Two-Step k-means Clustering Based Information Entropy for Detecting Environmental Barriers Using Wearable Sensor

Walking is the most basic means of transportation. Therefore, continuous management of the walking environment is very important. In particular, the identification of environmental barriers that can impede walkability is the first step in improving the pedestrian experience. Current practices for identifying environmental barriers (e.g., expert investigation and survey) are time-consuming and require additional human resources. Hence, we have developed a method to identify environmental barriers based on information entropy considering that every individual behaves differently in the presence of external stimuli. The behavioral data of the gait process were recorded for 64 participants using a wearable sensor. Additionally, the data were classified into seven gait types using two-step k-means clustering. It was observed that the classified gaits create a probability distribution for each location to calculate information entropy. The values of calculated information entropy showed a high correlation in the presence or absence of environmental barriers. The results obtained facilitated the continuous monitoring of environmental barriers generated in a walking environment.

THE EVALUATION OF PEDESTRIAN FACILITIES ON HAJJ CROWD BETWEEN ARAFAT AND MUZDALIFAH PEDESTRIAN STREET

Makkah is the holy city of Muslims which is located in the southwest of Saudi Arabia. It is the being visited by pilgrims from all nationalities every year for the annual Islamic Pilgrimage (Hajj). Hajj is the fifth pillar of Islam which is the largest annual religious pilgrimage event in the world. The Hajj management authority specifies that the current pilgrimage’s performance is challenging due to the increase of pilgrims every year. Pedestrian conflicts and uncomfortable walking environment are the crucial issues that have been identified, which are due to insufficient pedestrian facilities. Hence, this paper presents the pedestrian facilities assessment between Arafat to Muzdalifah road. The objectives of the study are to determine the available pedestrian facilities for pilgrimage from Arafat to Muzdalifah, and to suggest the suitable solution for pedestrian facilities in every 5 minutes walks. Meanwhile, qualitative methods of site inventory and observation were applied to gather the related data on the selected study area. Possible pedestrian facilities design is suggested for the purpose of future Hajj improvement.

Evaluation of Walking Comfort in Children’s School Travel at Street Scale: A Case Study in Tianjin (China)

(1) Background: school travel is an important part of a child’s daily activities. A comfortable walking environment can encourage children to walk to school. The existing methods of evaluating walking environments are not specific to children’s walks to school. (2) Methods: this study proposes a method of evaluating walking comfort in children traveling to school at street scale. Related indexes were selected that reflect children’s school travel behavior and their needs in street environments based on walking environment audit tools. Factor analysis was then used to calculate the relative weight of each index. (3) Results: the new evaluation method was tested in the neighborhoods around the First Central Primary School in Hedong District, Tianjin, China. The walking comfort for children’s school travel was evaluated in eight indexes: effective street width; street flatness; street cleanliness; interface diversity; buffer; shade coverage; green looking ratio; and sound decibels. Different classes and types of streets were found to have various vulnerabilities. (4) Conclusions: this evaluation method can accurately locate the weak spots in streets to improve the local policymakers’ perception of street environments, which can greatly facilitate the implementation of precise measures to promote children walking to school.

Wearable Inertial Gait Algorithms: Impact of Wear Location and Environment in Healthy and Parkinson’s Populations

Wearable inertial measurement units (IMUs) are used in gait analysis due to their discrete wearable attachment and long data recording possibilities within indoor and outdoor environments. Previously, lower back and shin/shank-based IMU algorithms detecting initial and final contact events (ICs-FCs) were developed and validated on a limited number of healthy young adults (YA), reporting that both IMU wear locations are suitable to use during indoor and outdoor gait analysis. However, the impact of age (e.g., older adults, OA), pathology (e.g., Parkinson′s Disease, PD) and/or environment (e.g., indoor vs. outdoor) on algorithm accuracy have not been fully investigated. Here, we examined IMU gait data from 128 participants (72-YA, 20-OA, and 36-PD) to thoroughly investigate the suitability of ICs-FCs detection algorithms (1 × lower back and 1 × shin/shank-based) for quantifying temporal gait characteristics depending on IMU wear location and walking environment. The level of agreement between algorithms was investigated for different cohorts and walking environments. Although mean temporal characteristics from both algorithms were significantly correlated for all groups and environments, subtle but characteristically nuanced differences were observed between cohorts and environments. The lowest absolute agreement level was observed in PD (ICC2,1 = 0.979, 0.806, 0.730, 0.980) whereas highest in YA (ICC2,1 = 0.987, 0.936, 0.909, 0.989) for mean stride, stance, swing, and step times, respectively. Absolute agreement during treadmill walking (ICC2,1 = 0.975, 0.914, 0.684, 0.945), indoor walking (ICC2,1 = 0.987, 0.936, 0.909, 0.989) and outdoor walking (ICC2,1 = 0.998, 0.940, 0.856, 0.998) was found for mean stride, stance, swing, and step times, respectively. Findings of this study suggest that agreements between algorithms are sensitive to the target cohort and environment. Therefore, researchers/clinicians should be cautious while interpreting temporal parameters that are extracted from inertial sensors-based algorithms especially for those with a neurological condition.

Pedestrianization Impacts on Air Quality Perceptions and Environment Satisfaction: The Case of Regenerated Streets in Downtown Seoul

Previous studies have investigated the increased volume of pedestrians to establish success rates of the pedestrian-friendly policy after a street redesign intervention. However, few studies have focused on the effect of street regeneration on air quality perception and user satisfaction. The influence of the physical environment on street vitality may vary, depending on area context and regional factors. A comprehensive understanding of effective interventions could increase pedestrians’ satisfaction with their walking environment. This study examines the effect of pedestrianization on individuals’ air quality perception and satisfaction, based on three regenerated streets in Seoul, Korea. We analyzed data from 672 questionnaires administered after the pedestrianization project. We used a subset of variables in a binary logistic regression model to understand general determinants of user satisfaction toward their walking environment. Our case study contributes to the verification of pedestrianization effects on air quality perceptions. Results show that overall satisfaction could be acquired through positive perceptions of air quality, as achieved through pedestrianization of streets. Moreover, pedestrian satisfaction varies according to the purpose, activities and health-related behaviors and attitudes. The interrelationships between environmental health, activity, satisfaction and quality of life provide design insights to consider when implementing pedestrianization projects in the future.

Phone-Related Distracted Walking Injuries as a Function of Age and Walking Environment

Using phones while walking has been a factor that has led to accidents and injuries. However, few studies have analyzed the propensity of injuries due to distracted walking for different age groups and in different types of walking environments. This study aims to examine the number of emergency department (ED) visits due to distracted walking across different age groups and walking environments using a publicly available dataset, the National Electronic Injury Surveillance System (NEISS) database. The results suggest that there were an estimated 29140 distracted walking injuries between the years 2011-2019. Individuals between 11 and 20 years old had the most injuries, followed by 21 to 30, and 31 to 40. Furthermore, the proportion of estimated injuries that occurred in different walking environments differed across age groups. Safety-orient interventions for future research for stairs and home environments were also recommended in the present study.

Investigating Built Environment Indicators to Develop a Local Walkability Index

Many studies have been conducted over the last 20 years to determine and measure factors that affect the walkability of city streets. Walkability is an essential factor in deciding whether a city is green or sustainable. This paper creates a comprehensive walkability index by analysing built environmental indicators that affect walkability. This research was conducted on mixed land use streets in Cairo, Egypt, combining the results from an online survey and a walkability assessment model developed by multi-criteria decision analysis techniques. The results were based on a three-pillar approach starting with the theoretical background to frame the walkability indicator, numerical assessment over the Egyptian cases using a multi-criteria decision-making (MCDM) technique and a qualitative user perception survey. Our results confirm that determining to what extent Cairo’s streets are walkable is crucial to enhancing pedestrians’ perceptions of the walking environment. Furthermore, the results illustrated the essential factors within the built environment indicators that influence pedestrian walking behaviour.