scholarly journals Analysis of the Message Propagation Speed in VANET with Disconnected RSUs

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 782
Author(s):  
Dhari Ali Mahmood ◽  
Gábor Horváth
Keyword(s):  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Propagation Speed ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Support Network ◽  
Markov Renewal Process ◽  
The Road ◽  
Message Propagation ◽  
Road Side Units

Vehicular ad-hoc networks (VANETs), which are networks of communicating vehicles, provide the essential infrastructure for intelligent transportation systems. Thanks to the significant research efforts to develop the technological background of VANETs, intelligent transportation systems are nowadays becoming a reality. The emergence of VANETs has triggered a lot of research aimed at developing mathematical models in order to gain insight into the dynamics of the communication and to support network planning. In this paper we consider the message propagation speed on the highway, where messages can be exchanged not only between the vehicles, but also between the road-side infrastructure and the vehicles as well. In our scenario, alert messages are generated by a static message source constantly. Relying on an appropriately defined Markov renewal process, we characterize the message passing process between the road-side units, derive the speed of the message propagation, and provide the transient distribution of the distance where the message is available. Our results make it possible to determine the optimal distance between road-side units (RSUs) and to calculate the effect of speed restrictions on message propagation.

scholarly journals Enhancement of Link Stability and Connectivity in Vehicular Ad hoc Networks

2021 ◽  
Vol 12 (1S) ◽  
pp. 266-271
Author(s):  
Kishor N. Tayade, Et. al.
Keyword(s):  
Ad Hoc Networks ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Routing Algorithm ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Mobile Nodes ◽  
The Road ◽  
Hoc Networks

Vehicular Ad hoc Networks is a promising sub-group of MANET. VANET is deployed on the highways, where the vehicles are mobile nodes. Safety and intelligent transportation are important VANET applications that require appropriate communication among vehicles, in particular routing technology. VANETs generally inherit their common features from MANETs where vehicles operate in a collaborative and dispersed way for promoting contact among vehicles and with network infrastructure like the Road Side Units (RSU) for enhanced traffic experience. In view of the fast growth of Intelligent Transportation Systems (ITS), VANETs has attracted considerable interest in this decade. VANET suffer from a major problem of link failure due to dynamic mobility of vehicles. In this paper we proposed a position based routing algorithm to identify stable path, this will improve the routing by decreasing overhead and interrupting the number of links. Link Expiration Time (LET) is used to provide the stable link, the link with the longest LET is considered as the most stable link. The multicast Ad-hoc On-demand Distance Vector (MAODV) is proposed to avoid the link breakages by using a link with longest LET.  Data loss is reduced by avoiding link breakages and enhance throughput by reducing the communication delay.

A Comprehensive Survey of the Key Technologies and Challenges Surrounding Vehicular Ad Hoc Networks

2021 ◽  
Vol 12 (4) ◽  
pp. 1-30
Author(s):  
Zhenchang Xia ◽  
Jia Wu ◽  
Libing Wu ◽  
Yanjiao Chen ◽  
Jian Yang ◽  
...  
Keyword(s):  
Ad Hoc Networks ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Key Technologies ◽  
Comprehensive Survey ◽  
Hoc Networks ◽  
Graph Neural Networks

Vehicular ad hoc networks ( VANETs ) and the services they support are an essential part of intelligent transportation. Through physical technologies, applications, protocols, and standards, they help to ensure traffic moves efficiently and vehicles operate safely. This article surveys the current state of play in VANETs development. The summarized and classified include the key technologies critical to the field, the resource-management and safety applications needed for smooth operations, the communications and data transmission protocols that support networking, and the theoretical and environmental constructs underpinning research and development, such as graph neural networks and the Internet of Things. Additionally, we identify and discuss several challenges facing VANETs, including poor safety, poor reliability, non-uniform standards, and low intelligence levels. Finally, we touch on hot technologies and techniques, such as reinforcement learning and 5G communications, to provide an outlook for the future of intelligent transportation systems.

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.

scholarly journals REDUCING THE TIME TO GET EMERGENCY ASSISTANCE FOR ACCIDENT VEHICLES ON THE ROAD THROUGH AN INTELLIGENT TRANSPORTATION SYSTEM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 827-832
Author(s):  
A. H. Nourbakhsh ◽  
M. R. Delavar ◽  
M. Jadidi ◽  
B. Moshiri
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Intelligent System ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Dijkstra Algorithm ◽  
Notification System ◽  
Smart Transportation ◽  
The Road ◽  
On The Road

Abstract. Intelligent Transportation Systems (ITS) is one of the main components of a smart city. ITS have several purposes including the increase of the safety and comfort of the passengers and the reduction of the road accidents. ITS can enhance safety in three modes before, within and after the collision by preventing accident via assistive system, sensing the collision situation and calculating the time of the collision and providing the emergency response in a timely manner. The main objective of this paper is related to the smart transportation services which can be provided at the time of the collision and after the accident. After the accident, it takes several minutes to hours for the person to contact the emergency department. If an accident takes place for a vehicle in a remote area, this time increases and that may cause the loss of life. In addition, determination of the exact location of the accident is difficult by the emergency centres. That leads to the possibility of erroneous responder act in dispatching the rescue team from the nearest hospital. A new assistive intelligent system is designed in this regard that includes both software and hardware units. Hardware unit is used as an On-Board Unit (OBU), which consists of GPS, GPRS and gyroscope modules. Once OBU detects the accident, a notification system designed and connected to OBU will sent an alarm to the server. The distance to the nearest emergency center is calculated using Dijkstra algorithm. Then the server sends a request for assistance to the nearest emergency centre. The proposed system is developed and tested at local laboratory conditions. The results show that this system can reduce Ambulance Arrival Time (AAT). The preliminary results and architecture of the system have been presented. The inclination angle determined by the proposed system along with the car position identified by the installed GPS sensor assists the crash/accident warning part of the system to send a help request to the nearest road emergency centre. These results verified that the probability of having a remote and smart car crash/accident decision support system using the proposed system has been improved compared to that of the existing systems.

scholarly journals Driver’s Drowsiness Detection Based on Behavioural Changes using ResNet

2019 ◽  
Vol 8 (3) ◽  
pp. 5708-5712
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Motor Vehicles ◽  
Steering Wheel ◽  
Road Accidents ◽  
Drowsiness Detection ◽  
Behavioural Changes ◽  
The Road

Recently there has been growing interest in intelligent transportation system because the road accidents become biggest problems of mankind and the casualties of accident also increases rapidly every year. The casualties are very often witnessed in heavy and light motor vehicles. Moreover, the accidents occur mainly due to carelessness and drowsy feeling of the driver. Intelligent transportation systems use deep learning mechanism to detect drowsiness of the driver and alert the same to driver. It results in reduction of accidents. The driver’s behaviour during drowsiness is detected by three types of approaches. One approach deploys the sensors in steering wheel and accelerator of the vehicle and analyzes the signal sent by the sensors to detect the drowsiness. Second approach focuses on measuring the heart rate, pulse rate and brain signals etc to predict the drowsiness. Third approach uses the facial expression of the driver such as blinking rate of eye, eye closure and yawning etc. The cause for most of the road accidents is driver’s drowsiness. Therefore, in this paper, the behavioural changes of driver is accounted to detect the drowsiness of the driver. Eye movement and yawning are two behavioural changes of driver is considered in this paper. There are many CNN based deep learning architectures such AlexNet, VGGNet, ResNet. In this paper, we propose the drowsiness detection using ResNet because this method works on the principle of passing the output to the next la. The performance of proposed mechanism detects the drowsiness of the driver better than AlexNet and VGGNet.

scholarly journals Recent Developments on Security and Privacy of V2V & V2I Communications: A Literature Review

2020 ◽  
Vol 48 (4) ◽  
pp. 377-383
Author(s):  
Evangelos Mitsakis ◽  
Iliani Styliani Anapali
Keyword(s):  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
New Technologies ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Privacy Requirements ◽  
Recent Developments ◽  
Hoc Networks

In the recent years Intelligent Transportation Systems and associated technologies have progressed significantly, including services based on wireless communications between vehicles (V2V) and infrastructure (V2I). In order to increase the trustworthiness of these communications, and convince drivers to adopt the new technologies, specific security and privacy requirements need to be addressed, using Vehicular Ad Hoc Networks (VANETs). To maintain VANET′s security and eliminate possible attacks, mechanisms are to be developed. In this paper, previous researches are reviewed aiming to provide information concerning matches between an attack and a solution in a VANET environment.

scholarly journals Modeling of Situation Response Time in Vehicular Ad-Hoc Network

MATICS ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Raphael AKINYEDE
Keyword(s):  
Response Time ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
New Technology ◽  
Main Idea ◽  
Transportation Systems ◽  
The Road ◽  
Vehicle To Vehicle ◽  
On The Road

<p class="Text"><strong>—<em> </em></strong>In Vehicular Ad-Hoc Networks (VANETs), wireless-equipped vehicles form a network spontaneously while traveling along the road. The direct wireless transmission from vehicle to vehicle makes it possible for them to communicate even where there is no telecommunication infrastructure; this emerging new technology provide ubiquitous connectivity to vehicular nodes while on the move, The main idea is to provide ubiquitous connectivity to vehicular nodes while on the move, and to create efficient vehicle-to-vehicle communications that enable the Intelligent Transportation Systems (ITS). This is achieved by allowing nodes within certain ranges to connect with each other in order to exchange information. Since accident happens in split seconds, to avoid communication inefficiency, there is need for this information to get to the intended vehicle on time. To solve this problem, this work models each vehicle in a chain of others and how it responds to the traffic around it using Microscopic (also known as car-following) method for modeling traffic flow; driver- to-driver and driver-to-road interactions within a traffic stream and the interaction between a driver and another driver on road were considered. The essence of this modeling is to determine the minimum response time required for a vehicle in VANET to respond and communicate situations on the road. A simulated scenario was carried out for two vehicles, a leading vehicle and following vehicle. The result shows that with an average of 32 meters apart with average difference in velocity of   1.23m/s, a minimum of 0.9secs is required for efficient situation response communication to ensue between them.</p>

Traffic Signal Control for a Single Intersection-Based Intelligent Transportation System

2020 ◽  
pp. 159-180
Author(s):  
Nouha Rida ◽  
Mohammed Ouadoud ◽  
Abderrahim Hasbi
Keyword(s):  
Real Time ◽  
Waiting Time ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Information ◽  
Traffic Signal Control ◽  
Traffic Light ◽  
The Road ◽  
Real Time Traffic

Traffic optimization at an intersection, using real-time traffic information, presents an important focus of research into intelligent transportation systems. Several studies have proposed adaptive traffic lights control, which concentrates on determining green light length and sequence of the phases for each cycle in accordance with the real-time traffic detected. In order to minimize the waiting time at the intersection, the authors propose an intelligent traffic light using the information collected by a wireless sensors network installed in the road. The proposed algorithm is essentially based on two parameters: the waiting time in each lane and the length of its queue. The simulations show that the algorithm applied at a network of intersections improves significantly the average waiting time, queue length, fuel consumption, and CO2 emissions.

scholarly journals Automatic Extraction of Structural and Non-Structural Road Edges from Mobile Laser Scanning Data

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5030 ◽  
Author(s):  
Yang ◽  
Liu ◽  
Jiang ◽  
Xu ◽  
Sheng ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Laser Scanning ◽  
Large Scale ◽  
Auxiliary Information ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Road Maintenance ◽  
The Road ◽  
Large Scale Data ◽  
Road Width

Accurate road information is important for applications involving road maintenance, intelligent transportation, and road network updates. Mobile laser scanning (MLS) can effectively extract road information. However, accurately extracting road edges based on large-scale data for complex road conditions, including both structural and non-structural road types, remains difficult. In this study, a robust method to automatically extract structural and non-structural road edges based on a topological network of laser points between adjacent scan lines and auxiliary surfaces is proposed. The extraction of road and curb points was achieved mainly from the roughness of the extracted surface, without considering traditional thresholds (e.g., height jump, slope, and density). Five large-scale road datasets, containing different types of road curbs and complex road scenes, were used to evaluate the practicality, stability, and validity of the proposed method via qualitative and quantitative analyses. Measured values of the correctness, completeness, and quality of extracted road edges were over 95.5%, 91.7%, and 90.9%, respectively. These results confirm that the proposed method can extract road edges from large-scale MLS datasets without the need for auxiliary information on intensity, image, or geographic data. The proposed method is effective regardless of whether the road width is fixed, the road is regular, and the existence of pedestrians and vehicles. Most importantly, the proposed method provides a valuable solution for road edge extraction that is useful for road authorities when developing intelligent transportation systems, such as those required by self-driving vehicles.

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