scholarly journals Traffic Accidents with Autonomous Vehicles: Type of Collisions, Manoeuvres and Errors of Conventional Vehicles’ Drivers

2020 ◽  
Vol 45 ◽  
pp. 161-168
Author(s):  
Đorđe Petrović ◽  
Radomir Mijailović ◽  
Dalibor Pešić
Keyword(s):  
Autonomous Vehicles ◽  
Traffic Accidents

scholarly journals Risk analysis for forecasting cyberattacks against connected and autonomous vehicles

2021 ◽  
Author(s):  
Sunniva F. Meyer ◽  
Rune Elvik ◽  
Espen Johnsson
Keyword(s):  
Risk Analysis ◽  
Transport System ◽  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Domestic Abuse ◽  
Connected Vehicles ◽  
Security Risk ◽  
Safety Measures

AbstractA security risk analysis was conducted to identify possible cyberattacks against a future transport system consisting of autonomous and connected vehicles. Six scenarios were developed: joyriding, kidnapping, domestic abuse, autopilot manipulation, a large transport accident, and paralysis of the transport system. Even if it were possible to increase the difficulty of conducting such cyberattacks, it might be impossible to eliminate such attacks entirely. Measures that limit the consequences will therefore be necessary. Such measures include safety measures in vehicles to protect their occupants in traffic accidents and measures that make vehicles easier to remove in case they do not function.

scholarly journals Threats and Alert Analytics in Autonomous Vehicles

10.29007/j6h1 ◽  
2020 ◽  
Author(s):  
Aakanksha Rastogi ◽  
Kendall Nygard
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Driver Assistance ◽  
Driving Experience ◽  
Vehicle To Vehicle ◽  
Hoc Networks ◽  
Self Driving Cars

Autonomous vehicles or self-driving cars emerged with a promise to deliver a driving experience that is safe, secure, law-abiding, alleviates traffic congestion and reduces traffic accidents. These self-driving cars predominantly rely on wireless technology, vehicular ad-hoc networks (VANETs) and Vehicle to Vehicle (V2V) networks, Road Side Units (RSUs), Millimeter Wave radars, light detection and ranging (LiDAR), sensors and cameras, etc. Since these vehicles are so dexterous and equipped with such advanced driver assistance technological features, their dexterity invites threats, vulnerabilities and hacking attacks. This paper aims to understand and study the technology behind these self-driving cars and explore, identify and address popular threats, vulnerabilities and hacking attacks to which these cars are prone. This paper also establishes a relationship between these threats, trust and reliability. An analysis of the alert systems in self-driving cars is also presented.

scholarly journals CHILD SAFETY IN AUTONOMOUS VEHICLES: "LIVING ROOM" LAYOUT

10.6036/10215 ◽  
2022 ◽  
Vol 97 (1) ◽  
pp. 30-34
Author(s):  
Mónica Diez Marín ◽  
JULIO ABAJO ALONSO ◽  
ALBERTO NEGRO MARNE ◽  
SUSANA MARIA ESCALANTE CASTRODEZA ◽  
MARIA TERESA FERNANDEZ
Keyword(s):  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Child Safety ◽  
Living Room ◽  
Human Body Model ◽  
Test Protocol ◽  
Occupant Safety ◽  
Passenger Safety ◽  
Seating Position ◽  
Child Occupant

Autonomous vehicles start to be introduced on our roads and will soon become a reality. Although fatal traffic accidents will be significantly reduced, remaining fatal passenger car crashes should be taken into account to ensure the safety of users. The new highly adaptable interior designs, with totally different layouts from the current ones, may significantly impact occupant safety, especially child passenger safety. Analyzing how these new vehicles affect child safety is a challenge that needs to be addressed. The "living room" layout (face-to-face seating position) is one of the preferences of families traveling with children. Young children need further support and supervision so the possibility of rotating seats to be able to be in front of the small children is a valuable feature for parents. Therefore, new seating orientations away from the forward facing position should be taken into account to ensure children protection. The objective of this study is to evaluate child occupant safety in a "living room" seating position (a possible option in full autonomous vehicles) versus the current forward facing position. Virtual testing methodology was used to perform this study. The virtual PIPER child human body model (HBM) was used. This model is one of the only HBMs developed and validated from child PMHS data (Paediatric Post-Mortem Human Surrogate). The two configurations were defined according with the EuroNCAP child occupant protection test protocol. It was found that the "living room" layout presents worse results according to the child's head injury patterns than in forward facing position. In conclusion, attending to the new seating orientations away from the forward facing position, it is necessary to adapt the restraint systems; otherwise children could suffer potentially dangerous situations.

Design Guidelines on Deep Learning–based Pedestrian Detection Methods for Supporting Autonomous Vehicles

2021 ◽  
Vol 54 (6) ◽  
pp. 1-36
Author(s):  
Azzedine Boukerche ◽  
Mingzhi Sha
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Pedestrian Detection ◽  
Transportation Systems ◽  
Design Guidelines ◽  
Detection Methods ◽  
Multi Scale ◽  
Present Design

Intelligent transportation systems (ITS) enable transportation participants to communicate with each other by sending and receiving messages, so that they can be aware of their surroundings and facilitate efficient transportation through better decision making. As an important part of ITS, autonomous vehicles can bring massive benefits by reducing traffic accidents. Correspondingly, much effort has been paid to the task of pedestrian detection, which is a fundamental task for supporting autonomous vehicles. With the progress of computational power in recent years, adopting deep learning–based methods has become a trend for improving the performance of pedestrian detection. In this article, we present design guidelines on deep learning–based pedestrian detection methods for supporting autonomous vehicles. First, we will introduce classic backbone models and frameworks, and we will analyze the inherent attributes of pedestrian detection. Then, we will illustrate and analyze representative pedestrian detectors from occlusion handling, multi-scale feature extraction, multi-perspective data utilization, and hard negatives handling these four aspects. Last, we will discuss the developments and trends in this area, followed by some open challenges.

scholarly journals Skid resistance demands of asphalt pavement during the braking process of autonomous vehicles

2019 ◽  
Vol 275 ◽  
pp. 04002
Author(s):  
Zheng Binshuang ◽  
Chen Jiaying ◽  
Zhao Runmin ◽  
Huang Xiaoming
Keyword(s):  
Traffic Safety ◽  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Asphalt Pavement ◽  
Practical Significance ◽  
Skid Resistance ◽  
Safe Driving ◽  
Emergency Braking ◽  
Braking Distance ◽  
Technical Specifications

As the main operationality of AVs, the braking property is directly related to traffic safety. Major traffic accidents are often related to the braking distance, the side slip and hydroplaning during the emergency braking, which depends on the pavement skid resistance. Therefore, the estimation to relate AVs braking distance requirements with pavement peak friction coefficient to ensure a safe driving condition on expressway is of high practical significance. In this paper, the effect of AVs on braking performance parameters and dynamic friction on tire-pavement interaction are investigated. Based on the field test of the Coastal highway in Jiangsu province of China, this paper proposes an algorithm to determine time-dependent braking distance of AVs considering pavement frictional properties. According to the algorithm, an AVs braking system is provided to reach the maximum braking force for improving the AVs traffic safety. Furthermore, it revises the braking distance formula of Design Specification for Highway Alignment and the skid resistance threshold adopted by Technical Specifications for Maintenance of Highway Asphalt Pavement.

scholarly journals Simulation of AEBS Applicability by Changing Radar Detection Angle

2021 ◽  
Vol 11 (5) ◽  
pp. 2305
Author(s):  
Yongsoon Choi ◽  
Seryong Baek ◽  
Cheonho Kim ◽  
Junkyu Yoon ◽  
Seongkwan Mark Lee
Keyword(s):  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Smart Cities ◽  
Autonomous Driving ◽  
Radar Detection ◽  
Safe Driving ◽  
Euro Ncap ◽  
Test Standards ◽  
Emergency Braking ◽  
Crash Avoidance

As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.

scholarly journals Development Strategies of Autonomous Vehicles in Taiwan

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Huey-Wen Chou ◽  
Chien-Hung Chao
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Industrial Development ◽  
Traffic Accidents ◽  
World Market ◽  
Driver Assistance Systems ◽  
Potential Market ◽  
Information And Communication ◽  
Near Future ◽  
Parking Demand

Autonomous vehicles can reduce traffic accidents, traffic congestion and parking demand and hence have great potential to become a major transportation mode in the near future. The potential market for autonomous vehicles is huge. Therefore, it is a necessity to develop strategies so as to outperform in this highly competitive world market. This research employs SWOT method to generate 14 criteria for the development of autonomous vehicles. Then, a decision-making method called “Decision Making and Trial Evaluation Laboratory-based Analytic Network Process” (DANP) is used to prioritize these criteria. Results show that two criteria that are strengths–Advanced Driver Assistance Systems (ADAS) and complete supply chain of Information and Communication Technology (ICT ) – should be treated with priority and another criterion – lack of own auto-brand and first-tier supplier – is not the focus. The result is fully coincident with the real situation of industrial development in Taiwan and can be a good reference for Taiwan’s government.

scholarly journals Law Applicable to Liability for Damages due to Traffic Accidents Involving Autonomous Vehicles

2020 ◽  
Vol 14 (2) ◽  
pp. 177-200
Author(s):  
Marek Swierczynski ◽  
Łukasz Żarnowiec
Keyword(s):  
Artificial Intelligence ◽  
International Law ◽  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Legal Framework ◽  
Private International Law ◽  
New Approach ◽  
Conflict Of Laws ◽  
Individual Consideration ◽  
The Law

The authors examine the problem of the law applicable to liability for damages due to traffic accidents involving autonomous vehicles. Existing conflict-of-laws regulation adopted in the Rome II Regulation and both Hague Conventions of 1971 and 1973 is criticized. Upon examination of these legal instruments, it becomes clear that existing regulation is very complex and complicated. In effect authors recommend revisions to the legal framework. Proposed solutions are balanced and take into consideration both the interests of the injured persons, as well the persons claimed to be liable. New approach allows for more individual consideration of specific cases and direct to better outcome of the disputes. The findings may be useful in handling the cases related to use of algorithms of artificial intelligence in private international law.

scholarly journals Sight distances at unsignalized intersections: a comparison of guidelines and requirements for human drivers and autonomous vehicles

2021 ◽  
Vol 59 (3) ◽  
pp. 7-19
Author(s):  
Zsófia Magyari ◽  
Csaba Koren ◽  
Mariusz Kieć ◽  
Attila Borsos
Keyword(s):  
Autonomous Vehicles ◽  
Traffic Accidents ◽  
Human Vision ◽  
Design Parameters ◽  
Major Road ◽  
Gap Acceptance ◽  
Human Capabilities ◽  
Road Design ◽  
Unsignalized Intersections ◽  
Minor Road

Many traffic accidents are caused by unforeseen and unexpected events in a site that was hidden from the driver's eyes. Road design parameters determining required visibility are based on relationships formulated decades ago. It is worth reviewing them from time to time in the light of technological developments. In this paper, sight distances for stopping and crossing situations are studied in relation to the assumed visual abilities of autonomous vehicles. Current sight distance requirements at unsignalized intersections are based among others on speeds on the major road and on ac-cepted gaps by human drivers entering or crossing from the minor road. Since these requirements vary from country to country, regulations and sight terms of a few selected countries are compared in this study. From the comparison it is remarkable that although the two concepts, i.e. gap acceptance on the minor road and stopping on the major road have different backgrounds, but their outcome in terms of required sight distances are similar. Both distances are depending on speed on the major road: gap sight distances show a linear, while stopping sight distances a parabolic function. In general, European SSD values are quite similar to each other. However, the US and Australian guidelines based on gap acceptance criteria recommend higher sight distances. Human capabilities and limitations are considered in sight field requirements. Autonomous vehicles survey their environment with sensors which are different from the human vision in terms of identifying objects, estimating distances or speeds of other vehicles. This paper compares current sight field requirements based on conventional vehicles and those required for autonomous vehicles. Visibility requirements were defined by three vision indicators: distance, angle of view and resolution abilities of autonomous cars and human drivers. These indicators were calculated separately for autonomous vehicles and human drivers for various speeds on the main road and for intersections with 90° and 60° angles. It was shown that the required sight distances are 10 to 40 meters shorter for autonomous vehicles than for conventional ones.

scholarly journals Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

2020 ◽  
Vol 17 (12) ◽  
pp. 4419 ◽  
Author(s):  
Kum Fai Yuen ◽  
Grace Chua ◽  
Xueqin Wang ◽  
Fei Ma ◽  
Kevin X. Li
Keyword(s):  
Autonomous Vehicles ◽  
Structural Equation ◽  
Traffic Accidents ◽  
Theory Of Planned Behaviour ◽  
Cumulative Effect ◽  
Relative Advantage ◽  
Public Acceptance ◽  
Infrastructure Development ◽  
Planned Behaviour ◽  
Marketing Education

Public acceptance of autonomous vehicles (AVs) is vital for a society to reap their intended benefits such as reduced traffic accidents, land usage, congestion and environmental pollution. The purpose of this paper is to use the theory of planned behaviour to pinpoint and examine the components affecting public acceptance of AVs. A model consisting of a network of hypothesised relationships is introduced. Thereafter, 526 residents in Seoul, Korea, were given a survey created for this research. Subsequently, to evaluate the collected information and estimate the model, structural equation modelling was adopted. The outcomes show individuals’ mindset on AVs, subjective customs, and behavioural influence directly influencing the acceptance of AVs. Furthermore, cognitive and emotive factors, namely comparative advantage, compatibility, complexity and hedonic motivation indirectly influence the acceptance of AVs via mindset and behavioural manipulation. Based on analysing the cumulative effect, attitude emerged with the strongest effect on public acceptance of autonomous vehicles. After this is, in decreasing order of influence, behavioural control, relative advantage, subjective norms, compatibility, hedonic motivation and complexity. The findings of this study implicate the prioritisation and allocation of resources, and policies relating to marketing, education, subsidisation and infrastructure development to better public acceptance of AVs.

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