scholarly journals Detecting anomalous road traffic conditions using VGG19 CNN Model

2021 ◽  
Vol 309 ◽  
pp. 01226
Author(s):  
M. Rajeshwari ◽  
CH. MallikarjunaRao
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Road Traffic ◽  
Dynamic Mode ◽  
Static Mode ◽  
Vehicle Accidents ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Street Traffic ◽  
Vehicle Movement

Detection on the real time road traffic has tremendous application possibilities in metropolitan road safety and traffic management. Due to the effect of numerous factors, for example: climate, viewpoints and road conditions in real-time traffic scene, Anomaly detection actually faces many difficulties. There are many reasons for vehicle accidents, for example: crashes, vehicle on flames and vehicle breakdowns, which exhibits distinctive and obscure behaviours. In this paper, we approached with a model to identify oddity in street traffic by monitoring the vehicle movement designs in two unmistakable yet associated modes which is 1. The vehicle’s dynamic mode and 2. The vehicle’s Static mode. The vehicle’s static mode investigation is gained using the background modelling after the detection of a vehicle, this strategy is useful to locate the unusual vehicle movement which keep still out and about. The dynamic mode vehicle examination is gained from identified and followed vehicle directions to locate the strange direction which is distorted from the predominant movement designs. The outcomes from the double mode investigations are at long last fused together by driven a distinguishing proof model to get the last peculiarity. For this research we are using traffic-net Dataset, VGG19 CNN model along with ImageNet weights and OpenCV.

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

The potential of monitoring traffic conditions up to 15 times a day using sub-meter resolution EO images

2021 ◽  
Author(s):  
Refiz Duro ◽  
Georg Neubauer ◽  
Alexandra-Ioana Bojor
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Traffic Monitoring ◽  
Movement Direction ◽  
Time Lags ◽  
Time Data ◽  
Traffic Lights ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Spatial Coverage

&lt;p&gt;Urbanization and the trend of people moving to cities often leads to problematic traffic conditions, which can be very challenging for traffic management. It can hamper the flow of people and goods, negatively affecting businesses through delays and the inability to estimate travel times and thus plan, as well as the environment and health of population due to increased fuel consumption and subsequent air pollution. Many cities have a policy and rules to manage traffic, ranging from standard traffic lights to more dynamic and adaptable solutions involving in-road sensors or cameras to actively modify the duration of traffic lights, or even more sophisticated IoT solutions to monitor and manage the conditions on a city-wide scale. The core to these technologies and to decision making processes is the availability of reliable data on traffic conditions, and better yet real-time data. Thus, a lot of cities are still coping with the lack of good spatial and temporal data coverage, as many of these solutions are requiring not only changes to the infrastructure, but also large investments.&lt;/p&gt;&lt;p&gt;One approach is to exploit the current and the forthcoming advancements made available by Earth Observation (EO) satellite technologies. The biggest advantage is EOs great spatial coverage ranging from a few km&amp;#178; to 100 km&amp;#178; per image on a spatial resolution down to 0.3m, thus allowing for a quick, city-spanning data collection. Furthermore, the availability of imaging sensors covering specific bands allows the constituent information within an image to be separated and the information to be leveraged.&lt;/p&gt;&lt;p&gt;In this respect, we present the findings of our work on multispectral image sets collected on three occasions in 2019 using very high resolution WorldView-3 satellite. We apply a combination of machine learning and PCA methods to detect vehicles and devise their kinematic properties (e.g., movement, direction, speed), only possible with satellites with a specific design allowing for short time lags between imaging in different spectral bands. As these data basically constitute a time-series, we will discuss how the results presented fully apply to the forthcoming WorldView-Legion constellation of satellites providing up to 15 revisits per day, and thus near-real time traffic monitoring and its impact on the environment.&lt;/p&gt;

scholarly journals Assessments of Real-Time Communications over TSN Automotive Networks

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 556
Author(s):  
Lucia Lo Bello ◽  
Gaetano Patti ◽  
Giancarlo Vasta
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Communication System ◽  
Traffic Management ◽  
Mac Layer ◽  
Automated Driving ◽  
Real Time Traffic ◽  
Management Scheme ◽  
Event Driven ◽  
Automotive Networks

The IEEE 802.1Q-2018 standard embeds in Ethernet bridges novel features that are very important for automated driving, such as the support for time-driven communications. However, cars move in a world where unpredictable events may occur and determine unforeseen situations. To properly react to such situations, the in-car communication system has to support event-driven transmissions with very low and bounded delays. This work provides the performance evaluation of EDSched, a traffic management scheme for IEEE 802.1Q bridges and end nodes that introduces explicit support for event-driven real-time traffic. EDSched works at the MAC layer and builds upon the mechanisms defined in the IEEE 802.1Q-2018 standard.

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

scholarly journals ENHANCED VANET ROUTING PROTOCOLS FOR DYNAMIC MAPPING IN REAL TIME TRAFFIC

2019 ◽  
Vol 01 (03) ◽  
pp. 139-147
Author(s):  
Wang Haoxiang ◽  
Smys S
Keyword(s):  
Real Time ◽  
Routing Protocols ◽  
Traffic Management ◽  
Path Optimization ◽  
Delivery Ratio ◽  
Digital Map ◽  
Real Time Traffic ◽  
Dynamic Mapping ◽  
Adhoc Network ◽  
Frame Work

The developments in the means of transportation along with the communication advancements has made the automotives to step into its next level of innovation by providing a safe, convenient and well-timed transportation. This is made possible by the introduction of the frame work that is particularly designed to establish connectivity between vehicles on road without any previous structure to support with. This paradigm formed particularly in organizing communication between vehicles is the vehicular Adhoc network (VANET) that causes a vehicles to vehicle connection for proper managing of the traffic flow to make the travel more safe and comfortable. The paper proposes a dynamic mapping of real time traffic with the acquisition of digital map by crowd mapping with clustering to offer path optimization to minimize the delay in the responses, for having an efficient traffic managing. The evaluation of the proposed methodology ensures the minimization of the delay in the communication and the improved delivery ratio incurred, when compared with the carry-forward based routings methods that cause more delay resulting in imperfect traffic management.

scholarly journals Sistem Pengamatan Kondisi Lalu Lintas Berbasis Data GPS pada Smartphone (Studi Kasus : Kota Denpasar)

2020 ◽  
Vol 7 (4) ◽  
pp. 667
Author(s):  
Gede Herdian Setiawan ◽  
I Ketut Dedy Suryawan
Keyword(s):  
Real Time ◽  
Traffic Congestion ◽  
Data Retrieval ◽  
Traffic Information ◽  
Vehicle Speed ◽  
Observation Model ◽  
Economic Activities ◽  
Traffic Condition ◽  
Traffic Conditions ◽  
Real Time Traffic

<p>Pertumbuhan jumlah kendaraan yang semakin meningkat setiap tahunnya mengakibatkan volume kendaraan yang melintasi ruas jalan semakin padat yang kerap mengakibatkan kemacetan lalu lintas. Kemacetan lalu lintas dapat menjadi beban biaya yang signifikan terhadap kegiatan ekonomi masyarakat. Informasi lalu lintas yang dinamis seperti informasi kondisi lalu lintas secara langsung <em>(real time)</em> akan membantu mempengaruhi aktivitas masyarakat pengguna lalu lintas untuk melakukan perencanaan dan penjadwalan aktivitas yang lebih baik. Penelitian ini mengusulkan model pengamatan kondisi lalu lintas berbasis data GPS pada <em>smartphone</em>, untuk informasi kondisi lalu lintas secara langsung. GPS <em>Receiver</em> pada <em>smartphone</em> menghasilkan data lokasi secara instan dan bersifat mobile sehingga dapat digunakan untuk pengambilan data kecepatan kendaraan secara langsung. Kecepatan kendaraan diperoleh berdasarkan jarak perpindahan koordinat kendaraan dalam satuan detik selanjutnya di konversi menjadi satuan kecepatan (km/jam) kemudian data kecepatan kendaraan di proses menjadi informasi kondisi lalu lintas. Secara menyeluruh model pengamatan berfokus pada tiga tahapan, yaitu akuisisi data kecepatan kendaraan berbasis GPS pada <em>smartphone</em>, pengiriman data kecepatan dan visualisasi kondisi lalu lintas berbasis GIS. Pengujian dilakukan pada ruas jalan kota Denpasar telah mampu mendapatkan data kecepatan kendaraan dan mampu menunjukkan kondisi lalu lintas secara langsung dengan empat kategori keadaan lalu lintas yaitu garis berwarna hitam menunjukkan lalu lintas macet dengan kecepatan kendaraan kurang dari 17 km/jam, merah menunjukkan padat dengan kecepatan kendaraan 17 km/jam sampai 27 km/jam, kuning menunjukkan sedang dengan kecepatan kendaraan 26 km/jam sampai 40 km/jam dan hijau menunjukkan lancar dengan kecepatan kendaraan diatas 40 km/jam.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Abstract"><em>The growth in the number of vehicles that is increasing every year has resulted in the volume of vehicles crossing the road increasingly congested which often results in traffic congestion. Traffic congestion can be a significant cost burden on economic activities. Dynamic traffic information such as information on real time traffic conditions will help influence the activities of the traffic user community to better plan and schedule activities. This study proposes a traffic condition observation model based on GPS data on smartphones, for information on real time traffic conditions. The GPS Receiver on the smartphone produces location and coordinate data instantly and is mobile so that it can be used for direct vehicle speed data retrieval. Vehicle speed is obtained based on the displacement distance of the vehicle's coordinates in units of seconds and then converted into units of speed (km / h), the vehicle speed data is then processed into information on traffic conditions. Overall, the observation model focuses on three stages, namely GPS-based vehicle speed data acquisition on smartphones, speed data delivery and visualization of GIS-based traffic conditions. Tests carried out on the Denpasar city road segment have been able to obtain vehicle speed data and are able to show traffic conditions directly with four categories of traffic conditions, namely black lines indicating traffic jammed with vehicle speeds of less than 17 km / h, red indicates heavy with speed vehicles 17 to 27 km / h, yellow indicates medium speed with vehicles 26 km/h to 40 km / h and green shows fluent with vehicle speeds above 40 km / h.</em></p><p><em><strong><br /></strong></em></p>

scholarly journals Research on Optimized Control Model of Freeway Based on Dynamic Traffic Demand Estimation

2014 ◽  
Vol 6 ◽  
pp. 797293 ◽  
Author(s):  
Zhu Jiang ◽  
Shubin Li
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Demand Estimation ◽  
Control Model ◽  
Control Module ◽  
Traffic Demand ◽  
The Real ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Global Optimal

According to the estimation information of dynamic traffic demands, a novel optimal control model of freeway was established on the basis of the hierarchical concept. There are four control modules in this model. The OD prediction module predicts the total traffic demands in a long time and determines the upper bound of the future queuing length in advance; the global optimal control module predicts the future traffic state and establishes the coordination constraints for each ramp in the network; the traffic demand estimation module estimates the real-time traffic conditions for each ramp; the local adaptive control module regulates ramp metering rate according to the estimated information of the real-time traffic conditions and the results optimized by the global optimal control module. The simulation results show that this control system is of a good dynamic performance. It coordinates the benefits of various ramps and optimizes the overall performance of the freeway network.

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