scholarly journals A Credibility Score Algorithm for Malicious Data Detection in Urban Vehicular Networks

Information ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 496
Author(s):  
Bartłomiej Płaczek ◽  
Marcin Bernas ◽  
Marcin Cholewa
Keyword(s):  
Vehicular Networks ◽  
State Of The Art ◽  
Negative Impact ◽  
Green Light ◽  
Traffic Signals ◽  
Signalized Intersection ◽  
Traffic Signal Control ◽  
Data Detection ◽  
Simulation Experiments ◽  
Improved Accuracy

This paper introduces a method to detect malicious data in urban vehicular networks, where vehicles report their locations to road-side units controlling traffic signals at intersections. The malicious data can be injected by a selfish vehicle approaching a signalized intersection to get the green light immediately. Another source of malicious data are vehicles with malfunctioning sensors. Detection of the malicious data is conducted using a traffic model based on cellular automata, which determines intervals representing possible positions of vehicles. A credibility score algorithm is introduced to decide if positions reported by particular vehicles are reliable and should be taken into account for controlling traffic signals. Extensive simulation experiments were conducted to verify effectiveness of the proposed approach in realistic scenarios. The experimental results show that the proposed method detects the malicious data with higher accuracy than compared state-of-the-art methods. The improved accuracy of detecting malicious data has enabled mitigation of their negative impact on the performance of traffic signal control.

Concurrent Progression of Through and Turning Movements for Arterials Experiencing Heavy Turning Flows and Bay-Length Constraints

2019 ◽  
Vol 2673 (9) ◽  
pp. 525-537
Author(s):  
Yen-Hsiang Chen ◽  
Yao Cheng ◽  
Gang-Len Chang
Keyword(s):  
State Of The Art ◽  
Negative Impact ◽  
Arterial Segment ◽  
Simulation Experiments ◽  
Average Delay ◽  
Left Turn ◽  
Signal Coordination ◽  
Priority Task ◽  
Proposed Model ◽  
The Impact

Contending with congestion on major urban arterials by providing progression bands has long been a priority task for the traffic community. However, on an arterial experiencing heavy left-turn volumes at major intersections, the left-turn queue may spill back rapidly and further degrade the effectiveness of the through progression band if the left-turn volume and the limited bay length have not been accounted for in the optimization of signal coordination plan. Such negative impact from left-turn queues also justifies the need to take into account the concurrent progression of through and left-turn flows on major arterials. To address these two issues, this paper presents a three-staged signal optimization model that can circumvent or minimize the impact of left-turn spillback to the through movements and concurrently minimize the delay of left-turn flows. The proposed model firstly obtains an initial maximized bandwidth from an existing state-of-the-art method and then maximizes the portion of through bandwidth not impeded by the left-turn overflows. The delay of left-turn flows at each intersection will also be minimized under the obtained effective through bandwidth. The results from the numerical analyses have confirmed the benefits and need of including the left-turn volume and its bay length in the design of dual progression for through and left-turn movements. The simulation experiments further show a reduction in the average delay and the number of stops, by 6.4% and 5.5%, respectively, for vehicles traversing an arterial segment of six intersections, compared with the state-of-the-art model, MULTIBAND.

scholarly journals Efficient End-to-End Sentence-Level Lipreading with Temporal Convolutional Networks

2021 ◽  
Vol 11 (15) ◽  
pp. 6975
Author(s):  
Tao Zhang ◽  
Lun He ◽  
Xudong Li ◽  
Guoqing Feng
Keyword(s):  
Performance Improvement ◽  
State Of The Art ◽  
Error Rates ◽  
Convolutional Network ◽  
Convolutional Networks ◽  
Sentence Level ◽  
End To End ◽  
High Level ◽  
Improved Accuracy ◽  
Talking Face

Lipreading aims to recognize sentences being spoken by a talking face. In recent years, the lipreading method has achieved a high level of accuracy on large datasets and made breakthrough progress. However, lipreading is still far from being solved, and existing methods tend to have high error rates on the wild data and have the defects of disappearing training gradient and slow convergence. To overcome these problems, we proposed an efficient end-to-end sentence-level lipreading model, using an encoder based on a 3D convolutional network, ResNet50, Temporal Convolutional Network (TCN), and a CTC objective function as the decoder. More importantly, the proposed architecture incorporates TCN as a feature learner to decode feature. It can partly eliminate the defects of RNN (LSTM, GRU) gradient disappearance and insufficient performance, and this yields notable performance improvement as well as faster convergence. Experiments show that the training and convergence speed are 50% faster than the state-of-the-art method, and improved accuracy by 2.4% on the GRID dataset.

Smart Traffic Light System

2021 ◽  
Vol 9 (9) ◽  
pp. 679-686
Author(s):  
Rashi Maheshwari
Keyword(s):  
Traffic Congestion ◽  
Traffic Signals ◽  
Traffic Monitoring ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
Mathematical Functions ◽  
Light System ◽  
Smart Traffic ◽  
And Control

Abstract: Traffic signal control frameworks are generally used to monitor and control the progression of cars through the intersection of roads. Moreover, a portable controller device is designed to solve the issue of emergency vehicles stuck in overcrowded roads. The main objective of this paper is to design and implement a suitable algorithm and its simulation for an intelligent traffic signal simulator. The framework created can detect the presence or nonappearance of vehicles within a specific reach by setting appropriate duration for traffic signals to react accordingly. By employing mathematical functions and algorithms to ascertain the suitable timing for the green signal to illuminate, the framework can assist with tackling the issue of traffic congestion. The explanation relies on recent fixed programming time. Keywords: Smart Traffic Light System, Smart City, Traffic Monitoring.

scholarly journals Software-defined Architecture for Urban Regional Traffic Signal Control

2020 ◽  
Vol 32 (2) ◽  
pp. 229-236
Author(s):  
Songhang Chen ◽  
Dan Zhang ◽  
Fenghua Zhu
Keyword(s):  
Traffic Congestion ◽  
Traffic Signal ◽  
Urban Traffic ◽  
Signal Control ◽  
Traffic Signal Control ◽  
The Novel ◽  
Simulation Experiments ◽  
Microscopic Traffic Simulation ◽  
Control Devices ◽  
Innovation Platform

Regional Traffic Signal Control (RTSC) is believed to be a promising approach to alleviate urban traffic congestion. However, the current ecology of RTSC platforms is too closed to meet the needs of urban development, which has also seriously affected their own development. Therefore, the paper proposes virtualizing the traffic signal control devices to create software-defined RTSC systems, which can provide a better innovation platform for coordinated control of urban transportation. The novel architecture for RTSC is presented in detail, and microscopic traffic simulation experiments are designed and conducted to verify the feasibility.

scholarly journals Performance Analysis of V2V and V2I LiFi Communication Systems in Traffic Lights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Gerardo Hernandez-Oregon ◽  
Mario E. Rivero-Angeles ◽  
Juan C. Chimal-Eguía ◽  
Arturo Campos-Fentanes ◽  
Jorge G. Jimenez-Gallardo ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Low Cost ◽  
Red Light ◽  
Green Light ◽  
Mathematical Expression ◽  
Traffic Light ◽  
Safe Driving ◽  
Traffic Lights

Vehicular networks is a key technology for efficiently communicating both user’s devices and cars for timely information regarding safe driving conditions and entertaining applications like social media, video streaming, and gaming services, among others. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective alternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-data-rate, and efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in a road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with the front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light) is able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on and so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1 system in order to obtain the average queue length. Then, Little’s theorem is applied to calculate the average waiting delay when the red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived.

PHASE DYNAMICS OF COMPLEX-VALUED NEURAL NETWORKS AND ITS APPLICATION TO TRAFFIC SIGNAL CONTROL

2005 ◽  
Vol 15 (01n02) ◽  
pp. 111-120 ◽  
Author(s):  
IKUKO NISHIKAWA ◽  
TAKESHI IRITANI ◽  
KAZUTOSHI SAKAKIBARA ◽  
YASUAKI KUROE
Keyword(s):  
Phase Synchronization ◽  
Coupled System ◽  
Traffic Signals ◽  
Activation Function ◽  
Traffic Signal Control ◽  
Phase Oscillators ◽  
Hopfield Networks ◽  
Synchronization Mechanism ◽  
Phase Dynamics ◽  
Complex Valued

Complex-valued Hopfield networks which possess the energy function are analyzed. The dynamics of the network with certain forms of an activation function is decomposable into the dynamics of the amplitude and phase of each neuron. Then the phase dynamics is described as a coupled system of phase oscillators with a pair-wise sinusoidal interaction. Therefore its phase synchronization mechanism is useful for the area-wide offset control of the traffic signals. The computer simulations show the effectiveness under the various traffic conditions.

scholarly journals Modeling the Traffic Flow of the Urban Signalized Intersection with a Straddling Work Zone

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Liling Zhu ◽  
Bingmei Jia ◽  
Da Yang ◽  
Yuezhu Wu ◽  
Guo Yang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Traffic Control ◽  
Negative Impact ◽  
Work Zone ◽  
Signalized Intersection ◽  
Specific Work ◽  
Social Force ◽  
Irregular Boundary ◽  
Factors Affecting ◽  
Boundary Characteristics

Work zones widely exist on urban roads in many countries and have a significant negative impact on traffic. Few studies have focused on modeling the traffic flow of the work zone on the urban arterials, especially on the work zone at the intersections. In this paper, a microscopic model based on the social force theory for the traffic flow of the intersection with a specific work zone, called straddling work zone, is proposed. The model can capture the no lane division and irregular boundary characteristics of the traffic of the intersection with a straddling work zone and also can reflect the interaction of the intersection traffic flows from the two opposite directions. The proposed model is calibrated and validated using the real work zone data, and the results display that the MARE values are all less than 10%. The factors affecting the traffic flow in the straddling work zone are analyzed through simulation. Our study reveals that the distance from the lower edge of the work zone to the median divider of the road and the proportion of large vehicles in the work zone have the greatest impact on the signalized intersection, which provides a reference for the future traffic control at the intersection with the straddling work zone.

Hyperspectral complex-domain image denoising: cube complex-domain BM3D (CCDBM3D) algorithm

2020 ◽  
Vol 2020 (10) ◽  
pp. 179-1-179-7
Author(s):  
Vladimir Katkovnik ◽  
Mykola Ponomarenko ◽  
Karen Egiazarian ◽  
Igor Shevkunov ◽  
Peter Kocsis
Keyword(s):  
Image Denoising ◽  
High Efficiency ◽  
State Of The Art ◽  
Block Matching ◽  
Complex Domain ◽  
Simulation Experiments ◽  
Cube Complex ◽  
Spatial Dimensions ◽  
Phase Amplitude ◽  
Complex Valued

We consider hyperspectral phase/amplitude imaging from hyperspectral complex-valued noisy observations. Block-matching and grouping of similar patches are main instruments of the proposed algorithms. The search neighborhood for similar patches spans both the spectral and 2D spatial dimensions. SVD analysis of 3D grouped patches is used for design of adaptive nonlocal bases. Simulation experiments demonstrate high efficiency of developed state-of-the-art algorithms.

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