Road Safety Applications Research Articles

ADAS (Advanced Driver Assistance System)

Innovations in information technologies have resulted in more complex road safety applications. These systems offer numerous possibilities for improving road mobility. This study provides an integrated system that addresses two essential topics :safety and efficiency. To this end, the development and implementation of an integrated advanced driver assistance system (ADAS) for rural and intercity environments is proposed. Flexible autopilot with usage productivity, a surpassing support mechanism for single-carriageway pathways that considers the correct velocity expansion and acknowledges between the finest appropriate path extends for the movement, a junction support structure with speed regulation during approximate moves, and a crash prevention system with vague movement features are among the characteristics that were recently developed. To accomplish this, rigorous automotive kinematics computations were used to preserve equilibrium, and power system simulations were used to create optimal patterns. Computer vision and modeling were utilized to test and optimize the control module operations. Finally, the equipment is designed to notify a driver if an issue is detected and, if necessary, assume control of the vehicle. ADAS radar detectors identify vehicles and the surrounding area using electromagnetic radiation. The device measures the pace and direction of viewed objects, enabling autonomous vehicle systems to send safety notifications and govern operating procedures. Every single bit of evidence, including automobile position, accurate satellite imagery, and intricate map-matching computations, impacts the choice-making mechanisms for different ADAS structures

Dynamic object detection using sparse LiDAR data for autonomous machine driving and road safety applications

Light Detection And Ranging (LiDAR) sensor offers solutions to extract real-time information of vehicle’s surroundings and can provide a new opportunity to improve the road safety related issues in mixed traffic conditions. This paper explores fundamental principles and combination of algorithms, to accurately detect, classify and track surrounding vehicles on expressways using a vehicle mounted cost-effective LiDAR sensor in dynamic conditions. The proposed approach employs algorithms such as Density-Based Spatial Clustering of Applications with Noise, Random sample consensus, and Kalman filter on 3D LiDAR data for ground and non-ground points segmentation, object clustering, road boundary identification, vehicle classification and tracking. Trajectory data of the tracked vehicles is used to estimate their relative positions and speeds. The surrounding vehicles were classified into three categories: two-wheelers, four-wheelers and heavy-vehicles. The proposed method achieves an accuracy, precision, recall, and F1-score above 94 %, demonstrating its robustness. The resilience and versatility of the proposed algorithm were validated through comprehensive evaluations on a significant dataset spanning over 8000 km (around 3.6 million frames) of driving data collected under varied environmental scenarios on expressway. Further, various applications of proposed methodology in road safety studies are discussed. The approach can extract real-time micro-level trajectory data for surrounding vehicles on expressways in any lighting condition, which is useful for researchers and can be used in connected and autonomous vehicles. It also provides valuable information for assessing surrogate safety measures and identifying road safety issues and suggesting countermeasures, including advanced and cost-effective driver assistance system applications.

An enhanced method for evaluating the effectiveness of protective devices for road safety application

This paper presents an enhanced probabilistic approach to estimate the real-world safety performance of new device concepts for road safety applications from the perspective of Powered Two-Wheeler (PTW) riders who suffer multiple injuries in different body regions. The proposed method estimates the overall effectiveness of safety devices for PTW riders by correlating computer simulations with various levels of actual injuries collected worldwide from accident databases. The study further develops the methodology initially presented by Johnny Korner in 1989 by introducing a new indicator, Global Potential Damage (GPD), that overcomes the limitations of the original method, encompassing six biomechanical injury indices estimated in five body regions. A Weibull regression model was fit to the field data using the Maximum Likelihood Method with boundaries at the 90% confidence level for the construction of novel injury risk curves for PTW riders. The modified methodology was applied for the holistic evaluation of the effectiveness of a new safety system, the Belted Safety Jacket (BSJ), in head-on collisions across multiple injury indices, body regions, vehicle types, and speed pairs without sub-optimizing it at specific crash severities. A virtual multi-body environment was employed to reproduce a selected set of crashes. The BSJ is a device concept comprising a vest with safety belts to restrict the rider’s movements relative to the PTW during crashes. The BSJ exhibited 59% effectiveness, with an undoubted benefit to the head, neck, chest, and lower extremities. The results show that the proposed methodology enables an overall assessment of the injuries, thus improving the protection of PTW users. The novel indicator supports a robust evaluation of safety systems, specifically relevant in the context of PTW accidents.

A secure routing protocol using trust‐based clustering and bionic intelligence algorithm for UAV‐assisted vehicular ad hoc networks

AbstractVehicular ad hoc networks (VANET) are one of the advanced technologies for distributing dynamic vehicular information across the globe. The VANET is extensively used in many applications, especially road safety applications and intelligent transport systems (ITS). However, direct communication causes high bandwidth (BW) requirement and power consumption. Hence, this article introduces a clustering‐based mechanism to communicate vehicles with infrastructures. The cluster head (CH) is formed based on certain rules, and nodes or vehicles are combined. But, maintaining stability remains challenging for the traditional clustering mechanism. Moreover, the developed technique must examine the malicious and reduce the risk of fake information sharing. This research emphasizes a trust‐based clustering mechanism to select the CH based on a vehicle's knowledge, reputation, and experience. In addition to this, the backup head is also analyzed to promote trust in each vehicle. After clustering, secure routing is undertaken. For this, a bionic remora optimization algorithm (BROA) is proposed, and it considers the hop Count Field as well as the transmission range of vehicles to select the best routes. The performance measures such as end‐to‐end delay ratio, packet delivery ratio (PDR), throughput, trust values, energy consumption are analyzed and compared with existing techniques. In an experimental scenario, the proposed technique has an end‐to‐end delay of 3.8 ms, PDR of 98%, trust value of .4 and .06 for wormhole and Sybil attack, energy of and throughput of 78.7 kbps are attained. The outcome results prove the efficacy of a proposed method.

ABM-V: An Adaptive Backoff Mechanism for Mitigating Broadcast Storm in VANETs

In vehicular ad hoc networks (VANETs), the broadcast storm problem may disable road safety applications and cause congestion or traffic accidents. Existing schemes propose broadcast storm mitigation by reducing the number of relay vehicles. Concurrently, in improving reachability, these schemes stipulate that vehicles expected to transmit packets to more next-hop neighbors have higher relay priority. However, the potential redundancy caused by duplicate reception by neighbors is ignored, which exacerbates the contention and collisions in transmission. This paper proposes an adaptive backoff mechanism for mitigating broadcast storm in VANETs (ABM-V). Specifically, the receiver estimates the expected benefit and redundancy by combining the distribution of neighbors. Then, the receiver adaptively adjusts the backoff time by utilizing Dempster-Shafer evidence theory. Finally, the receiver with the shortest backoff time becomes the relay and rebroadcasts the packet to its neighbors. Simulation results illustrate that ABM-V significantly reduces the rebroadcast ratio and redundancy ratio compared with the existing typical schemes while maintaining stable reachability.

Resilience-by-design in Adaptive Multi-agent Traffic Control Systems

Connected and Autonomous Vehicles (CAVs) with their evolving data gathering capabilities will play a significant role in road safety and efficiency applications supported by Intelligent Transport Systems (ITSs), such as Traffic Signal Control (TSC) for urban traffic congestion management. However, their involvement will expand the space of security vulnerabilities and create larger threat vectors. In this article, we perform the first detailed security analysis and implementation of a new cyber-physical attack category carried out by the network of CAVs against Adaptive Multi-Agent Traffic Signal Control (AMATSC), namely, coordinated Sybil attacks, where vehicles with forged or fake identities try to alter the data collected by the AMATSC algorithms to sabotage their decisions. Consequently, a novel, game-theoretic mitigation approach at the application layer is proposed to minimize the impact of such sophisticated data corruption attacks. The devised minimax game model enables the AMATSC algorithm to generate optimal decisions under a suspected attack, improving its resilience. Extensive experimentation is performed on a traffic dataset provided by the city of Montréal under real-world intersection settings to evaluate the attack impact. Our results improved time loss on attacked intersections by approximately 48.9%. Substantial benefits can be gained from the mitigation, yielding more robust adaptive control of traffic across networked intersections.

DSRC Versus LTE-V2X: Empirical Performance Analysis of Direct Vehicular Communication Technologies

Vehicle-to-Vehicle (V2V) communication systems have an eminence potential to improve road safety and optimize traffic flow by broadcasting Basic Safety Messages (BSMs). Dedicated Short-Range Communication (DSRC) and LTE Vehicle-to-Everything (V2X) are two candidate technologies to enable V2V communication. DSRC relies on the IEEE 802.11p standard for its PHY and MAC layer while LTE-V2X is based on 3GPP’s Release 14 and operates in a distributed manner in the absence of cellular infrastructure. There has been considerable debate over the relative advantages and disadvantages of DSRC and LTE-V2X, aiming to answer the fundamental question of which technology is most effective in real-world scenarios for various road safety and traffic efficiency applications. In this paper, we present a comprehensive survey of these two technologies (i.e., DSRC and LTE-V2X) and related works. More specifically, we study the PHY and MAC layer of both technologies in the survey study and compare the PHY layer performance using a variety of field tests. First, we provide a summary of each technology and highlight the limitations of each in supporting V2X applications. Then, we examine their performance based on different metrics.

Cooperative communication for safety message dissemination in unsaturated networks with varying contention windows

SummarySafety message dissemination is crucial in vehicular ad hoc networks (VANETs) for road safety applications. Vehicles regularly transmit safety messages to surrounding vehicles to prevent road accidents. However, changing vehicle mobility and density can cause unstable network conditions in VANETs, making it inappropriate to use a fixed contention window (CW) for different network densities. It has been proposed a 1‐D Markov model under unsaturation conditions to analyze the performance of the system with varying CWs under changing vehicle densities. Additionally, it introduces the use of cooperative communication (CoC) to relay failed safety messages. In CoC, two control packets, namely, negative acknowledge (NACK) and enable to cooperate (ETC), are utilized. The proposed analytical model named cooperative communication for safety message dissemination (CoC‐SMD) is used to calculate throughput and average packet delay for varying CW and different packet size. The simulation confirms the validity of the analytical results and show significant improvement in the metrics through the use of varying CW sizes and CoC compared with existing techniques.

From conflicts to crashes: Simulating macroscopic connected and automated driving vehicle safety

Safety evaluation is a critical aspect through the future stages of automation development. Since there is a lack of historical and generalizable safety data in high levels of Connected and Autonomous Vehicles (CAVs), a possible approach to follow is the microscopic simulation method. Through microsimulation, vehicle trajectories are able to be exported and traffic conflicts to be identified using the Surrogate Safety Assessment Model (SSAM). Therefore, it is crucial to develop techniques in order to analyze conflict data extracted from microsimulation and evaluate crash data aiming to support road safety applications of automation technologies. This paper attempts to propose a safety evaluation approach for estimating crash rate of CAVs through microsimulation. For this purpose, the city center of Athens (Greece) was modelled using the Aimsun Next software paying attention to the calibration and validation of the model using real data of traffic characteristics. Moreover, different scenarios were formulated concerning different market penetration rates (MPRs) of CAVs and two fully automated generations (1st and 2nd generation) were simulated for modelling them. Subsequently, the SSAM software was used in order traffic conflicts to be identified and then converted to crash rate. Analysis of the outputs along with traffic data and network geometry characteristics were then conducted. The results indicated that in higher CAV MPRs, crash rates will be significantly lower as well as when the following-vehicle in the occurred conflict is a 2nd generation CAV. Lane change conflicts caused the highest crash rates compared to rear-end conflicts, which presented the lowest rates.

Networking in Vehicular Ad-Hoc Networks (VANET) for Accident Prevention

Abstract: VANET (Vehicular Ad Hoc Network) is an emerging technology for intelligent inter-vehicle communications. It is a specialized derivation of pure multi-hop ad hoc networking that is currently undergoing industrial prototyping; however, the dreamed idea of a general purpose vehicular ad hoc network is still a long way off. For the past few years, vehicular communication has been a hot topic. The VANET objective is to use short-range wireless technology to provide road safety and commercial comfort applications. Many routing protocols have been designed specifically for such networks, with the majority of them attempting to make use of information that may be available at the vehicle by the time a routing choice is required. We have investigated the AODV and GPSR in this study. Keywords: AODV, GPSR, Vehicular Ad Hoc Networks, Ad-Hoc Routing, Routing Protocols.

Traffic Aware Data Gathering Protocol for VANETs

Vehicular Ad-Hoc Networks (VANETs) are a challenging yet active research area. It offers a wide range of applications, including Intelligent Transport System (ITS), effective road traffic monitoring, efficient traffic flow and road safety applications. During real-time data gathering for emergency scenarios, the fixed silent segments cause a problem for smooth communication. Moreover, the critical ITS operations may be delayed due to this problem. This paper proposes a Real-Time Traffic-Aware Data Gathering Protocol (TDG) where the dynamic segmentation switching is adopted to handle the communication limitations. TDG is lightweight and dynamically designed for collecting and forwarding data packets based on current and rapid evolving traffic conditions. The primary objective is to reduce network and data communication overhead to incorporate real-time data collection time constraints. TDG implements a data aggregation scheme for data analysis to fetch information based on location, speed, vehicle id and neighbour count. Moreover, a data extraction scheme is implemented to increase data retrieval and data utilization effectiveness in an intelligent way at the base station. Extensive simulation and evaluation results validate that our proposed solution outperforms existing data gathering protocols in effectiveness, efficiency, delay, communication overhead and data transmission rate.

Efficient Reinforcement Learning-Based Transmission Control for Mitigating Channel Congestion in 5G V2X Sidelink

Channel congestion has been an open challenge for vehicular networks due to the limited resource of communication channels. Explosion of channel access requests from a massive number of transmitter vehicles can exhaust bandwidth and then degrade transmission quality. The rapid drop of messages (because of the high bit error rate in the transmission congestion condition) can threaten the safety of connected vehicles. Maintaining congestion-free communications is then essential to improve the reliability for vehicular networks, including Cellular-V2X (C-V2X)-based cooperative intelligent transport systems and road-safety applications. In this work, we present a novel intelligent transmission control model, namely DEEPCUT, to automatically adjust the message broadcasting rate of a transmitter vehicle. DEEPCUT works based on a Double Deep Q-learning Networks with Prioritized Experience Relay framework. DEEPCUT encourages the transmitter vehicle to (1) reduce its broadcasting rate if the vehicle is maintaining a safe distance from its neighbors and (2) increase the rate if the vehicle is approaching the others at a high-risk distance, all done by using reward/punish strategies. The evaluation results show that DEEPCUT can cut up 16% redundant data while increasing 22% packet reception rate compared with baseline models, particularly in crowd vehicular communications. Our risk-based transmission control can be an excellent complement to address the congestion when the channel cannot satisfy every vehicle’s resource requests. At best, the risk assessment-based approach in our congestion control method can provide a novel material to enhance Decentralized Congestion Control (DCC) for 5G V2X sidelink in the coming specifications.

Edge Based Lightweight Authentication Architecture Using Deep Learning for Vehicular Networks

<p>When vehicles are connected to the Internet through vehicle-to-everything (V2X) systems, they are exposed to diverse attacks and threats through the network connections. Vehicle-hacking attacks in the road can significantly affect driver safety. However, it is difficult to detect hacking attacks because vehicles not only have high mobility and unreliable link conditions, but they also use broadcast-based wireless communication. To this end, V2X systems need a simple but a powerful authentication procedure on the road. Therefore, this paper proposes an edge based lightweight authentication architecture using a deep learning algorithm for road safety applications in vehicle networks. The proposed lightweight authentication architecture enables vehicles that are physically separated to form a vehicular cloud in which vehicle-to-vehicle communications can be secured. In addition, an edge-based cloud data center performs deep learning algorithms to detect car hacking attempts, and then delivers the detection results to a vehicular cloud. Extensive simulations demonstrate that the proposed authentication architecture significantly enhanced the security level. The proposed authentication architecture has 94.51 to 99.8% F1-score results depending on the number of vehicles in the intrusion detection system using control area network traffic.</p> <p> </p>

A new paradigm for multi-path routing protocol for data delivery in wireless sensor networks

There are mainly two techniques in routing protocols for wireless sensor networks, single-path, and multi-path routing. Single path routing suffers from many drawbacks and limitations facing the real-time constraints and fault-tolerant applications, especially regarding time delivery of sensed data (warnings), like road safety applications, for example. Therefore, we proposed a new multi-path routing protocol based on spanning trees and a new message routing paradigm that makes single and multi-path routing easy. Simulation results show that the protocol can develop a basic infrastructure for the deliverance of timely warning data and provides fault tolerance by constructing shortest disjoint-nodes paths.

Vehicular Communications for Road Safety Applications

Computer system frameworks are more modern, similar to vehicles, taking into account that they have PC sensors and are committed to a piece of the vehicle's activity. There is a framework that is cooperative to guarantee an answer that may redesign the security in rush hour gridlock. Correspondences in vehicles are a crisis of the IT innovation that incorporates the vehicle to vehicle, vehicle to framework, vehicle to person on foot correspondence, and the vehicle to everything. Regularly, these vehicles' clients have a hefty dependence on the seat straps and airbags to defend them from any dangers during a mishap. They are like a security net that would defend the gymnastic performers in a bazaar show. The advanced methodology goes past the security nets methodologically, and we ought to battle that the vehicular correspondence networks are not there yet. On the off chance that they are probably going to be available, no trial capacity ought to be finished. There is a conviction of conceivable value of the savvy vehicle coordination that could be higher. The exhibition gauge might be secure further assessment. The innovative work and mechanical consolidation of vehicular correspondence advancements will guarantee a coordinated car innovation. The mix of vehicles' data benefits, their security, and their financial presentation will add to a wise metropolitan transportation structure.

The Utility of DSRC and V2X in Road Safety Applications and Intelligent Parking: Similarities, Differences, and the Future of Vehicular Communication.

As the technological advancement in the automotive field increases and the complexity of vehicle and infrastructure applications is extremely high, new directions and approaches are needed in this field. Supporting and developing vehicular applications dedicated to road safety by analyzing the current behavior of existing networks in various forms is imperative. This paper studies and implements a DSRC-type communications infrastructure that receives a set of controllable and adjustable indicators, which can provide messages to network drivers in a timely manner. The implementation is based on the 802.11p protocol and initially addresses pedestrian infrastructure or pedestrian safety, controlled areas, and perimeters that allow intelligent communications. The design and setting of the communication parameters in the lower layer of the DSRC stack for vehicle applications are part of this work, aspects that are also relevant in the case of autonomous vehicles.

5G-based V2V broadcast communications: A security perspective

The V2V services have been specified by the 3GPP standards body to support road safety and non-safety applications in the 5G cellular networks. It is expected to use the direct link (known as the PC5 interface), as well as the new radio interface in 5G, to provide a connectivity platform among vehicles. Particularly, vehicles will use the PC5 interface to broadcast safety messages to inform each other about potential hazards on the road. In order to function safely, robust security mechanisms are needed to ensure the authenticity of received messages and trustworthiness of message senders. These mechanisms must neither add significantly to message latency nor affect the performance of safety applications. The existing 5G-V2V standard allow protection of V2V messages to be handled by higher layer security solutions defined by other standards in the ITS domain. However having a security solution at the 5G access layer is conceivably preferable in order to ensure system compatibility and reduce deployment cost. Accordingly, the main aim of this paper is to review options for 3GPP access layer security in future 5G-V2V releases. Initially, a summary of 5G-V2V communications and corresponding service requirements is presented. An overview of the application level security standards is also given, followed by a review of the impending options to secure V2V broadcast messages at the 5G access layer. Finally, paper presents the relevant open issues and challenges on providing 3GPP access layer security solution for direct V2V communication.

The role of perceived legitimacy in understanding traffic rule compliance: A scoping review

BackgroundPerceived legitimacy associated with rules and authorities is an important element for understanding and encouraging compliance with rules in the field of road safety, often more so than with a deterrence approach. Despite a growing interest in legitimacy in recent decades and in the psychological field in particular, its definitions and measurements appear to be heterogeneous, subject to debate and in need of a common theoretical framework. Therefore, one can expect these limitations to also concern the definitions and measurements of legitimacy in the field of road safety. However, no literature review related to this issue is currently available. This contribution therefore aims to fill this void by proposing a scoping review investigating, in the field of road safety, how legitimacy is defined, measured, related to compliance and what are its main determinants. MethodsA scoping review was conducted, based on research literature from eight databases and concerned with the perceived legitimacy of traffic rules or traffic enforcement and rule compliance or traffic violations. Twenty-six publications meeting inclusion criteria were retained. The characteristics and content of publications were analyzed to identify the relevant elements related to our research questions. Results and conclusionThe main results revealed that perceived legitimacy in the field of road safety can be related to different objects (i.e., traffic rules, traffic violations, traffic enforcement, institutions) that should be better delineated and differentiated in future research. While perceived legitimacy is generally associated with compliance with traffic rules, its theoretical definitions and measures in the field of road safety are heterogeneous and present validity issues which limit the comparability of studies and so the accumulation of knowledge for both theoretical research and road safety applications. No empirical study investigating the outcomes of perceived legitimacy beyond compliance was identified. Few empirical studies have investigated the determinants of perceived legitimacy. Most identified empirical studies were cross-sectional, which is a limitation to establishing causality in investigated relationships. Theoretical implications and research perspectives to improve studies on legitimacy in the field of road safety and develop a multidimensional model of the perceived legitimacy of traffic rules are therefore proposed and discussed.

Neuroevolution-Based Adaptive Antenna Array Beamforming Scheme to Improve the V2V Communication Performance at Intersections.

The opportunistic exchange of information between vehicles can significantly contribute to reducing the occurrence of accidents and mitigating their damages. However, in urban environments, especially at intersection scenarios, obstacles such as buildings and walls block the line of sight between the transmitter and receiver, reducing the vehicular communication range and thus harming the performance of road safety applications. Furthermore, the sizes of the surrounding vehicles and weather conditions may affect the communication. This makes communications in urban V2V communication scenarios extremely difficult. Since the late notification of vehicles or incidents can lead to the loss of human lives, this paper focuses on improving urban vehicle-to-vehicle (V2V) communications at intersections by using a transmission scheme able of adapting to the surrounding environment. Therefore, we proposed a neuroevolution of augmenting topologies-based adaptive beamforming scheme to control the radiation pattern of an antenna array and thus mitigate the effects generated by shadowing in urban V2V communication at intersection scenarios. This work considered the IEEE 802.11p standard for the physical layer of the vehicular communication link. The results show that our proposal outperformed the isotropic antenna in terms of the communication range and response time, as well as other traditional machine learning approaches, such as genetic algorithms and mutation strategy-based particle swarm optimization.

Vehicular Communications Utility in Road Safety Applications: A Step toward Self-Aware Intelligent Traffic Systems

The potential of wireless technologies is significant in the area of the safety and efficiency of road transport and communications systems. The challenges and requirements imposed by end users and competent institutions demonstrate the need for viable solutions. A common protocol by which there could be vehicle-to-vehicle and vehicle-to-road communications is ideal for avoiding collisions and road accidents, all in a vehicular ad hoc network (VANET). Ways of transmitting warning messages simultaneously by vehicle-to-vehicle and vehicle-to-infrastructure communications by various multi-hop routings are set out. Approaches to how to improve communication reliability by achieving low latency are addressed through the multi-channel (MC) technique based on two non-overlaps for vehicle-to-vehicle (V2V) and vehicle-to-road (V2R) or road-to-vehicle (R2V) communications. The contributions of this paper offer an opportunity to use common communication adaptable protocols, depending on the context of the situation, coding techniques, scenarios, analysis of transfer rates, and reception of messages according to the type of protocol used. Communications between the road infrastructure and users through a relative communication protocol are highlighted and simulated in this manuscript. The results obtained by the proposed and simulated scenarios demonstrate that it is complementary and that the common node of V2V/V2R (R2V) communication protocols substantially improves the process of transmitting messages in low-latency conditions and is ideal for the development of road safety systems.