracking based on SACON background model

A new background modeling method based on Sample Consensus (SACON) was proposed for detecting foreground objects. The method, which has higher accuracy than other five popular methods in the experiment when seven typical video sequences were adopted, is suit for detecting and tracking the moving target under complex circumstances. On pedestrian detection and tracking, considering the target to be non-rigid, a new target appearance model containing spatial domain and color information was built based on SACON. The experimental results show that the method can describe pedestrian feature exactly and can detect or track targets with barriers and similar color and small targets with high accuracy.

Walking pedestrian recognition

In previous years, many methods providing the ability to recognize rigid obstacles-sedans and trucks-have been developed. These methods provide the driver with relevant information. They are able to cope reliably with scenarios on motorways. Nevertheless, not much attention has been given to image processing approaches to increase the safety of pedestrians in urban environments. In the paper, a method for the detection, tracking, and final recognition of pedestrians crossing the moving observer's trajectory is suggested. A combination of data- and model-driven approaches is realized. The initial detection process is based on a fusion of texture analysis, model-based grouping of, most likely, the geometric features of pedestrians, and inverse-perspective mapping (binocular vision). Additionally, motion patterns of limb movements are analyzed to determine initial object-hypotheses. The tracking of the quasirigid part of the body is performed by different algorithms that have been successfully employed for the tracking of sedans, trucks, motorbikes, and pedestrians. The final classification is obtained by a temporal analysis of the walking process.

Bicycle and Pedestrian Level-of-Service Performance Measures and Standards for Congestion Management Systems

The Gainesville Mobility Plan Prototype was developed as the congestion management system plan for Gainesville, Florida, and incorporated level-of-service (LOS) performance measures for bicycle and pedestrian facilities. The LOS evaluations describe the degree of bicycle and pedestrian accommodation in a transportation corridor. The bicycle LOS measures are designated basic facility provided, conflicts, speed differential, motor vehicle LOS, maintenance, and provision of transportation demand management programs or intermodal links. Pedestrian LOS criteria are similar and incorporate specific pedestrian features. The Gainesville bicycle and pedestrian LOS performance measures use a point scale resulting in an LOS rating system of A through F. The scoring system was developed with sensitivity to characteristics that may be mutually exclusive or inclusive to determine all possible combinations of points. The methodology hypothesizes that there is a critical mass of variables that must be present to attract ...

Bicycle and Pedestrian Level-of-Service Performance Measures and Standards for Congestion Management Systems

The Gainesville Mobility Plan Prototype was developed as the congestion management system plan for Gainesville, Florida, and incorporated level-of-service (LOS) performance measures for bicycle and pedestrian facilities. The LOS evaluations describe the degree of bicycle and pedestrian accommodation in a transportation corridor. The bicycle LOS measures are designated basic facility provided, conflicts, speed differential, motor vehicle LOS, maintenance, and provision of transportation demand management programs or intermodal links. Pedestrian LOS criteria are similar and incorporate specific pedestrian features. The Gainesville bicycle and pedestrian LOS performance measures use a point scale resulting in an LOS rating system of A through F. The scoring system was developed with sensitivity to characteristics that may be mutually exclusive or inclusive to determine all possible combinations of points. The methodology hypothesizes that there is a critical mass of variables that must be present to attract nonmotorized trips. The methodology is applicable for corridor evaluations on arterial and collector roadways in urban or suburban areas. The criteria include measures of programmatic and off-street projects such as rail-trails, bicycle parking, bikes-on-transit, employer-based programs, and so forth, in addition to traditional on-street facility improvements. By measuring such improvements recommendations for more diverse projects can be supported. This analysis was applied to several roadways with promising results that generally corresponded to user perceptions of the facilities. LOS evaluation was used as a tool of the congestion management system to develop project recommendations and priorities, but it may also be useful in concurrency and long-range transportation planning.