scholarly journals Illegal parking road recognition based on video detection equipment

2018 ◽  
Vol 232 ◽  
pp. 02055
Author(s):  
Xinyue Fan ◽  
Qi Shen ◽  
Qinglong He
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
Adaptive Method ◽  
Calculation Model ◽  
Descent Method ◽  
Steepest Descent Method ◽  
Travel Time Reliability ◽  
Video Detection ◽  
Actual Use ◽  
Network Status

Based on the big data collected by the video detection equipment, the network topology table of the city level video detection equipment is constructed by using the time relation and the spatial position relation of the data. By using the steepest descent method and adaptive method, the travel confidence time randomness model is constructed, which can describe whether a traveler can finish his travel time on time. It overcomes the shortcomings of the existing travel time reliability calculation model, which is difficult to combine with the actual use of video detection equipment data, then examples analysis are followed. The results show that, for the data collected by the video detection device, the travel confidence time randomness model is more accurate than the existing models. It can describe the probability of the traveler arriving at the destination in a given time more accurately, which can be used to identify illegal parking road and provide a reliable basis for traffic management departments in traffic planning, dividing road network status and traffic situation prediction.

Evaluation of Operational Effects of I-66 Active Traffic Management System

2017 ◽  
Vol 2616 (1) ◽  
pp. 91-103 ◽  
Author(s):  
PilJin Chun ◽  
Michael D. Fontaine
Keyword(s):  
Travel Time ◽  
Traffic Management ◽  
Management System ◽  
Travel Time Reliability ◽  
Variable Speed ◽  
Time Data ◽  
Speed Limits ◽  
Variable Speed Limits ◽  
Traffic Management System ◽  
Virginia Department

In September 2015, the Virginia Department of Transportation instituted an active traffic management system on I-66 in Northern Virginia. I-66 is a major commuter route into Washington, D.C., that experiences significant recurring and nonrecurring congestion. The active traffic management system sought to manage existing capacity dynamically and more effectively with hard shoulder running, advisory variable speed limits, lane use control signs, and queue warning systems. An initial before-and-after analysis of the system’s operational effectiveness was performed with probe-based travel time data from the provider, INRIX, and used records from the active traffic management’s traffic operations center. On weekdays, statistically significant improvements were often observed during off-peak periods, but conditions did not improve during peak periods. Weekends showed the greatest improvements, with travel times and travel time reliability measures improving by 10% to 14%. Segment-level analysis revealed that most of the benefits were attained because of the use of hard shoulder running outside of the peak periods, which created additional capacity on I-66. Benefits due to advisory variable speed limits were inconclusive because of limited data.

scholarly journals Travel Time Reliability for Urban Networks: Modelling and Empirics

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Fangfang Zheng ◽  
Xiaobo Liu ◽  
Henk van Zuylen ◽  
Jie Li ◽  
Chao Lu
Keyword(s):  
Standard Deviation ◽  
Travel Time ◽  
Network Traffic ◽  
Traffic Management ◽  
Weighted Average ◽  
Network Density ◽  
Travel Time Reliability ◽  
Time Rate ◽  
Traffic Characteristics ◽  
Average Travel Time

The importance of travel time reliability in traffic management, control, and network design has received a lot of attention in the past decade. In this paper, a network travel time distribution model based on the Johnson curve system is proposed. The model is applied to field travel time data collected by Automated Number Plate Recognition (ANPR) cameras. We further investigate the network-level travel time reliability by connecting the network reliability measures such as the weighted standard deviation of travel time rate and the weighted skewness of travel time rate distributions with network traffic characteristics (e.g., the network density). The weighting is done with respect to the number of signalized intersections on a trip. A clear linear relation between the weighted average travel time rate and the weighted standard deviation of travel time rate can be observed for different time periods with time-varying demand. Furthermore, both the weighted average travel time rate and the weighted standard deviation of travel time rate increase monotonically with network density. The empirical findings of the relation between network travel time reliability and network traffic characteristics can be possibly applied to assess traffic management and control measures to improve network travel time reliability.

Evaluating the Impact of Real-Time Mobility and Travel Time Reliability Information on Truck Drivers’ Routing Decisions

2018 ◽  
Vol 2672 (9) ◽  
pp. 164-172 ◽  
Author(s):  
Xiaoqiang Kong ◽  
William L. Eisele ◽  
Yunlong Zhang ◽  
Daren B. H. Cline
Keyword(s):  
Decision Making ◽  
Travel Time ◽  
Real Time ◽  
Traffic Management ◽  
Truck Drivers ◽  
Decision Making Process ◽  
Travel Time Reliability ◽  
Travel Time Prediction ◽  
Binary Logistic Regression Model ◽  
The Impact

This study represents the first research to investigate the impacts of two critical determinants—level of congestion and travel time reliability—on routing decisions with two groups of truck drivers having different levels of awareness of the real-time and the historical traffic conditions on available routes. The research analyzed 14,538 global positioning system devices recording trips on the I-495 crossing through Maryland, Virginia, and Washington, DC, and 2,166 trips in the Dallas area, to explore how truck drivers make routing decisions based on real-time travel time and reliability information by applying a binary logistic regression model. Researchers found that for truck drivers who are not familiar with the historical traffic and travel time conditions on available routes, real-time congestion information is a significant factor in their routing decision-making process, while travel time reliability is not a major consideration. For frequent truck drivers who are familiar with the historical traffic and travel time conditions on available routes, travel time reliability is a significant factor in their routing decision-making process, and traffic congestion information is not a significant factor. These results bring more accuracy to travel time prediction and provide valuable insights into traffic management and reliability performance measures. Moreover, this research provides statistical evidence proving the potential value of delivering travel time reliability information to drivers, traffic management agencies, and navigation map developers.

Development of Decision Support System for Integrated Active Traffic Management Systems Considering Travel Time Reliability

2020 ◽  
Vol 2674 (2) ◽  
pp. 167-180 ◽  
Author(s):  
Whoibin Chung ◽  
Mohamed Abdel-Aty ◽  
Ho-Chul Park ◽  
Qing Cai ◽  
Mdhasibur Rahman ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Travel Time ◽  
Support System ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Management Strategies ◽  
Travel Time Reliability ◽  
Traffic Condition ◽  
Traffic Conditions

A new decision support system (DSS) using travel time reliability was developed for integrated active traffic management (IATM) including freeways and arterials. The DSS consists of recommendation and evaluation of response plans. The DSS also includes three representative traffic management strategies: variable speed limits, queue warning, and ramp metering. The recommendation of response plans for recurring traffic congestion was generated from the logics of the three strategies. The evaluation of response plans was conducted by travel time reliability through the prediction of traffic conditions with response plans. The near-future prediction of traffic conditions with control strategies was conducted through METANET for freeways and arterials. The developed DSS was evaluated under three types of traffic congestion: extreme, heavy, and moderate. According to the evaluation results, the developed DSS recommended an IATM strategy with the highest synergistic relationships in real time and contributed to enhancing the effectiveness of the IATM strategies. It was confirmed that arterials should have the allowable residual capacity for the improvement of traffic flow of the entire corridor network. Furthermore, the DSS demonstrated a more balanced traffic condition between freeways and arterials.

Solution of inverse coefficient problem for fractional anomalous diffusion equation

2012 ◽  
Vol 9 (2) ◽  
pp. 65-70
Author(s):  
E.V. Karachurina ◽  
S.Yu. Lukashchuk
Keyword(s):  
Anomalous Diffusion ◽  
Fractional Derivatives ◽  
Descent Method ◽  
Extremum Problem ◽  
Steepest Descent Method ◽  
Coefficient Problem ◽  
Caputo Fractional Derivatives ◽  
Inverse Coefficient Problem ◽  
Residual Functional ◽  
Inverse Coefficient

An inverse coefficient problem is considered for time-fractional anomalous diffusion equations with the Riemann-Liouville and Caputo fractional derivatives. A numerical algorithm is proposed for identification of anomalous diffusivity which is considered as a function of concentration. The algorithm is based on transformation of inverse coefficient problem to extremum problem for the residual functional. The steepest descent method is used for numerical solving of this extremum problem. Necessary expressions for calculating gradient of residual functional are presented. The efficiency of the proposed algorithm is illustrated by several test examples.

scholarly journals Improved Immune Algorithm Combined with Steepest Descent Method for Optimal Design of IPMSM for FCEV Traction Motor

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3904
Author(s):  
Ji-Chang Son ◽  
Myung-Ki Baek ◽  
Sang-Hun Park ◽  
Dong-Kuk Lim
Keyword(s):  
Optimal Design ◽  
Permanent Magnet Synchronous Motor ◽  
Torque Ripple ◽  
Descent Method ◽  
Immune Algorithm ◽  
Electric Machines ◽  
Steepest Descent Method ◽  
Superior Performance ◽  
Element Analysis ◽  
Traction Motor

In this paper, an improved immune algorithm (IIA) was proposed for the torque ripple reduction optimal design of an interior permanent magnet synchronous motor (IPMSM) for a fuel cell electric vehicle (FCEV) traction motor. When designing electric machines, both global and local solutions of optimal designs are required as design result should be compared in various aspects, including torque, torque ripple, and cogging torque. To lessen the computational burden of optimization using finite element analysis, the IIA proposes a method to efficiently adjust the generation of additional samples. The superior performance of the IIA was verified through the comparison of optimization results with conventional optimization methods in three mathematical test functions. The optimal design of an IPMSM using the IIA was conducted to verify the applicability in the design of practical electric machines.

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