Access In Vehicular Environments Research Articles

Intelligent Resource Allocation Scheme Using Reinforcement Learning for Efficient Data Transmission in VANET.

Vehicular ad hoc networks (VANETs) use multiple channels to communicate using wireless access in vehicular environment (WAVE) standards to provide a variety of vehicle-related applications. The current IEEE 802.11p WAVE communication channel structure is composed of one control channel (CCH) and several service channels (SCHs). SCHs are used for non-safety data transmission, while the CCH is used for broadcasting beacons, control, and safety. WAVE devices transmit data that alternate between CCHs and SCHs, and each channel is active for a duration called the CCH interval (CCHI) and SCH interval (SCHI), respectively. Currently, both intervals are fixed at 50 ms. However, fixed-length intervals cannot effectively respond to dynamically changing traffic loads. Additionally, when many vehicles are simultaneously using the limited channel resources for data transmission, the network performance significantly degrades due to numerous packet collisions. Herein, we propose an adaptive resource allocation technique for efficient data transmission. The technique dynamically adjusts the SCHI and CCHI to improve network performance. Moreover, to reduce data collisions and optimize the network's backoff distribution, the proposed scheme applies reinforcement learning (RL) to provide an intelligent channel access algorithm. The simulation results demonstrate that the proposed scheme can ensure high throughputs and low transmission delays.

Design of Leaky Wave Antenna for V2V Communications

In this article, a low-profile, microstrip-based, periodic leaky wave antenna has been proposed for vehicle-to-vehicle (V2V) communications. The leaky-wave structure, loaded periodically with stepped impedance resonator stubs operates in the 5.4–6.2 GHz frequency band, which includes the WAVE (Wireless Access in Vehicular Environments) band (5.85–5.925 GHz) required for automated vehicular communications. The S11 obtained in the spectrum is below −12.68 dB. While the majority of the antennas designed for V2V communications produced omnidirectional patterns, the structure proposed in this work yields a directional pattern, preventing unnecessary outages of signals. The periodic structure gives an added advantage of beam scanning, resulting in a wider, yet directive coverage in the desired frequency band. A backward beam scan from −13˚ to −31˚ is obtained in the frequency range of 5.4–6.2 GHz with a gain variation of around ±0.6 dB only.

A Multi-Channel Packet Scheduling Approach to Improving Video Delivery Performance in Vehicular Networks

When working with the Wireless Access in Vehicular Environment (WAVE) protocol stack, the multi-channel operation mechanism of the IEEE 1609.4 protocol may impact the overall network performance, especially when using video streaming applications. In general, packets delivered from the application layer during a Control Channel (CCH) time slot have to wait for transmission until the next Service Channel (SCH) time slot arrives. The accumulation of packets at the beginning of the latter time slot may introduce additional delays and higher contention when all the network nodes try, at the same time, to obtain access to the shared channel in order to send the delayed packets as soon as possible. In this work, we have analyzed these performance issues and proposed a new method, which we call SkipCCH, that helps the MAC layer to overcome the high contention produced by the packet transmission bursts at the beginning of every SCH slot. This high contention implies an increase in the number of packet losses, which directly impacts the overall network performance. With our proposal, streaming video in vehicular networks will provide a better quality of reconstructed video at the receiver side under the same network conditions. Furthermore, this method has particularly proven its benefits when working with Quality of Service (QoS) techniques, not only by increasing the received video quality but also because it avoids starvation of the lower-priority traffic.

Security in Optical Wireless Communication-Based Vehicular Ad Hoc Networks Using Signature and Certificate Revocation

A vehicular ad hoc network is a capable method of making possible road well-being, traffic supervision, as well as information distribution for driving users and travelers. One definitive objective in the blueprint of this type of network is to refuse to accept a variety of malevolent mistreatment and security assaults. The paper analyzed the existing procedure, which has covered the ways of offering security duties and conserving user solitude in the context of wireless access in vehicular environments (WAVE) applications. To make the standards more realistic, it considers techniques of certificate revocation and conditional privacy preservation. These techniques are found to be the most promising ones in vehicular ad hoc networks (VANET). Therefore, a group of narrative security methods is proposed for the safe implementation of the techniques of certificate revocation and conditional privacy preservation. For enhancement of security, the paper proposes that the message should be encapsulated with a proper certificate and be duly signed. For faster communication, we propose the use of optical wireless communication (OWC) between an onboard unit (OBU) and a roadside unit (RSU).

A Novel Analytical Model for the IEEE 802.11p/bd Medium Access Control, with Consideration of the Capture Effect in the Internet of Vehicles

The traditional vehicular ad hoc network (VANET), which is evolving into the internet of vehicles (IoV), has drawn great attention for its enormous potential in road safety improvement, traffic management, infotainment service support, and even autonomous driving. IEEE 802.11p, as the vital standard for wireless access in vehicular environments, has been released for more than one decade and its evolution, IEEE 802.11bd, has also been released for a few months. Since the analytical models for the IEEE 802.11p/bd medium access control (MAC) play important roles in terms of performance evaluation and MAC protocol optimization, a lot of analytical models have been proposed. However, the existing analytical models are still not accurate as a result of ignoring some important factors of the MAC itself and real communication scenarios. Motivated by this, a novel analytical model is proposed, based on a novel two-dimensional (2-D) Markov chain model. In contrast to the existing studies, all the important factors are considered in this proposed model, such as the backoff freezing mechanism, retry limit, post-backoff states, differentiated packet arrival probabilities for empty buffer queue, and queue model of packets in the buffer. In addition, the influence of the capture effect under a Nakagami-m fading channel has also been considered. Then, the expressions of successful transmission, collided transmission, normalized unsaturated throughput, and average packet delay are all meticulously derived, respectively. At last, the accuracy of the proposed analytical model is verified via the simulation results, which show that it is more accurate than the existing analytical models.

A Bee Colony-Based Algorithm for Task Offloading in Vehicular Edge Computing

Complex vehicular applications, such as automatic driving and augmented reality are delay sensitive and require massive computational resources. Despite being more connected and smarter, vehicles still cannot appropriately meet the demands of these applications. By allowing neighboring vehicles and edge servers coupled to base stations to share their available computing resources, vehicular edge computing systems help to handle these applications. Then, vehicles can use the task offloading technique by sending application tasks to be executed remotely and receiving the processing results later. Although this technique aims to reduce application execution time, performing it in vehicular scenarios is challenging. In such scenarios, network nodes vary their computing and energy loads and move quickly, causing frequent disconnections and failures. Thus, we propose an algorithm called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Bee colony-based Task offloading in Vehicular edge computing</i> (BTV) to reliably reduce the execution time of applications in vehicular edge computing systems. The BTV algorithm provides task scheduling solutions to different servers in a feasible time, using several contextual parameters and wireless access in vehicular environments and fifth-generation networks. Experimental results show that our solution can reduce the average execution time of applications by up to 74.4% and with up to 0.0% of failures, outperforming other existing solutions.

Deep learning-based channel quality indicators prediction for vehicular communication

Vehicular communication shares essential information for safety and convenience. Vehicular communication must guarantee a high transmission rate with stable communication. In vehicular communication environments, the channel characteristic frequently varies due to the high-speed movement of the vehicles. Understanding the channel conditions is essential to maintain stable communication. We propose an optimal channel quality indicator (CQI) prediction model for expecting channel characteristics. Our prediction model defines the CQI from the received signal strength indication (RSSI) and is applied to the IEEE 802.11p wireless access in vehicular environments (WAVE) standard. The prediction part applies robust long-short term memory (LSTM) network to sequential data. The CQI prediction model is trained and evaluated using vehicular communication data collected by an IEEE 802.11p WAVE device. We compare the prediction performance of the proposed model with the auto-regressive integrated moving average, support vector regression, and multilayer perception models.

Road Safety on the Example of Wireless Services – Case Study

The paper considers organising wireless access in vehicular environments. Such environments are normally affected by Doppler effects, so the IEEE 802.11p standard is expected to ensure an appropriate quality of service for moving objects. Theoretically, the IEEE 802.11p standard compensates for Doppler effects, but it should be ascertained whether 802.11p is still efficient at tiny Doppler shifts and when an object moves at higher speeds. The 802.11p link provides a data rate which is twice as low for 802.11a. Thus, an end-to-end simulation is carried out for the links at wide ranges of signal-to-noise ratio by varying the Doppler shift from 0 Hz to 100 Hz. The simulation also involves 8 modulation types for 128-, 512-, and 1024-bit packet transmissions to cover all possible study cases. The efficiency criterion is the packet-error rate, to which the data rate is additionally considered. The main simulation result is that the 802.11p link is efficient only at not high speeds. The packet length should be shortened to suppress the influence of the object’s speed. Therefore, to enable high-quality wireless access in vehicular environments, a combination of the 802.11p and 802.11a links should be used, where phase shift keying is more effective for 802.11a and quadrature amplitude modulation is more effective for 802.11p. The trade-off herein is a data rate versus margin speed.

Intermittent jamming for eavesdropping defense in WAVE based vehicular networks

Wireless Access in Vehicular Environments (WAVE) based vehicular networking has been considered as a promising technology to improve road safety and provide diverse value-added services. However, it is vulnerable to eavesdropping attacks due to the broadcasting nature of wireless communications. Eavesdropping in WAVE based vehicular network can reveal drivers' private and can be taken as preamble to other critical attacks resulting in severe threats to drivers' personal safety and property safety. In this paper, we deal with this threat by proposing an intermittent jamming (IJ) based eavesdropping defense mechanism. The optimal IJ scheme is found by solving the problem of minimizing the jamming energy cost while disabling the eavesdropping activities. The practicability of the design is ensured by considering the network specific communication properties. Numerical analysis is conducted to investigate the relationship between the optimal IJ scheme and the network scenario. Simulation study is carried out to compare the performance of our design with that of the existing continuous jamming (CJ) based scheme. The results indicate that comparing with the CJ scheme, our design uses less energy to disable eavesdropping. IJ saves more than 34% energy while achieving an average packet error rate (PER) of 87.42% at the eavesdropper, and saves more than 22% energy while achieving an average PER of 94.95% at the eavesdropper.

Virtual Traffic Light Implementation on a Roadside Unit over 802.11p Wireless Access in Vehicular Environments.

Blind intersections have high accident rates due to the poor visibility of oncoming traffic, high traffic speeds, and lack of infrastructure (e.g., stoplights). These intersections are more commonplace in rural areas, where traffic infrastructure is less developed. The Internet of Vehicles (IoV) aims to address such safety concerns through a network of connected and autonomous vehicles (CAVs) that intercommunicate. This paper proposes a Road-Side Unit-based Virtual Intersection Management (RSU-VIM) over 802.11p system consisting of a Field-Programmable Gate Array (FPGA) lightweight RSU that is solar power-based and tailored to rural areas. The RSU utilizes the proposed RSU-VIM algorithm adapted from existing virtual traffic light methodologies to communicate with vehicles over IEEE 802.11p and facilitate intersection traffic, minimizing visibility issues. The implementation of the proposed system has a simulated cloud delay of 0.0841 s and an overall system delay of 0.4067 s with 98.611% reliability.

Cooperative vehicular networks: An optimal and machine learning approach

Intelligent Transport Systems (ITS) provide a promising technology to enhance road safety. The vehicular standard wireless access in vehicular environment (WAVE), also known as dedicated short-range communication (DSRC), can assist in reducing the number of deadly crashes. However, DSRC has a limited range. To enhance the network coverage, roadside units (RSUs) are placed along the road. However, the placement of RSUs at every instant increases the infrastructure cost. In this paper, we proposed the cooperative vehicular architecture, with network function virtualization (NFV) enabled RSU inside the mobile edge computing (MEC) unit. RSUs are only placed in the dense traffic region. We applied the Long short-term memory (LSTM) based machine-learning algorithm to predict the traffic flow based on the vehicle information table (VIT) maintained at the MEC unit. NFV is implemented at the top of RSU. Based on predicted traffic density it assists RSU to enhance its coverage range by exploiting the transmit power. Furthermore, MEC is also responsible for cooperative relay-based communication. Optimal stopping theory is modeled to select the best candidate relay node immediately. In this paper, we tested the proposed scheme in actual on-road vehicles and through simulations performed in network simulator NS-3.

Design of V2X-Based Vehicular Contents Centric Networks for Autonomous Driving

Recent technical innovation has driven the evolution of autonomous vehicles. To improve safety as well as on-road vehicular experience, vehicles should be connected with each other or to vehicular networks. Some specification groups, e.g., IEEE and 3GPP, have studied and released vehicular communication requirements and architecture. IEEE’s Wireless Access in Vehicular Environment focuses on dedicated and short-range communication, while 3GPP’s New Radio V2X supports not only sidelink but also uplink communication. The 3GPP Release 16, which supports 5G New Radio, offers evolved functionalities such as network slice, Network Function Virtualization, and Software-Defined Networking. In this paper, we define and design a vehicular network architecture compliant with 5G core networks to enable and support autonomous driving. As a validation example, a high-definition map needs to contain the context of trajectory for localization and planning of autonomous driving vehicles. We also propose new methods by which autonomous vehicles can push and pull map content efficiently, without causing bottlenecks on the network core. We evaluate the performance of the proposed method via network simulations and our autonomous driving vehicle on the road. Experimental results indicate that the proposed method improves the performance of vehicular content delivery in real-world road environments.

A flexible and adaptive medium access control protocol for improving quality of service in vehicular ad-hoc networks

Designing MAC (Medium Access Control) protocols for VANETs is a difficult task due to the inherently unstable nature of these networks when compared to traditional ad hoc networks (high node speed, position changes that lead to disconnections, signal losses, etc.). In recent years, several standardization efforts have been made by the IEEE in association with the scientific community in this area and they proposed the 1609.4 MAC protocol in the IEEE WAVE (Wireless Access in Vehicular Environments) stack. The aim of our work is to improve the quality of service and overall performances of this 1609.4 MAC protocol by proposing three mechanisms. First, we introduce an equity algorithm that aims to ensure more fairness between nodes. We also adapt the SCH (Service CHannel) interval to the network's needs with a dynamic SCH interval mechanism. Finally, we propose an emergency mechanism that aims to ensure the transmission of critical safety packets when dangerous events occur on the road. The results of our simulations show a significant improvement of the protocol's performances in terms of throughput, packet loss and critical packet delivery rates under several scenarios.

Interference Rejection Combining Approach in Vehicle Communication Systems for Throughput Enhancement

In this paper, we present interference rejection combining scheme for interference suppression in wireless access in vehicular environments (WAVE) system. WAVE system performances depend on interference traffic since various signals and noises are present due to various vehicles on the road. The IRC scheme can minimize the interference presence from the received signal within the massive interference condition, resulting in the substantial gain of signal-to-interference and noise ratios (SINR) and performance. Based on the experiment of our proposed scheme, given the vehicle speed, SINR and different channel condition, our proposed scheme for interference suppression achieved significant improvements by 2 dB SINR performance gain in the low speed condition and above 0.5 dB performance gain at the high speed case. To extend our scheme for the comprehensive analysis, we also produced the vehicle speed and SINR performance map, which showed the performance pattern over vehicle speed and SINR of our scheme.

Data Dissemination Scheme for VANET using Genetic algorithm and Particle Swarm Optimization

A vehicular ad hoc network (VANET) consist of moving vehicles connected via wireless technology e.g., Wireless Access in Vehicular Environment (WAVE) for the aim of exchanging information. Therefore data dissemination in VANET has become issue of debate for researcher. In VANET broadcasting play an important role. The aim of VANET is to ensure passenger safety through emergency message. With multiple objectives broadcast storm is assumed to be an NP-Hard problem. In this paper we propose DDV algorithm to solve broadcast storm problem. Fitness function has used to optimize the objective of proposed algorithm. The proposed algorithm producing better optimization results. We are considering a highway scenario in city with dynamic rotation, to evaluate the performance of the DDV algorithm we compare the result with Smart flooding techniques, MOGA (Multi Objective Genetic algorithm) [1] and EEADP. Our result show the better performance in terms of reduce the number of retransmission, increase the packet delivery ratio and provide better throughput.

Proactive Flexible Interval Intermittent Jamming for WAVE‐Based Vehicular Networks

In this paper, we deal with the eavesdropping issue in Wireless Access in Vehicular Environments‐ (WAVE‐) based vehicular networks. A proactive flexible interval intermittent jamming (FIJ) approach is proposed which predicts the time length T of the physical layer packet to be transmitted by the legitimate user and designs flexible jamming interval (JI) and jamming‐free interval (JF) based on the predicted T. Our design prevents eavesdroppers from overhearing the information with low energy cost since the jamming signal is transmitted only within JI. Numerical analysis and simulation study validate the performance of our proactive FIJ, in terms of jamming energy cost and overhearing defense, by comparing with the existing intermittent jamming (IJ) and FIJ.

Optimal Exploitation of On-Street Parked Vehicles as Roadside Gateways for Social IoV—A Case of Kigali City

Vehicular Ad Hoc Network (VANET) is a subclass of Mobile Ad Hoc Network that mainly consists of moving and/or stationary vehicles, connected through wireless protocols such as IEEE 802.11p and wireless access in vehicular environments (WAVE). With the evolution of the Internet of Things (IoT), ordinary VANET has turned to the Internet of Vehicles (IoV), with additional social aspects, a novel extension themed SIoV has become common in urban areas. However vehicular wireless communication paradigms exhibit short radio communication. This problem has always been approached by supplementing moving vehicles with stationary Road Side Infrastructures, commonly known as roadside units (RSUs). The penetration of such RSUs on the global market is very low; furthermore, their procurement, deployment, and maintenance costs are prohibitively very high. All mentioned challenges have discouraged the widespread deployment of roadside infrastructure especially within large urban scenarios. With this research, we leverage on-street parked vehicles to allow them to exist as temporal gateways in the case study area. A novel modeling technique is introduced to enable a specific Percentage of parked vehicles to take up the role of roadside gateways for a certain percentage of their parking time. A mobile application is implemented that manages parking duration of the vehicle, based on the arrival, and departure time frames. Two more existing strategies were discussed (road-intersection RSUs deployment approach and Inter-vehicle scheme) to validate our proposed method through comparative studies. To evaluate the network performance evaluation, we compare two performance metrics, that is, Packets success delivery rate, and overall packets throughput under numerous vehicle densities. Using parked vehicles as temporal roadside gateways has demonstrated better results in comparison to intersection based RSUs deployment approach, and free vehicle to vehicle communication approach.

WAVE-Based Vehicle Localization With Fuzzy Filter for Autopilot in a Free-Flow Toll Station

In this article, a wireless access in vehicular environments based localization technology is proposed to supplement the gaps of output frequency for global position system, saving dedicated localization facility. A subcarrier-based reflection filter is used to mitigate multipath effect. A fuzzy vector space and its fuzzy distance of normalized received signal strength indication sequence are formulated to solve the scarce variability problem of the position feature while offsetting common hardware errors and traffic noises. Based on them, the vehicle coordinates are calculated through integrating position feature with fuzzy distance, precise and stable result is achieved. Experiments confirmed its constant centimeter-level accuracy error, millisecond-level execute time as well as ignorable effects of grid size, speed, traffic, and weather. Performances meet the requirements of enforcement, autopilot, and navigation.

Symbol-Level Selective Channel Estimation in Packet-Based OFDM Systems.

Wireless access in vehicular environments to support wireless communication between vehicles has been developed to provide road safety and infotainment services. In vehicular environments where the channel changes rapidly, channel estimation is very important in improving the reliability of wireless communication. Therefore, numerous channel estimation schemes have been proposed; however, none of the schemes proposed so far can perform well over the entire signal-to-noise ratio (SNR) region. In this paper, we propose a novel channel estimation scheme that selectively uses the better scheme between two channel estimation schemes on a symbol-by-symbol basis. The results show that the proposed scheme performs symbol-by-symbol selection of the better channel estimation scheme within a packet, and thus shows excellent performance over the entire SNR region in vehicular environments in terms of the bit error rate and packet error rate.

Collision Prevention Algorithm for Fishing Vessels Using mmWAVE Communication

This study leveraged the millimeter wireless access in vehicular environments (mmWAVE) communication technology to reflect the maneuvering characteristics of small fishing vessels and constructed a collision prevention algorithm that can be applied relatively easily. The algorithm was verified through simulation and actual ship experiments. The algorithm had four components: detection of vessels within three miles; identification of dangerous vessels by applying the time to the closest point of approach (TCPA) and distance at the closest point of approach (DCPA) criteria; continuous monitoring of maritime traffic risk; and incremental alarm signaling. The simulations and experiments confirmed that the alarm was generated incrementally in accordance with the distance to a dangerous situation, with no false alarms. Thus, the proposed algorithm offers potential to enhance the safety of small fishing vessels.