Development of Crash Modification Factors for Uncontrolled Pedestrian Crossing Treatments

2017 ◽  
Author(s):  
Charles Zegeer ◽  
Raghavan Srinivasan ◽  
Bo Lan ◽  
Daniel Carter ◽  
Sarah Smith ◽  
...  
Keyword(s):  
Crash Modification Factors ◽  
Pedestrian Crossing

Development of Crash Modification Factors for Uncontrolled Pedestrian Crossing Treatments

2017 ◽  
Vol 2636 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Charlie Zegeer ◽  
Craig Lyon ◽  
Raghavan Srinivasan ◽  
Bhagwant Persaud ◽  
Bo Lan ◽  
...  
Keyword(s):  
The United States ◽  
Crash Risk ◽  
Limited Sample ◽  
Cross Sectional ◽  
Empirical Bayesian ◽  
Treatment Type ◽  
Crash Modification Factors ◽  
Pedestrian Crashes ◽  
Pedestrian Crossing ◽  
Crash Types

The objective of this study was to develop crash modification factors for four treatment types: rectangular rapid-flashing beacon (RRFB), pedestrian hybrid beacon (PHB), pedestrian refuge island (RI), and advance yield or stop markings and signs (AS). From 14 cities throughout the United States, 975 treatment and comparison sites were selected. Most of the treatment sites were selected at intersections on urban, multilane streets, because these locations present a high risk for pedestrian crashes and are where countermeasures typically are needed most. For each treatment site, relevant data were collected on the treatment characteristics, traffic, geometric, and roadway variables, and the pedestrian crashes and other crash types that occurred at each site. Cross-sectional regression models and before–after empirical Bayesian analysis techniques were used to determine the crash effects of each treatment type. All four of the treatment types were found to be associated with reductions in pedestrian crash risk, compared with the reductions at untreated sites. PHBs were associated with the greatest reduction of pedestrian crash risk (55% reduction), followed by RRFBs (47% reduction), RIs (32% reduction), and AS (25% reduction). The results for RRFBs had their basis in a limited sample and must be used with caution.

ENSURING THE PEDESTRIAN’S SAFETY DESIGN OF URBAN STREET CROSSWALKS

2019 ◽  
pp. 103-110
Author(s):  
Dmitriy Nemchinov
Keyword(s):  
Traffic Flow ◽  
Minimum Distance ◽  
Travel Speed ◽  
Vehicle Speed ◽  
Urban Street ◽  
Safety Design ◽  
Positive Practices ◽  
Time Required ◽  
Pedestrian Crossing ◽  
The City

The article presents an analysis of positive practices for ensuring the safety of pedestrians at the inter-section of the city streets carriageway, as well as a description of some innovations of regulatory and tech-nical documents, including an increased number of cases when a safety island can be arranged at a pedestri-an crossing. requirements for providing visibility at a pedestrian crossing to determine the minimum distance of visibility at a pedestrian crossing based on the time required pedestrians for crossing the roadway, recommended options for using ground unregulated pedestrian crossings on trapezoidal artificial irregularities according to GOST R 52605; traffic flow) and Z-shaped (also in the direction of the traffic flow), the requirements for the size of the securi-ty island have been established to allow put bicycle inside of safety island, a recommended set of measures to reduce the vehicle speed and describes the types of activities and describes a method of their application, describes methods zones device with reduced travel speed - residential and school zones, set requirements for turboroundabouts and methods of their design.

scholarly journals Impacts of mobile phone distractions on pedestrian crossing behavior at signalized intersections: An observational study in China

2019 ◽  
Vol 11 (4) ◽  
pp. 168781401984183 ◽  
Author(s):  
Zhuping Zhou ◽  
Sixian Liu ◽  
Wenxin Xu ◽  
Ziyuan Pu ◽  
Shuichao Zhang ◽  
...  
Keyword(s):  
Observational Study ◽  
Mobile Phone ◽  
Signalized Intersections ◽  
Pedestrian Crossing

Effect of pedestrian traffic light on traffic flow accompany with pedestrian crossing

2021 ◽  
pp. 126059
Author(s):  
Yanhong Wang ◽  
Chong Zhang ◽  
Pengbin Ji ◽  
Tianning Si ◽  
Zhenzhen Zhang
Keyword(s):  
Traffic Flow ◽  
Traffic Light ◽  
Pedestrian Traffic ◽  
Pedestrian Crossing

scholarly journals Analysis and Prediction of Pedestrians’ Violation Behavior at the Intersection Based on a Markov Chain

2021 ◽  
Vol 13 (10) ◽  
pp. 5690
Author(s):  
Chengyuan Mao ◽  
Lewen Bao ◽  
Shengde Yang ◽  
Wenjiao Xu ◽  
Qin Wang
Keyword(s):  
Markov Chain ◽  
Markov Chain Model ◽  
Warning System ◽  
Demographic Characteristics ◽  
Chain Model ◽  
Behavior Prediction ◽  
Road Geometry ◽  
Using Data ◽  
Pedestrian Crossing ◽  
Prediction Approach

Pedestrian violations pose a danger to themselves and other road users. Most previous studies predict pedestrian violation behaviors based only on pedestrians’ demographic characteristics. In practice, in addition to demographic characteristics, other factors may also impact pedestrian violation behaviors. Therefore, this study aims to predict pedestrian crossing violations based on pedestrian attributes, traffic conditions, road geometry, and environmental conditions. Data on the pedestrian crossing, both in compliance and in violation, were collected from 10 signalized intersections in the city of Jinhua, China. We propose an illegal pedestrian crossing behavior prediction approach that consists of a logistic regression model and a Markov Chain model. The former calculates the likelihood that the first pedestrian who decides to cross the intersection illegally within each signal cycle, while the latter computes the probability that the subsequent pedestrians who decides to follow the violation. The proposed approach was validated using data gathered from an additional signalized intersection in Jinhua city. The results show that the proposed approach has a robust ability in pedestrian violation behavior prediction. The findings can provide theoretical references for pedestrian signal timing, crossing facility optimization, and warning system design.

scholarly journals AoA-based Localization System using a Single IoT Gateway An Application for Smart Pedestrian Crossing

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Noori BniLam ◽  
Dennis Joosens ◽  
Rafael Berkvens ◽  
Jan Steckel ◽  
Maarten Weyn
Keyword(s):  
Localization System ◽  
Pedestrian Crossing

Observational-based study to explore pedestrian crossing behaviors at signalized and unsignalized crosswalks

2021 ◽  
Vol 151 ◽  
pp. 105990
Author(s):  
Kayvan Aghabayk ◽  
Javad Esmailpour ◽  
Ahmad Jafari ◽  
Nirajan Shiwakoti
Keyword(s):  
Pedestrian Crossing

scholarly journals Effectiveness of modified pedestrian crossing signs in an urban area

2021 ◽  
Author(s):  
Stephen A. Arhin ◽  
Adam Gatiba ◽  
Melissa Anderson ◽  
Babin Manandhar ◽  
Melkamsew Ribbisso ◽  
...  
Keyword(s):  
Urban Area ◽  
Pedestrian Crossing

scholarly journals A Lightweight Motional Object Behavior Prediction System Harnessing Deep Learning Technology for Embedded ADAS Applications

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 692
Author(s):  
Wen-Chia Tsai ◽  
Jhih-Sheng Lai ◽  
Kuan-Chou Chen ◽  
Vinay M.Shivanna ◽  
Jiun-In Guo
Keyword(s):  
Embedded System ◽  
Moving Objects ◽  
Object Localization ◽  
Crossing Over ◽  
Learning Technology ◽  
Prediction System ◽  
Behavior Prediction ◽  
Detection Model ◽  
Pedestrian Crossing ◽  
Object Behavior

This paper proposes a lightweight moving object prediction system to detect and recognize pedestrian crossings, vehicles cutting-in, and vehicles ahead applying emergency brakes based on a 3D Convolution network for behavior prediction. The proposed design significantly improves the performance of the conventional 3D convolution network (C3D) adapted to predict the behaviors employing behavior recognition network capable of performing object localization, which is pivotal in detecting the numerous moving objects’ behaviors, combining and verifying the detected objects with the results of the YOLO v3 detection model with that of the proposed C3D model. Since the proposed system is a lightweight CNN model requiring far lesser parameters, it can be efficiently realized on an embedded system for real-time applications. The proposed lightweight C3D model achieves 10 frames per second (FPS) on a NVIDIA Jetson AGX Xavier and yields over 92.8% accuracy in recognizing pedestrian crossing, over 94.3% accuracy in detecting vehicle cutting-in behavior, and over 95% accuracy for vehicles applying emergency brakes.

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