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"Automated vehicles Security measures."
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Awake at the wheel: how auto technology innovations present ongoing sleep challenges and new safety opportunities
Abstract
Individuals and society are dependent on transportation. Individuals move about their world for work, school, healthcare, social activities, religious and athletic events, and so much more. Society requires the movement of goods, food, medicine, etc. for basic needs, commerce, cultural and political exchanges, and all of its dynamic, complex elements. To meet these critical daily demands, the transportation system operates globally and around the clock. Regardless of their role, a basic requirement for the individuals operating the transportation system is that they are awake and at optimal alertness. This applies to individuals driving their own cars, riding a bike or motorcycle, as well as pilots of commercial aircraft, train engineers, long-haul truck drivers, and air traffic controllers. Alert operators are a basic requirement for a safe and effective transportation system. Decades of scientific and operational research have demonstrated that the 24/7 scheduling demands on operators and passengers of our transportation system create sleep and circadian disruptions that reduce alertness and performance and cause serious safety problems. These challenges underly the longstanding interest in transportation safety by the sleep and circadian scientific community. An area currently offering perhaps the most significant opportunities and challenges in transportation safety involves vehicle technology innovations. This paper provides an overview of these latest innovations with a focus on sleep-relevant issues and opportunities. Drowsy driving is discussed, along with fatigue management in round-the-clock transportation operations. Examples of cases where technology innovations could improve or complicate sleep issues are discussed, and ongoing sleep challenges and new safety opportunities are considered.
Journal Article
A Methodological Framework to Assess Road Infrastructure Safety and Performance Efficiency in the Transition toward Cooperative Driving
There is increasing interest in connected and automated vehicles (CAVs), since their implementation will transform the nature of transportation and promote social and economic change. Transition toward cooperative driving still requires the understanding of some key questions to assess the performances of CAVs and human-driven vehicles on roundabouts and to properly balance road safety and traffic efficiency requirements. In this view, this paper proposes a simulation-based methodological framework aiming to assess the presence of increasing proportions of CAVs on roundabouts operating at a high-capacity utilization level. A roundabout was identified in Palermo City, Italy, and built in Aimsun (version 20) to describe the stepwise methodology. The CAV-based curves of capacity by entry mechanism were developed and then used as target capacities. To calibrate the model parameters, the capacity curves were compared with the capacity data simulated by Aimsun. The impact on the safety and performance efficiency of a lane dedicated to CAVs was also examined using surrogate measures of safety. The paper ends with highlighting a general improvement with CAVs on roundabouts, and with providing some insights to assess the advantages of the automated and connected driving technologies in transitioning to smarter mobility.
Journal Article
Hacking Connected Cars
A field manual on contextualizing cyber threats, vulnerabilities, and risks to connected cars through penetration testing and risk assessment Hacking Connected Cars deconstructs the tactics, techniques, and procedures (TTPs) used to hack into connected cars and autonomous vehicles to help you identify and mitigate vulnerabilities affecting.
eBook
Safety evaluation via conflict classification during automated shuttle bus service operations
The widespread adoption of Connected and Automated Vehicles (CAVs) is being propelled, not only in the realm of private vehicles but also within transit systems. This development serves to enhance urban transport activities, rendering transportation more appealing to passengers. The present study aims to identify and examine the safety effects of testing different operational speed shuttle bus services in various future mobility conditions. To investigate impacts of autonomous shuttle bus services and to further examine their operational speed, the microscopic simulation method was performed. Specifically, four sets of simulation scenarios were comprised: a baseline scenario representing the current conditions and three operational speed scenarios (15 km/h, 30 km/h and 45 km/h) for an autonomous shuttle service. Each one of these sets included eleven CAV market penetration rates (MPRs) of CAVs of the general traffic (ranging from 0 to 100% in 10% increments). By analyzing the trajectory data extracted from microsimulation, traffic conflicts were identified and further analyzed by developing Mixed-Effects Multinomial Logit Regression models (ME-MLMs) in order to associate conflict type taking into account network characteristics as well as traffic conditions. Several aspects were determined as statistical significant parameters influencing type of conflict. The analysis yielded several significant findings that provide quantitative measurements and assessments of the effects observed, enabling a better understanding of the safety implications associated with the widespread adoption of automated services.
Journal Article
Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors
This paper presents a vehicle autonomous localization method in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. Barcode tags are deployed in pairs on both sides of the tunnel walls at certain intervals as artificial landmarks. The barcode coding is designed based on UPC-A code. The global coordinates of the upper left inner corner point of the feature frame of each barcode tag deployed in the tunnel are uniquely represented by the barcode. Two on-board vision sensors are used to recognize each pair of barcode tags on both sides of the tunnel walls. The distance between the upper left inner corner point of the feature frame of each barcode tag and the vehicle center point can be determined by using a visual distance projection model. The on-board ultrasonic sensors are used to measure the distance from the vehicle center point to the left side of the tunnel walls. Once the spatial geometric relationship between the barcode tags and the vehicle center point is established, the 3D coordinates of the vehicle center point in the tunnel's global coordinate system can be calculated. Experiments on a straight corridor and an underground tunnel have shown that the proposed vehicle autonomous localization method is not only able to quickly recognize the barcode tags affixed to the tunnel walls, but also has relatively small average localization errors in the vehicle center point's plane and vertical coordinates to meet autonomous unmanned vehicle positioning requirements in local area of coal mine tunnel.
Journal Article
Law and tech collide: foreseeability, reasonableness and advanced driver assistance systems
Recently, many scholars have explored the legal challenges likely to be posed by introduction of automated and autonomous vehicles. Minimal attention has focused on the legal implications of advanced driver assistance systems (ADAS) in vehicles already currently available. These can warn of external dangers, monitor driver behavior and control how a vehicle brakes, accelerates, maintains speed or position on the road. The dynamic driving task is no longer reliant simply on the physical interaction of human driver with that vehicle. Instead, the vehicle may act apart from human direction as it senses other objects in the immediate environment or monitors the human driver's behavior or biometrics. These technological tools, which reduce the opportunity for human error, can be described as augmenting human driving capacity. Increases in safety promised by ADAS, arguably already evidenced by data, may require a reassessment of the risks posed by 'un-augmented' human drivers, what is now foreseeable given the data generated by ADAS and wearable driver-monitoring technology, and whether 'un-augmented' driving is any longer a reasonable response to that risk.
Journal Article
Efficient Multi-Layer Credential Revocation Scheme for 6G Using Dynamic RSA Accumulators and Blockchain
As a new generation of mobile communication networks, 6G security faces many new security challenges. Vehicle to Everything (V2X) will be an important part of 6G. In V2X, connected and automated vehicles (CAVs) need to frequently share data with other vehicles and infrastructures. Therefore, identity revocation technology in the authentication is an important way to secure CAVs and other 6G scenario applications. This paper proposes an efficient credential revocation scheme with a four-layer architecture. First, a rapid pre-filtration layer is constructed based on the cuckoo filter, responsible for the initial screening of credentials. Secondly, a directed routing layer and the precision judgement layer are designed based on the consistency hash and the dynamic RSA accumulator. By proposing the dynamic expansion of the RSA accumulator and load-balancing algorithm, a smaller and more stable revocation delay can be achieved when many users and terminal devices access 6G. Finally, a trusted storage layer is built based on the blockchain, and the key revocation parameters are uploaded to the blockchain to achieve a tamper-proof revocation mechanism and trusted data traceability. Based on this architecture, this paper also proposes a detailed identity credential revocation and verification process. Compared to existing solutions, this paper’s solution has a combined average improvement of 59.14% in the performance of the latency of the cancellation of the inspection, and the system has excellent load balancing, with a standard deviation of only 11.62, and the maximum deviation is controlled within the range of ±4%.
Journal Article
Can Shared Control Improve Overtaking Performance? Combining Human and Automation Strengths for a Safer Maneuver
The Shared Control (SC) cooperation scheme, where the driver and automated driving system control the vehicle together, has been gaining attention through the years as a promising option to improve road safety. As a result, advanced interaction methods can be investigated to enhance user experience, acceptance, and trust. Under this perspective, not only the development of algorithms and system applications are needed, but it is also essential to evaluate the system with real drivers, assess its impact on road safety, and understand how drivers accept and are willing to use this technology. In this sense, the contribution of this work is to conduct an experimental study to evaluate if a previously developed shared control system can improve overtaking performance on roads with oncoming traffic. The evaluation is performed in a Driver-in-the-Loop (DiL) simulator with 13 real drivers. The system based on SC is compared against a vehicle with conventional SAE-L2 functionalities. The evaluation includes both objective and subjective assessments. Results show that SC proved to be the best solution for assisting the driver during overtaking in terms of safety and acceptance. The SC’s longer and smoother control transitions provide benefits to cooperative driving. The System Usability Scale (SUS) and the System Acceptance Scale (SAS) questionnaire show that the SC system was perceived as better in terms of usability, usefulness, and satisfaction.
Journal Article
Enhancing Intrusion Detection in Autonomous Vehicles Using Ontology-Driven Mitigation
With the increasing complexity of Autonomous Vehicle networks, enhanced cyber security has become a critical challenge. Traditional security techniques often struggle to adapt dynamically to evolving threats. Overcoming these limitations, this paper presents a novel domain ontology to structure knowledge concerning AV security threats, intrusion characteristics, and corresponding mitigation techniques. Unlike previous work, which mainly focused on static classifications or direct integration within Intrusion Detection Systems, our approach has the distinctive feature of creating a formalized and coherent semantic representation. The ontology was designed using Protégé 4.3 and Web Ontology Language (OWL), modeled from the core cyber security concepts of AVs, and it provides a more nuanced threat classification and significantly superior automated reasoning capability. An important feature of our design is that the ontology formalization was done independently of any real-time IDS integration. A PoC was carried out to prove that the ontology could select the most appropriate method of mitigation, using as input the output of machine-learning-based IDS; SPARQL queries retrieve mitigation instance, type, and effectiveness. This design choice enables us to concentrate strictly on validating the foundational semantic coherence and reasoning power of the knowledge structure, hence providing a robust and reliable analytical framework for further reactive and predictive security applications. The experimental evaluation confirms enhanced effectiveness in knowledge organization and reduces inconsistencies in security threat analysis. Specifically, class classification was performed in 1.049 s, while consistency check required just 0.044 s, hence validating the model’s robustness against classification principles and concept inferences. This work thus paves the way for the development of more intelligent and adaptive security frameworks. In the future, research will be focused on the integration with real-time security monitoring and IDS frameworks and on the study of optimization techniques, such as genetic algorithms, to improve the real-time selection of the countermeasures.
Journal Article