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.

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.

A Kalman Filter-Based Queue Length Estimation Method with Low-Penetration Mobile Sensor Data at Signalized Intersections

2018 ◽  
Vol 2672 (45) ◽  
pp. 253-264 ◽  
Author(s):  
Juyuan Yin ◽  
Jian Sun ◽  
Keshuang Tang
Keyword(s):  
Kalman Filter ◽  
Queue Length ◽  
Estimation Method ◽  
Mobile Internet ◽  
Internet Technology ◽  
Sensor Data ◽  
Linear Regression Method ◽  
Mobile Sensor ◽  
Length Estimation ◽  
Queue Lengths

Queue length estimation is of great importance for signal performance measures and signal optimization. With the development of connected vehicle technology and mobile internet technology, using mobile sensor data instead of fixed detector data to estimate queue length has become a significant research topic. This study proposes a queue length estimation method using low-penetration mobile sensor data as the only input. The proposed method is based on the combination of Kalman Filtering and shockwave theory. The critical points are identified from raw spatiotemporal points and allocated to different cycles for subsequent estimation. To apply the Kalman Filter, a state-space model with two state variables and the system noise determined by queue-forming acceleration is established, which can characterize the stochastic property of queue forming. The Kalman Filter with joining points as measurement input recursively estimates real-time queue lengths; on the other hand, queue-discharging waves are estimated with a line fitted to leaving points. By calculating the crossing point of the queue-forming wave and the queue-discharging wave of a cycle, the maximum queue length is also estimated. A case study with DiDi mobile sensor data and ground truth maximum queue lengths at Huanggang-Fuzhong intersection, Shenzhen, China, shows that the mean absolute percentage error is only 11.2%. Moreover, the sensitivity analysis shows that the proposed estimation method achieves much better performance than the classical linear regression method, especially in extremely low penetration rates.

scholarly journals Methods for estimating vehicle queues at a marine terminal: A computational comparison

2014 ◽  
Vol 24 (3) ◽  
pp. 611-619 ◽  
Author(s):  
Gang Chen ◽  
Zhong-Zhen Yang
Keyword(s):  
Queue Length ◽  
Simulation Software ◽  
Urban Traffic ◽  
Estimation Accuracy ◽  
Estimation Model ◽  
Advantages And Disadvantages ◽  
Natural Logarithm ◽  
Length Estimation ◽  
Proposed Model ◽  
Simulation Based

Abstract A long queue of vehicles at the gate of a marine terminal is a common traffic phenomenon in a port-city, which sometimes causes problems in urban traffic. In order to be able to solve this issue, we firstly need accurate models to estimate such a vehicle queue length. In this paper, we compare the existing methods in a case study, and evaluate their advantages and disadvantages. Particularly, we develop a simulation-based regression model, using the micro traffic simulation software PARAMIC. In simulation, it is found that the queue transient process follows a natural logarithm curve. Then, based on these curves, we develop a queue length estimation model. In the numerical experiment, the proposed model exhibits better estimation accuracy than the other existing methods

Modeling the Impacts of Traffic Flow Arrival Profiles on Ramp Metering Queues

2018 ◽  
Vol 2672 (15) ◽  
pp. 85-92 ◽  
Author(s):  
Guangchuan Yang ◽  
Rui Yue ◽  
Zong Tian ◽  
Hao Xu
Keyword(s):  
Traffic Flow ◽  
Queue Length ◽  
Ramp Metering ◽  
Signalized Intersection ◽  
Signal Timing ◽  
Microscopic Simulation ◽  
Length Estimation ◽  
Platoon Dispersion ◽  
Queue Lengths ◽  
Potential Impact

An adequate queue storage length is critical for a metered on-ramp to prevent ramp queue spillback to the upstream signalized intersection. Previous research on queue length estimation or queue storage length design at metered ramps has not taken into account the potential impact of various on-ramp traffic flow arrival profiles on ramp queue lengths. This paper depicts the traffic flow arrival profiles and queue generation processes at three different metered ramp categories. Based on a large number of microscopic simulation runs, it is found that, under a given demand-to-capacity scenario, the queue at a metered ramp with two on-ramp feeding movements is more likely to be cleared in a cycle than at a metered ramp with three on-ramp feeding movements. Also, the platoon dispersion effect significantly reduces the ramp queue length, and hence the queue storage needs at a metered ramp. In addition, this paper reveals that ramp queue length tends to increase linearly with upstream signal cycle length. The design of queue storage length for a metered on-ramp hence needs to fully consider the various ramp configurations and upstream signal timing settings.

scholarly journals Interdisciplinary Evaluation of Intersection Performances—A Microsimulation-Based MCDA

2021 ◽  
Vol 13 (4) ◽  
pp. 1859
Author(s):  
Kadir Diler Alemdar ◽  
Ahmet Tortum ◽  
Ömer Kaya ◽  
Ahmet Atalay
Keyword(s):  
Traffic Engineering ◽  
Traffic Management ◽  
Evaluation Criteria ◽  
Urban Traffic ◽  
Suitable Alternative ◽  
Order Preference ◽  
Energy Environment ◽  
Vehicle Delay ◽  
Hierarchy Process ◽  
Co Emission

Intersections are the most important regions in terms of urban traffic management. The intersection areas on the corridor should be analyzed together for consistency in traffic engineering. To do so, three intersections on the Vatan Street corridor in İstanbul, the most crowded city of Turkey, were examined. Various geometric and signal designs were performed for intersections and the most suitable corridor design was analyzed. The corridor designs were modeled with the PTV VISSIM microsimulation software. The most suitable corridor design was evaluated by using the results obtained from the microsimulation via analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) from multi criteria decision analysis (MCDA) methods. The evaluation criteria in the study are vehicle delay, queue length, stopped delay, stops, travel time, vehicle safety, CO emission, fuel consumption, and construction cost. As a result, the current and the most suitable alternative corridors were compared according to the comparison parameters and up to 80% improvements were observed. Thus, some advantages were obtained in terms of energy, environment, time, and cost.

scholarly journals Queue Length Forecasting in Complex Manufacturing Job Shops

Forecasting ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 322-338
Author(s):  
Marvin Carl May ◽  
Alexander Albers ◽  
Marc David Fischer ◽  
Florian Mayerhofer ◽  
Louis Schäfer ◽  
...  
Keyword(s):  
Operations Management ◽  
Queue Length ◽  
Manufacturing Systems ◽  
Production Control ◽  
Data Sets ◽  
Job Shops ◽  
Static Data ◽  
Queue Lengths ◽  
Operational Excellence

Currently, manufacturing is characterized by increasing complexity both on the technical and organizational levels. Thus, more complex and intelligent production control methods are developed in order to remain competitive and achieve operational excellence. Operations management described early on the influence among target metrics, such as queuing times, queue length, and production speed. However, accurate predictions of queue lengths have long been overlooked as a means to better understanding manufacturing systems. In order to provide queue length forecasts, this paper introduced a methodology to identify queue lengths in retrospect based on transitional data, as well as a comparison of easy-to-deploy machine learning-based queue forecasting models. Forecasting, based on static data sets, as well as time series models can be shown to be successfully applied in an exemplary semiconductor case study. The main findings concluded that accurate queue length prediction, even with minimal available data, is feasible by applying a variety of techniques, which can enable further research and predictions.

scholarly journals Quantitative Analysis of Queue Length of Falah Roundabout (UAE, Sharjah)

2018 ◽  
Vol 3 (4) ◽  
pp. 6
Author(s):  
Emran Al Otaibi ◽  
Mohammed Refaei ◽  
Nadia Nassif ◽  
Anas Naqawa
Keyword(s):  
Queue Length ◽  
Factors Affecting ◽  
True Value ◽  
Data Regression ◽  
Field Data Collection ◽  
Term Paper ◽  
The Will ◽  
Queue Lengths ◽  
Rule Method ◽  
A Minor

Roundabouts have faced a huge development in terms of designing and operation, the reason behind that is to get the most safe and functional design. The functionality is affected by different factors e.g. line width, diameter of the roundabout etc., when the capacity of the roundabout is fully utilized, queue length starts to form in the different approaches, which indicates of a minor or major issue that should be studied. This paper discusses the different factors affecting the queue length of an approach on the roundabout (Al Falah roundabout), after obtaining the data, regression analysis was done to provide a model that can be used for estimating the volume capacity ratio from queue lengths or vice versa. Two other methods were used to compare the obtained model (HCM 2010 Method and Two Minute Rule Method), in addition to a field data collection of the actual timing needed to pass that queue length, which was assigned as the true value of the models and comparing depending on it. Finally, the discussion of the term paper, will include the different concepts of advanced statistical analysis, the will (as expected) contain different types of distributions and the coloration between the keys of the roundabouts design, and will study the limitation and how it can be improved in future.

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