Real-Time Estimation of Saturation flow Rates for Dynamic Traffic Signal Control using Connected-Vehicle Data

This paper proposes a connected vehicle-based traffic signal control scheme that seeks to improve both vehicle and pedestrian operations. Real-time information on vehicle speeds and locations is combined with knowledge of pedestrian arrivals to optimize signal timings that minimize a weighted average of vehicle and pedestrian delays. Such real-time pedestrian information might be available using existing sensors—such as pedestrian push buttons or infrared detectors—as well as in a connected environment. The algorithm implements a rolling-horizon optimization framework that optimizes signal phase sequences over some period but only implements the first phase in the optimized sequence. The results reveal that considering pedestrians in the optimization can improve delays to both pedestrians and vehicles compared with ignoring pedestrians. Within the proposed framework, average vehicle delay increases and average pedestrian delay decreases as more weight is assigned to pedestrian delay in the optimization. In general, the average person delay can be minimized when the relative weight between vehicle and pedestrian delay is consistent with the average occupancy rate of cars. However, a different weight may be chosen to prioritize pedestrian movement, if desired. These results are robust under varying demand levels and demand patterns. The effectiveness of the algorithm decreases as the information level of pedestrian arrivals decreases, and the algorithm becomes ineffective when information from fewer than 60% pedestrians is available. However, the detection of more than 60% of pedestrians can likely be achieved using existing technologies and thus would likely be available in a connected environment.

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A machine for real-time estimation of the tribological characteristics of materials

Industrial laboratory Diagnostics of materials ◽

10.26896/1028-6861-2020-86-4-61-65 ◽

2020 ◽

Vol 86 (4) ◽

pp. 61-65

Author(s):

M. V. Abramchuk ◽

R. V. Pechenko ◽

K. A. Nuzhdin ◽

V. M. Musalimov

Keyword(s):

Real Time ◽

Time Estimation ◽

Tribological Characteristics ◽

Continuous Processing ◽

Friction Machine ◽

Dynamic Friction Coefficient ◽

Displacement Sensors ◽

Frictional Interaction ◽

Real Time Estimation ◽

Automated Quality Control

A reciprocating friction machine Tribal-T intended for automated quality control of the rubbing surfaces of tribopairs is described. The distinctive feature of the machine consists in implementation of the forced relative motion due to the frictional interaction of the rubbing surfaces fixed on the drive and conjugate platforms. Continuous processing of the signals from displacement sensors is carried out under conditions of continuous recording of mutual displacements of loaded tribopairs using classical approaches of the theory of automatic control to identify the tribological characteristics. The machine provides consistent visual real time monitoring of the parameters. The MATLAB based computer technologies are actively used in data processing. The calculated tribological characteristics of materials, i.e., the dynamic friction coefficient, damping coefficient and measure of the surface roughness, are presented. The tests revealed that a Tribal-T reciprocating friction machine is effective for real-time study of the aforementioned tribological characteristics of materials and can be used for monitoring of the condition of tribo-nodes of machines and mechanisms.

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