scholarly journals Real-time Queue Length Estimation Applying Shockwave Theory at Urban Signalized Intersections

2021 ◽  
Author(s):  
Márton Tamás Horváth ◽  
Tamás Tettamanti
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Queue Length ◽  
Traffic Management ◽  
Urban Traffic ◽  
Length Estimation ◽  
Queue Lengths ◽  
General Goal ◽  
Store And Forward ◽  
Urban Traffic Control

Signal control is a basic need for urban traffic control; however, it is a very rough intervention in the free flow of traffic, which often results in queues in front of signal heads. The general goal is to reduce the delays caused, and to plan efficient traffic management on the network. For this, the exact knowledge of queue lengths on links is one of crucial importance. This article presents a link-based methodology for real-time queue length estimation in urban signalized road networks. The model uses a Kalman Filter-based recursive method and estimates the length of the queue in every cycle. The input of the filter, i.e. the dynamics of queue length is described by the traffic shockwave theory and the store and forward model. The method requires one loop-detector per link placed at the appropriate position, for which the article also provides suggestions.

Measuring Vehicle Queue Length with Video

2011 ◽  
Vol 179-180 ◽  
pp. 109-114
Author(s):  
Zhong Qin ◽  
Guang Ting Su ◽  
Yi Chen ◽  
Qi Zhou Liu ◽  
Min Huang
Keyword(s):  
Traffic Control ◽  
Queue Length ◽  
Image Sequences ◽  
Urban Traffic ◽  
Experimental Results ◽  
Signal Control ◽  
Detection Algorithms ◽  
Intersection Signal Control ◽  
Urban Traffic Control ◽  
Stop Line

Queue length behind the stop line is an important parameter in the model of intersection signal control which is the base of urban traffic control. In this paper, the detection algorithms of queue length by the image information are proposed. At first, the background differential is used to extract the vehicle after the stop line, and then the three regional of the left, straight and right are identified, and finally at the different regions, tail of the vehicles queue is detected based on the change of image sequences gray, so the queue length is measured. The experimental results confirmed the effectiveness of the algorithm.

Traffic Management Parameters from Single Inductive Loop Detectors

2000 ◽  
Vol 1719 (1) ◽  
pp. 112-120 ◽  
Author(s):  
Tom Cherrett ◽  
Hugh Bell ◽  
Mike McDonald
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Fixed Time ◽  
Urban Traffic ◽  
Flow Conditions ◽  
Inductive Loop ◽  
Loop Detectors ◽  
Time Period ◽  
S Period ◽  
Urban Traffic Control

Investigated are potential new uses for the digital output produced by single inductive loop detectors (2 m x 1.5 m and 2 m x 6.5 m) used in most European urban traffic control systems. Over a fixed time period, the average loop-occupancy time per vehicle (ALOTPV) for a detector being sampled every 250 ms is determined by taking the number of 250-ms occupancies and dividing by the number of vehicles. In a similar way, the average headway time between vehicles (AHTBV) is determined by taking the number of 250-ms vacancies and dividing by the number of vehicles. Over a 30-s period, the minimum and maximum values of ALOTPV and AHTBV ranged from 1 to 120 (an ALOTPV of 1 and an AHTBV of 120 representing free-flow conditions, an ALOTPV of 120 and an AHTBV of 1 representing a stationary queue). Identifying periods when a link was operating under capacity and at capacity and when it had become saturated could be more clearly identified by using plots of ALOTPV and AHTBV data over time compared to the more traditional percentage occupancy output. ALOTPV also was used to successfully identify long vehicles from cars down to speeds of 15 km/h.

Upper Level for Real Time Urban Traffic Control Systems

1990 ◽  
Vol 23 (8) ◽  
pp. 473-476 ◽  
Author(s):  
A. Kessaci ◽  
J.L. Farges ◽  
J.J. Henry
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Traffic Control ◽  
Urban Traffic ◽  
Upper Level ◽  
Urban Traffic Control

Cycling and Urban Traffic Management and Control Systems

2000 ◽  
Vol 1705 (1) ◽  
pp. 77-84 ◽  
Author(s):  
Stephen D. Clark ◽  
Matthew W. Page
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Urban Traffic ◽  
The United Kingdom ◽  
Explicit Consideration ◽  
Additional Costs ◽  
And Performance ◽  
Urban Traffic Control ◽  
Motorized Vehicles ◽  
And Control

Since the 1950s, cycling has been a declining mode of travel in the United Kingdom. During this same period, sophisticated techniques for managing traffic in the urban environment have been developed. Given these circumstances, the presence of cyclists is often ignored by urban traffic control (UTC) systems, which are dominated by consideration of the flows and journey times of private motorized vehicles. Authorities are enthusiastic about the promotion of cycling as a mode of travel and are looking to see if this can be assisted by use of traffic management systems. The fact that cyclists and potential cyclists vary considerably in their abilities and performance, as well as in their attitudes to timesaving and safety, is highlighted. The context of the problem is set, the specific issue of detection of cycles is examined, the potential for implementation of priority measures in different types of UTC systems is discussed, and the issue is illustrated with some actual installations. Limited European evidence would suggest that only minimum effort is needed to take explicit account of cycling when a UTC system is being implemented. This supports the idea that cyclists can be given a higher degree of consideration within a UTC system without incurring significant additional costs. Only when cycling achieves a near-dominant proportion of the trips within a city and is growing in volume, as is the case in China, is explicit consideration to cyclists given.

scholarly journals Efficient Video-Based Vehicle Queue Length Estimation Using Computer Vision and Deep Learning for an Urban Traffic Scenario

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1786
Author(s):  
Muhammad Umair ◽  
Muhammad Umar Farooq ◽  
Rana Hammad Raza ◽  
Qian Chen ◽  
Baher Abdulhai
Keyword(s):  
Traffic Engineering ◽  
Queue Length ◽  
Urban Traffic ◽  
Fine Tuning ◽  
Low Resolution ◽  
Vehicle Class ◽  
Traffic Lane ◽  
Length Estimation ◽  
Traffic Scenario ◽  
Queue Lengths

In the traffic engineering realm, queue length estimation is considered one of the most critical challenges in the Intelligent Transportation System (ITS). Queue lengths are important for determining traffic capacity and quality, such that the risk for blockage in any traffic lane could be minimized. The Vision-based sensors show huge potentials compared to fixed or moving sensors as they offer flexibility for data acquisition due to large-scale deployment at a huge pace. Compared to others, these sensors offer low installation/maintenance costs and also help with other traffic surveillance related tasks. In this research, a CNN-based approach for estimation of vehicle queue length in an urban traffic scenario using low-resolution traffic videos is proposed. The system calculates queue length without the knowledge of any camera parameter or onsite calibration information. The estimation in terms of the number of cars is considered a priority as compared to queue length in the number of meters since the vehicular delay is the number of waiting cars times the wait time. Therefore, this research estimates queue length based on total vehicle count. However, length in meters is also provided by approximating average vehicle size as 5 m. The CNN-based approach helps with accurate tracking of vehicles’ positions and computing queue lengths without the need for installation of any roadside or in-vehicle sensors. Using a pre-trained 80-classes YOLOv4 model, an overall accuracy of 73% and 88% was achieved for vehicle-based and pixel-based queue length estimation. After further fine-tuning of model on the low-resolution traffic images and narrowing down the output classes to vehicle class only, an average accuracy of 83% and 93%, respectively, was achieved which shows the efficiency and robustness of the proposed approach.

ART-UTC: An adaptive real-time urban traffic control strategy

2017 ◽  
Author(s):  
Rob van Kooten ◽  
Pieter Imhof ◽  
Karst Brummelhuis ◽  
Maurits van Pampus ◽  
Anahita Jamshidnejad ◽  
...  
Keyword(s):  
Real Time ◽  
Control Strategy ◽  
Traffic Control ◽  
Urban Traffic ◽  
Urban Traffic Control

Operational Real-Time Urban Traffic Control System

1997 ◽  
Vol 30 (8) ◽  
pp. 603-607 ◽  
Author(s):  
F. Boillot ◽  
J.C. Pierrelée ◽  
F. Lenoir ◽  
S. Sellam
Keyword(s):  
Control System ◽  
Real Time ◽  
Traffic Control ◽  
Urban Traffic ◽  
Traffic Control System ◽  
Urban Traffic Control
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