scholarly journals Multispectral Fusion Approach for Traffic Target Detection in Bad Weather

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 271
Author(s):  
Yajing Han ◽  
Dean Hu
Keyword(s):  
Traffic Control ◽  
Intelligent Transportation Systems ◽  
Cost Effective ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Surveillance Systems ◽  
Traffic Surveillance ◽  
Thermal Images ◽  
The Road ◽  
Bad Weather

Visual traffic surveillance using computer vision techniques can be noninvasive, automated and cost effective. Traffic surveillance systems with the ability to detect, count and classify vehicles can be employed in gathering traffic statistics and achieving better traffic control in intelligent transportation systems. This works well in daylight when the road users are clearly visible to the camera, but it often struggles when the visibility of the scene is impaired by insufficient lighting or bad weather conditions such as rain, snow, haze and fog. Therefore, in this paper, we design a dual input faster region-based convolutional neural network (RCNN) to make full use of the complementary advantages of color and thermal images to detect traffic objects in bad weather. Different from the previous detector, we used halfway fusion to fuse color and thermal images for traffic object detection. Besides, we adopt the polling from multiple layers method to adapt the characteristics of large size differences between objects of traffic targets to accurately identify targets of different sizes. The experimental results show that the present method improves the target recognition accuracy by 7.15% under normal weather conditions and 14.2% under bad weather conditions. This exhibits promising potential for implementation with real-world applications.

scholarly journals Vehicle Tracking and Counting System in Dusty Weather with Vibrating Camera Conditions

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Nastaran Yaghoobi Ershadi ◽  
José Manuel Menéndez
Keyword(s):  
Traffic Control ◽  
Gaussian Model ◽  
Weather Conditions ◽  
Surveillance Systems ◽  
Traffic Surveillance ◽  
Traffic Conditions ◽  
Detection And Tracking ◽  
Traffic Volumes ◽  
Medium Level ◽  
Bad Weather

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles are a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.) or dusty weather in arid and semiarid regions or at night, among others. In this paper, we proposed a method to track and count vehicles in dusty weather with a vibrating camera. For this purpose, we used a background subtraction based strategy mixed with extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result. Our proposed method was tested on several video surveillance records in different conditions such as in dusty or foggy weather, with a vibrating camera, and on roads with medium-level traffic volumes. The results showed that the proposed method performed better than other previously published methods, including the Kalman filter or Gaussian model, in different traffic conditions.

scholarly journals A Novel Algorithm Based on the Pixel-Entropy for Automatic Detection of Number of Lanes, Lane Centers, and Lane Division Lines Formation

Entropy ◽  
2018 ◽  
Vol 20 (10) ◽  
pp. 725 ◽  
Author(s):  
Fernando Hermosillo-Reynoso ◽  
Deni Torres-Roman ◽  
Jayro Santiago-Paz ◽  
Julio Ramirez-Pacheco
Keyword(s):  
Traffic Flow ◽  
Intelligent Transportation Systems ◽  
Moving Objects ◽  
Color Space ◽  
Automatic Detection ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Lane Detection ◽  
Computational Time ◽  
The Road

Lane detection for traffic surveillance in intelligent transportation systems is a challenge for vision-based systems. In this paper, a novel pixel-entropy based algorithm for the automatic detection of the number of lanes and their centers, as well as the formation of their division lines is proposed. Using as input a video from a static camera, each pixel behavior in the gray color space is modeled by a time series; then, for a time period τ , its histogram followed by its entropy are calculated. Three different types of theoretical pixel-entropy behaviors can be distinguished: (1) the pixel-entropy at the lane center shows a high value; (2) the pixel-entropy at the lane division line shows a low value; and (3) a pixel not belonging to the road has an entropy value close to zero. From the road video, several small rectangle areas are captured, each with only a few full rows of pixels. For each pixel of these areas, the entropy is calculated, then for each area or row an entropy curve is produced, which, when smoothed, has as many local maxima as lanes and one more local minima than lane division lines. For the purpose of testing, several real traffic scenarios under different weather conditions with other moving objects were used. However, these background objects, which are out of road, were filtered out. Our algorithm, compared to others based on trajectories of vehicles, shows the following advantages: (1) the lowest computational time for lane detection (only 32 s with a traffic flow of one vehicle/s per-lane); and (2) better results under high traffic flow with congestion and vehicle occlusion. Instead of detecting road markings, it forms lane-dividing lines. Here, the entropies of Shannon and Tsallis were used, but the entropy of Tsallis for a selected q of a finite set achieved the best results.

scholarly journals Type of communication between driver and car, based on the augmented reality: "new trend" in building intelligent transportation systems

2017 ◽  
Vol 6 (1) ◽  
pp. 6-14 ◽  
Author(s):  
S.B. Efremov
Keyword(s):  
Augmented Reality ◽  
Transport System ◽  
Intelligent Transportation Systems ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Driving Safety ◽  
The Road ◽  
Advantages And Disadvantages ◽  
Road Signs ◽  
On The Road

In order to increase safety while driving and to minimize the burden on the driver, the information should be transmitted to him/her in such a way that the driver needn’t spent time on its recognition and comprehension. Projecting and visualization of information on the windshield can help simplify the dialogue between a car and a driver ("operator") and expand the influence of intellectual transport system using projection information about traffic jams in the field of perception of the driver, so that it does not interfere with the driver on the road. This article discusses the possible advantages and disadvantages of using "hints", created within the framework of the "augmented reality" to increase driving safety by treating them as a new form of communication between a car and a driver. So, it seems to be a new approach to the utilization of the system, based on performances in the field of augmented reality to recognize road signs, which impose virtual objects on the field of perception in all types of traffic situations including the uncomfortable weather conditions. This approach can be used to increase accuracy of intellectual transport system with the augmented reality to support the driver in various driving situations, increasing comfort and reducing the number of accidents

scholarly journals ANALYSIS OF DIFFERENT VISUAL STRATEGIES OF ‘ISOLATED VEHICLE’ AND ‘DISTURBED VEHICLE’

Transport ◽  
2018 ◽  
Vol 33 (3) ◽  
pp. 853-860
Author(s):  
Nicola BONGIORNO ◽  
Gaetano BOSURGI ◽  
Orazio PELLEGRINO ◽  
Giuseppe SOLLAZZO
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Disturbed Condition ◽  
The Road ◽  
Driving Behaviour ◽  
Visual Behaviour ◽  
Road Geometry ◽  
Potential Applications ◽  
Road Characteristics

This paper analyses the driver’ visual behaviour in the different conditions of ‘isolated vehicle’ and ‘disturbed vehicle’. If the meaning of the former is clear, the latter condition considers the influence on the driving behaviour of various objects that could be encountered along the road. These can be classified in static (signage, stationary vehicles at the roadside, etc.) and dynamic objects (cars, motorcycles, bicycles). The aim of this paper is to propose a proper analysis regarding the driver’s visual behaviour. In particular, the authors examined the quality of the visually informa-tion acquired from the entire road environment, useful for detecting any critical safety condition. In order to guaran-tee a deep examination of the various possible behaviours, the authors combined the several test outcomes with other variables related to the road geometry and with the dynamic variables involved while driving. The results of this study are very interesting. As expected, they obviously confirmed better performances for the ‘isolated vehicle’ in a rural two-lane road with different traffic flows. Moreover, analysing the various scenarios in the disturbed condition, the proposed indices allow the authors to quantitatively describe the different influence on the visual field and effects on the visual behaviour, favouring critical analysis of the road characteristics. Potential applications of these results may contribute to improve the choice of the best maintenance strategies for a road, to select the optimal signage location, to define forecasting models for the driving behaviour and to develop useful instruments for intelligent transportation systems.

scholarly journals An Advanced Deep Learning Approach for Multi-Object Counting in Urban Vehicular Environments

2021 ◽  
Vol 13 (12) ◽  
pp. 306
Author(s):  
Ahmed Dirir ◽  
Henry Ignatious ◽  
Hesham Elsayed ◽  
Manzoor Khan ◽  
Mohammed Adib ◽  
...  
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Weather Conditions ◽  
Research Area ◽  
Transportation Systems ◽  
Detection Accuracy ◽  
Adverse Weather ◽  
Object Counting ◽  
The Impact

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have been proposed in the literature to address this problem. However, the resulting detection accuracy is still not adequate. This paper proposes an efficient approach that uses deep learning concepts and correlation filters for multi-object counting and tracking. The performance of the proposed system is evaluated using a dataset consisting of 16 videos with different features to examine the impact of object density, image quality, angle of view, and speed of motion towards system accuracy. Performance evaluation exhibits promising results in normal traffic scenarios and adverse weather conditions. Moreover, the proposed approach outperforms the performance of two recent approaches from the literature.

Potential Using Vehicle to Vehicle Communication Based on Wireless Fidelity (Wi-Fi) for Supporting Intelligent Transportation Systems (ITS)

2021 ◽  
pp. 61-76
Author(s):  
إسراء عصام بن موسى ◽  
عبدالسلام صالح الراشدي
Keyword(s):  
Intelligent Transportation Systems ◽  
Ad Hoc ◽  
Real Life ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
The Road ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Vehicle To Vehicle Communication ◽  
Wireless Fidelity

Vehicular Ad-hoc Network (VANET) becomes one of the most popular modern technologies these days, due to its contribution to the development and modernization of Intelligent Transportation Systems (ITS). The primary goal of these networks is to provide safety and comfort for drivers and passengers in roads. There are many types of VANET that are used in ITS, in this paper, we particularly focus on the Vehicle to Vehicle communication (V2V), which each vehicle can exchange information to inform drivers of other vehicles about the current state of the road flow, in the event of any emergency to avoid accidents, and reduce congestion on roads. We proposed V2V using Wi-Fi (wireless fidelity); the reason of its unique characteristics that distinguish it from other types. There are many difficulties and the challenges in implementing most types of V2V, and the reason is due to the lack of devices and equipment needed for real implementation. To prove the possibility of applying this type in real life, we made a prototype contains a modified toy car, a 12-volt power supply, sensors, visual, audible alarm, a visual “LED” devices, and finally a 12-volt DC relay unit. As a conclusion, the proposed implementation in spite of minimal requirements and use simple equipment, we have achieved the most important main objectives of the paper: preventing vehicles from collision, early warning, and avoiding congestion on the roads.

A Survey of Approaches for Estimating Meteorological Visibility Distance Under Foggy Weather Conditions

2020 ◽  
pp. 65-92 ◽  
Author(s):  
Faouzi Kamoun ◽  
Hazar Chaabani ◽  
Fatma Outay ◽  
Ansar-Ul-Haque Yasar
Keyword(s):  
Intelligent Transportation Systems ◽  
Situational Awareness ◽  
Wide Spectrum ◽  
Distance Estimation ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Driver Assistance Systems ◽  
Research Issues ◽  
Visibility Distance ◽  
Assistance Systems

The immaturity of fog abatement technologies for highway usage has led to growing interest towards developing intelligent transportation systems that are capable of estimating meteorological visibility distance under foggy weather conditions. This capability is crucial to support next-generation cooperative situational awareness and collision avoidance systems as well as onboard driver assistance systems. This chapter presents a survey and a comprehensive taxonomy of daytime visibility distance estimation approaches based on a review and synthesis of the literature. The proposed taxonomy is both comprehensive (i.e., captures a wide spectrum of earlier contributions) and effective (i.e., enables easy comparison among previously proposed approaches). The authors also highlight some open research issues that warrant further investigation.

scholarly journals Analysis of Space-Time Variation of Passenger Flow and Commuting Characteristics of Residents Using Smart Card Data of Nanjing Metro

2019 ◽  
Vol 11 (18) ◽  
pp. 4989 ◽  
Author(s):  
Wei Yu ◽  
Hua Bai ◽  
Jun Chen ◽  
Xingchen Yan
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Management ◽  
Rapid Development ◽  
Weather Conditions ◽  
Transportation Systems ◽  
Space Time ◽  
Smart Cards ◽  
The Sustainable Development ◽  
Passenger Flow ◽  
Challenges And Opportunities

The rapid development of cities has brought new challenges and opportunities to traditional traffic management. The usage of smart cards promotes the upgrading of intelligent transportation systems, and also produces considerable big data. As an important part of the urban comprehensive transportation system, Nanjing metro has more than 1 million inbound and outbound records of traffic smart cards used by residents every day. How to process these traffic data and present them visually is an urgent problem in modern traffic management. In this study, five working days with normal weather conditions in Nanjing were selected, and the swiping records of the smart cards were extracted, and the space–time characteristics were analyzed. In terms of time analysis, this research analyzed the 24-h fluctuation of daily average passenger flow, peak hour coefficient of passenger flow, 24-h fluctuation of passenger flow on different metro lines, passenger flow intensity on different metro lines and passenger flow comparison at different stations. In spatial analysis, this study uses thermodynamic charts to represent the inflow and outflow of passengers at different stations during early and evening peak periods. The analysis results and visualized images directly reflect the area where Nanjing metro congestion is located, and also shows the commuting characteristics of residents. It can solve the problem of urban congestion, carry out the rational layout of urban functional areas, and promote the sustainable development of people and cities.

Improving Unpaved Roads in Virginia: Case Study

2003 ◽  
Vol 1819 (1) ◽  
pp. 149-154
Author(s):  
Michael W. Dunn ◽  
S. Noelle On
Keyword(s):  
Cost Effective ◽  
Weather Conditions ◽  
Small Scale ◽  
Elected Officials ◽  
Unpaved Roads ◽  
The Road ◽  
Improvement Process ◽  
Key Factor ◽  
Low Volume ◽  
Virginia Department

Minimizing costs and streamlining the construction of low-volume roads offers an opportunity for transportation agencies to effectively meet the needs of rural citizens. The Virginia Department of Transportation (VDOT) maintains approximately 56,941 mi of the state’s roads, including Interstate, primary, and secondary facilities. Between 1987 and 1994, VDOT paved nearly 1,900 mi of unpaved roads. In rural parts of the state, many miles of state-maintained roads still have gravel and dirt surfaces. Each year the local transportation residency offices, in conjunction with local elected officials, contractors, and area citizens, strive to improve and pave as many miles of gravel and dirt roads as possible. The Hillsville Residency of VDOT, located in rural Carroll and Floyd Counties, has developed an efficient and cost-effective method for improving low-volume gravel and dirt roads. This process relies heavily on cooperative efforts by VDOT, contractors, elected officials, and especially citizens. Land donations from citizens represent the cornerstone of this process, signifying that citizen cooperation is the key factor in a project’s success. Because most of the decisions in the improvement process are at the local residency level, trusting relationships and frequent communication can be established, small-scale and local contractors are given more business opportunities, and local VDOT personnel can better understand citizen concerns and perform road improvements accordingly. In addition, the time line for the road improvement process is based on seasons—the most appropriate weather conditions are considered for the work being performed. This program enables more roads to be paved each year, improving the level of service and quality of life for local citizens.

Developing a Market-Sensitive Intelligent Transportation Systems Educational Program

1997 ◽  
Vol 1588 (1) ◽  
pp. 120-129 ◽  
Author(s):  
Maria P. Boilé ◽  
Lazar N. Spasovic ◽  
Louis J. Pignataro
Keyword(s):  
Intelligent Transportation Systems ◽  
Educational Program ◽  
Civil Engineering ◽  
Intelligent Transportation ◽  
Educational Needs ◽  
Transportation Systems ◽  
Academic Programs ◽  
Surveillance Systems ◽  
Institute Of Technology ◽  
Public And Private Sector

Results of research undertaken to evaluate the educational needs of the emerging field of Intelligent Transportation Systems (ITSs) are presented, and whether course offerings in academic programs meet these needs is ascertained. A survey was conducted to determine needs for ITS education among public- and private-sector entities and to assess the perception of the academic sector on the type and level of ITS education to be offered. The results indicate that academic programs are aware of the educational needs of the private and public sectors in ITS and have been reacting to those needs. A traditional civil engineering curriculum is inadequate to educate engineers in ITS, thus the ITS educational program must be inter-(or cross-) disciplinary. Focus should be on the areas that are not traditionally part of civil engineering education such as communications, traffic surveillance, systems analysis, and social and institutional issues. The results are intended primarily to provide a guideline for universities to develop the content of an ITS program by identifying the type of program structure as well as the topics to be covered in the courses. A case study is presented of how such a program was implemented at the graduate level at the New Jersey Institute of Technology.

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