Application of a regression model for predicting traffic volume from dynamic monitoring data to the bridge safety evaluation

2017 ◽  
Vol 7 (4) ◽  
pp. 429-443 ◽  
Author(s):  
Kaiwan Wattana ◽  
Mayuko Nishio
Keyword(s):  
Regression Model ◽  
Safety Evaluation ◽  
Traffic Volume ◽  
Monitoring Data ◽  
Dynamic Monitoring ◽  
Bridge Safety

scholarly journals Structural Safety Evaluation of Tunnel Based on the Dynamic Monitoring Data during Construction

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiaokun Yan ◽  
Hu Li ◽  
Feng Liu ◽  
Yang Liu
Keyword(s):  
Safety Evaluation ◽  
Constitutive Relationship ◽  
Monitoring Data ◽  
Dynamic Monitoring ◽  
Structural Safety ◽  
Underground Excavation ◽  
Tunnel Excavation ◽  
Evaluation Approach ◽  
Relationship Of ◽  
Shallow Buried Tunnel

It is still a challenge to accurately evaluate the structural safety of tunnel during the process of construction. To address this issue, a safety evaluation approach of tunnel based on the monitoring data during construction is proposed in this study. Firstly, the detailed description of modelling the tunnel excavation, releasing the load acting on the tunnel, and selecting the constitutive relationship of surrounding rock of tunnel is introduced. Secondly, aiming at an actual shallow-buried tunnel with underground excavation, utilizing the analytical results of deformation of tunnel, the structural safety of tunnel is evaluated by using a reliability-based method. Finally, the effectiveness of the proposed method is demonstrated by using the dynamic monitoring data obtained during the construction of an actual tunnel.

scholarly journals Real-Time Safety Optimization of Connected Vehicle Trajectories Using Reinforcement Learning

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3864
Author(s):  
Tarek Ghoul ◽  
Tarek Sayed
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Low Cost ◽  
Safety Evaluation ◽  
Traffic Volume ◽  
Connected Vehicles ◽  
Connected Vehicle ◽  
Real World Data ◽  
Physical Constraints ◽  
Traffic Conflicts

Speed advisories are used on highways to inform vehicles of upcoming changes in traffic conditions and apply a variable speed limit to reduce traffic conflicts and delays. This study applies a similar concept to intersections with respect to connected vehicles to provide dynamic speed advisories in real-time that guide vehicles towards an optimum speed. Real-time safety evaluation models for signalized intersections that depend on dynamic traffic parameters such as traffic volume and shock wave characteristics were used for this purpose. The proposed algorithm incorporates a rule-based approach alongside a Deep Deterministic Policy Gradient reinforcement learning technique (DDPG) to assign ideal speeds for connected vehicles at intersections and improve safety. The system was tested on two intersections using real-world data and yielded an average reduction in traffic conflicts ranging from 9% to 23%. Further analysis was performed to show that the algorithm yields tangible results even at lower market penetration rates (MPR). The algorithm was tested on the same intersection with different traffic volume conditions as well as on another intersection with different physical constraints and characteristics. The proposed algorithm provides a low-cost approach that is not computationally intensive and works towards optimizing for safety by reducing rear-end traffic conflicts.

Bridge-safety evaluation using ultrasonic stress measurement

1996 ◽  
Author(s):  
Al V. Clark ◽  
Margarit G. Lozev ◽  
P. A. Fuchs
Keyword(s):  
Stress Measurement ◽  
Safety Evaluation ◽  
Bridge Safety ◽  
Ultrasonic Stress Measurement

Study on the Information Processing Technology of Deformation Monitoring Data in the Underground Engineering

2013 ◽  
Vol 353-356 ◽  
pp. 1555-1558
Author(s):  
Ke Wu ◽  
Ke Zhang ◽  
Cheng Jun Wang ◽  
Chuang Zhao
Keyword(s):  
Data Processing ◽  
Measurement Data ◽  
Processing System ◽  
Deformation Monitoring ◽  
Surrounding Rock ◽  
Monitoring Data ◽  
Dynamic Monitoring ◽  
Information Control ◽  
Underground Engineering ◽  
Engineering Construction

The deformation monitoring of surrounding rock and data processing in tunnel is the foundation and safety technical support of underground engineering information control and management. However, due to the special environment in the underground engineering construction, acquiring the deformation information of surrounding rock accurately and fast to assess the stability of surrounding rock is becoming one of the bottleneck problems for underground construction project information to be solved. According to the underground engineering projects, Based on the dynamic monitoring data processing and analysis, a set of underground engineering construction monitoring measurement data processing system is established, which can meet the acquisition of the monitoring measurement data, the arrangement of the measured data, data analysis and feedback, the monitoring data regression analysis.

Implementation of a Web Platform to Present Real Time Dynamic Monitoring Data from Heritage Structures

2019 ◽  
pp. 2245-2253
Author(s):  
David Fosca ◽  
Patricia Pórcel ◽  
Giacomo Zonno ◽  
Benjamín Castañeda ◽  
Rafael Aguilar
Keyword(s):  
Real Time ◽  
Monitoring Data ◽  
Dynamic Monitoring ◽  
Time Dynamic ◽  
Web Platform

scholarly journals Dynamic Monitoring and Stability Analysis of Rock-bolted Crane Girder In large Cavern With Layered Surrounding Rock

2020 ◽  
Vol 165 ◽  
pp. 03025
Author(s):  
Jing Liu ◽  
Xiaomin Liu ◽  
Shengjie Di ◽  
Xi Lu
Keyword(s):  
Stability Analysis ◽  
Stability Condition ◽  
Stress Condition ◽  
Surrounding Rock ◽  
Monitoring Data ◽  
Dynamic Monitoring ◽  
Power Station ◽  
Load Bearing ◽  
Underground Cavern ◽  
Normal Law

The large and medium-sized hydropower projects underground cavern group are basically in relatively integrate surrounding rock, so there are few engineering examples in layered surrounding rock with type III surrounding rocks as the main rock, and lack of successful experience. According to rock-bolted crane girder under the layered surrounding rock of a large underground power station, analyzing prototype dynamic monitoring data of the excavation, unloading and load-bearing test .The distribution of the monitoring data conforms to the normal law, and there are no large outliers, under the action of a large number of bolts, rock-bolted crane girder basically forms a good integrity with the layered surrounding rock, and the load-bearing test has no effect on the stress condition and stability condition of surrounding rock.

Design Optimization and Safety Evaluation of Cross-Sea Bridge Barrier

2011 ◽  
Vol 97-98 ◽  
pp. 100-107
Author(s):  
Lei Fang ◽  
Liang Zhang ◽  
Shu Ming Yan ◽  
Ning Jia ◽  
Min Jing ◽  
...  
Keyword(s):  
Design Optimization ◽  
Impact Test ◽  
Safety Evaluation ◽  
Full Scale ◽  
Finite Elements Analysis ◽  
Acceptance Criteria ◽  
Analysis And Design ◽  
Bridge Safety ◽  
Study Results ◽  
New Type

By comprehensive analysis and design optimization of barrier structure parameters, a new type of beam-and-post steel barrier was invented according to impact test condition and acceptance criteria of cross-sea bridge barrier. Full-scale impact tests and finite elements analysis were conducted to do safty evalution of the barrier. The results show that, ASI value is 1.62 for test and that is 1.67 for FEA, THIV is 30.7km/h for test and that is 31.2km/h for FEA. Working width is 0.88m for test and that is 0.62m for FEA. Occupant risk evaluation index can meet the requirements of level B and the working width can meet the requirements of level W3. Both of tracking and posture of vehicles are well. The study results above show that safety performance of cross-sea bridge barrier can meet or exceed the acceptance criteria. FEA results are consistent with Full-scale impact test, which validate the reliability of FEA. cross-sea bridge barrier can meet the highest test level for beam-and-post steel barrier, which can defend the out-of-control vehicles effectively and help to ensure the bridge safety.

scholarly journals Model for Estimating Travel Time on Dynamic Highway Networks in Akure, Ondo State Nigeria

2020 ◽  
Vol 5 (3) ◽  
pp. 275-281
Author(s):  
Onyemaechi John Nnamani ◽  
Victor Ayodele Ijaware ◽  
Joseph Olalekan Olusina ◽  
Timothy Oluwadare Idowu
Keyword(s):  
Regression Model ◽  
Travel Time ◽  
Traffic Volume ◽  
Real Field ◽  
Percentage Error ◽  
Time Variability ◽  
Time Model ◽  
Independent Variables ◽  
Highway Networks ◽  
Significant Difference

Travel time variability or distribution is very important to travel time reliability studies in transportation systems. This study aimed at developing a multivariate regression model for estimating travel times for dynamic highway networks in Akure Metropolis. The independent variables for the model are Traffic volume, density, speed of vehicles, and traffic flow while the dependent response variable is the Travel time. The estimated travel time was compared with the observed travel time from the real field data and the estimation using the regression model reveals a significant level of accuracy. Also, it was discovered that traffic volume, speed, density, and flow were highly correlated with travel time. The result analyzed using descriptive statistics in the SPSS software environment reveals an R2 value of 0.998, thereby indicating that the independent variables accounted for 99% of travel time in the study area. The Hypothesis tested at 95% confidence level using ANOVA unveils that there is no significant difference between the observed and estimated travel time model. The Mean Absolute Percentage Error (MAPE) of 0.049 shows that the model performed very well and was very efficient for analyzing the probabilistic relation between travel time and the independent variables. The study recommends the use of the developed travel time model for estimating travel time within the study area.

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