scholarly journals Studying the Simultaneous Effect of Autonomous Vehicles and Distracted Driving on Safety at Unsignalized Intersections

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Mohammad Khashayarfard ◽  
Habibollah Nassiri
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Safety Assessment ◽  
Human Error ◽  
Transportation Systems ◽  
Text Messages ◽  
Assessment Model ◽  
Driving Simulators ◽  
Time To Collision ◽  
Unsignalized Intersections

Human error is one of the leading causes of accidents. Distraction, fatigue, poor visibility, speeding, and other such errors made by drivers can cause accidents. With the rapid advancements in automation technologies, transportation planners have strived to use Intelligent Transportation Systems (ITS) to minimize human error. In this study, the effect of Autonomous Vehicles (AVs) on the number of potential conflicts at two unsignalized intersections is investigated by using a microsimulation model in PTV Vissim software. For human-driven cars, the factor that is considered for calibration is driver distraction mainly caused by reading or writing text messages on a cellphone while driving. This factor can be estimated using driving simulators. In this paper, five different scenarios were defined for simulation, in addition to the primary state, according to the different market penetration rates of AVs in Vissim. Safety assessment was performed by the Surrogate Safety Assessment Model (SSAM) using Time to Collision (TTC) and Deceleration Rate to Avoid Crashes (DRAC) indicators to determine the number of accidents. It was concluded that the presence of 100% of AVs could reduce the potential for accidents by up to 93%.

scholarly journals How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

2020 ◽  
Vol 10 (18) ◽  
pp. 6306 ◽  
Author(s):  
Luke Butler ◽  
Tan Yigitcanlar ◽  
Alexander Paz
Keyword(s):  
Conceptual Framework ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Technological Innovations ◽  
Potential Solution ◽  
Wide Range ◽  
Smart Mobility

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

scholarly journals Towards a Severity Assessment Method for Potential Cyber Attacks to Connected and Autonomous Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Qiyi He ◽  
Xiaolin Meng ◽  
Rong Qu
Keyword(s):  
Cyber Security ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Assessment Method ◽  
Transportation Systems ◽  
Cyber Attacks ◽  
Large Set ◽  
Security Attacks ◽  
Physical Damage

CAV (connected and autonomous vehicle) is a crucial part of intelligent transportation systems. CAVs utilize both sensors and communication components to make driving decisions. A large number of companies, research organizations, and governments have researched extensively on the development of CAVs. The increasing number of autonomous and connected functions however means that CAVs are exposed to more cyber security vulnerabilities. Unlike computer cyber security attacks, cyber attacks to CAVs could lead to not only information leakage but also physical damage. According to the UK CAV Cyber Security Principles, preventing CAVs from cyber security attacks need to be considered at the beginning of CAV development. In this paper, a large set of potential cyber attacks are collected and investigated from the aspects of target assets, risks, and consequences. Severity of each type of attacks is then analysed based on clearly defined new set of criteria. The levels of severity for the attacks can be categorized as critical, important, moderate, and minor. Mitigation methods including prevention, reduction, transference, acceptance, and contingency are then suggested. It is found that remote control, fake vision on cameras, hidden objects to LiDAR and Radar, spoofing attack to GNSS, and fake identity in cloud authority are the most dangerous and of the highest vulnerabilities in CAV cyber security.

scholarly journals Evaluating the Safety Impact of Connected and Autonomous Vehicles with Lane Management on Freeway Crash Hotspots Using the Surrogate Safety Assessment Model

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hui Zhang ◽  
Ninghao Hou ◽  
Jianhua Zhang ◽  
Xuyi Li ◽  
Yan Huang
Keyword(s):  
Traffic Safety ◽  
Autonomous Vehicles ◽  
Safety Assessment ◽  
Assessment Model ◽  
Trajectory Data ◽  
Collision Risk ◽  
Velocity Difference ◽  
Safety Benefit ◽  
Crash Hotspots ◽  
The Impact

One goal for large-scale deployment of connected and autonomous vehicles is to achieve the traffic safety benefit since connected and autonomous vehicles (CAVs) could reduce the collision risk by enhancing the driver’s situation perception ability. Previous studies have analyzed the safety impact of CAVs involved in traffic, but only few studies examined the safety benefits brought by CAVs when approaching high-collision-risk road segments such as the freeway crash hotspots. This study chooses one freeway crash hotspot in Wuhan, China, as an instance and attempts to estimate the safety benefits for differential penetration rates (PRs) of CAVs using the surrogate safety assessment model (SSAM). First, the freeway crash hotspot is identified with kernel density estimation and simulated by VISSIM. Then, the intelligent driver model (IDM) and Wiedemann 99 (a car-following model) are adopted and calibrated to control the driving behaviors of CAVs and human-driven vehicles (HVs) in this study, respectively. The impact that rather CAVs are constrained with or without managed lanes on traffic safety is also discussed, and the PR of CAVs is set from 10% to 90%. The results of this study show that when the PR of CAVs is lower than 50%, there is no significant improvement on the safety measures such as conflicts, acceleration, and velocity difference, which are extracted from the vehicle trajectory data using SSAM. When the penetration rate is over 70%, the experiment results demonstrate that the traffic flow passing the freeway hotspot is with fewer conflicts, smaller acceleration, and smaller velocity difference in the scenario where CAVs are constrained with managed lane compared with the scenario without managed lane control. The safety benefit that CAVs bring needs to be discussed. The lane management of CAVs will also lead to distinct safety impact.

Driving Simulators: Are They Valid Test Environments for ITS Development?

1997 ◽  
Vol 41 (2) ◽  
pp. 926-928 ◽  
Author(s):  
Robert A. Glaser ◽  
Donald L. Fisher
Keyword(s):  
Intelligent Transportation Systems ◽  
Driving Simulator ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Driving Simulators ◽  
Valid Test ◽  
University Of Massachusetts ◽  
The University ◽  
Serious Injuries

Driving simulators are increasingly being used to test the Intelligent Transportation Systems (ITS) that interface with the driver in the vehicle. Examples of such technologies include autonomous, on-board sensors (Huguenin, 1993) which potentially can prevent many of the rear-end crashes that lead to fatalities or serious injuries (Knipling, Mironer, Hendricks, Tijerin, Everson, Allen and Wilson, 1993). A study of the simulator image factors which affect the detection of rear-end collisions and, more generally, of motion is described below. The study was undertaken on the University of Massachusetts driving simulator located at the Amherst campus.

Intelligent transportation system for sustainable environment in smart cities

2021 ◽  
pp. 002072092098350
Author(s):  
Liang Zhao ◽  
Yuanhua Jia
Keyword(s):  
Environmental Sustainability ◽  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Advanced Technology ◽  
Toxic Substances ◽  
Sustainable Environment

Advanced technology has ushered in the urge to enhance the travel experience. Besides the consistent desire to travel faster and more comfortably, the need to ensure transportation sustainability has remained constant. Smart cities employ top-grade technological applications to facilitate operations. Intelligent transportation systems involve the use of advanced transportation technologies. Through the integration of the Internet of Vehicles, cars in traffic can send and receive data between themselves and other vehicles and the environment. This data is processed to ensure efficient transportation by controlling traffic flows and preventing accidents. In this study, a literature review is conducted on how intelligent transportation systems contribute to environmental sustainability in smart cities. With technologies such as electricity-driven cars and autonomous vehicles, the systems minimize the emission of toxic substances to the environment while enhancing the interaction of the car with its surroundings to avoid accidents.

scholarly journals Integration of Blockchain with Connected and Autonomous Vehicles: Vision and Challenge

2022 ◽  
Vol 14 (1) ◽  
pp. 1-10
Author(s):  
Tooska Dargahi ◽  
Hossein Ahmadvand ◽  
Mansour Naser Alraja ◽  
Chia-Mu Yu
Keyword(s):  
Data Protection ◽  
Intelligent Transportation Systems ◽  
Data Security ◽  
Autonomous Vehicles ◽  
Personal Data ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Blockchain Technology ◽  
Wide Range

Connected and Autonomous Vehicles (CAVs) are introduced to improve individuals’ quality of life by offering a wide range of services. They collect a huge amount of data and exchange them with each other and the infrastructure. The collected data usually includes sensitive information about the users and the surrounding environment. Therefore, data security and privacy are among the main challenges in this industry. Blockchain, an emerging distributed ledger, has been considered by the research community as a potential solution for enhancing data security, integrity, and transparency in Intelligent Transportation Systems (ITS). However, despite the emphasis of governments on the transparency of personal data protection practices, CAV stakeholders have not been successful in communicating appropriate information with the end users regarding the procedure of collecting, storing, and processing their personal data, as well as the data ownership. This article provides a vision of the opportunities and challenges of adopting blockchain in ITS from the “data transparency” and “privacy” perspective. The main aim is to answer the following questions: (1) Considering the amount of personal data collected by the CAVs, such as location, how would the integration of blockchain technology affect transparency , fairness , and lawfulness of personal data processing concerning the data subjects (as this is one of the main principles in the existing data protection regulations)? (2) How can the trade-off between transparency and privacy be addressed in blockchain-based ITS use cases?

scholarly journals Comparison of Different Clustering Algorithms to Secured VANETs Communication

2021 ◽  
pp. 59-75
Author(s):  
Prashant Kumar Shrivastava ◽  
Dr. L. K. Vishwamitra
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Data Dissemination ◽  
New Technology ◽  
Clustering Algorithms ◽  
Transportation Systems ◽  
Vehicular Communication ◽  
Smart Vehicles

ITS (Intelligent Transportation Systems) are growing increasingly popular because of the necessity for superior cyber-physical systems and comfort applications and services required for usage in autonomous vehicles. There are two types of Vehicular Ad-Hoc Networks (VANETs) that are vital to ITS: V2I (Vehicle-to-Infrastructure) and V2V (Vehicle-to-Vehicle). VANETs are a new technology with several potential uses in the ITS. It comprises smart vehicles and roadside equipment that connect over open-access wireless networks. An attacker may disrupt vehicular communication which can lead to potentially life-threatening scenarios because of the significant expansion in the number of vehicles in use today. VANETs must use robust security and authentication procedures to provide safe vehicular communication. This paper provides a comprehensive analysis ofthe VANET system including its characteristics and challenges. There is a concept of data dissemination that has been provided in brief. Clustering is the most important topic in VANET that is used to cluster the vehicles to secure and safely message transmission over the network. There is a taxonomy of clustering techniques has provided in a detailed manner. Besides, it has also shown the comparison of different clustering parameters-based mechanisms and MAC protocols in VANET.

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 Software-Defined Heterogeneous Vehicular Networking: The Architectural Design and Open Challenges

2019 ◽  
Vol 11 (3) ◽  
pp. 70 ◽  
Author(s):  
Adnan Mahmood ◽  
Wei Zhang ◽  
Quan Sheng
Keyword(s):  
Intelligent Transportation Systems ◽  
Autonomous Vehicles ◽  
Traffic Management ◽  
Architectural Design ◽  
Transportation Systems ◽  
Safety Critical ◽  
Vehicular Networking ◽  
Performance Requirements ◽  
Radio Access ◽  
Stringent Performance

The promising advancements in the telecommunications and automotive sectors over the years have empowered drivers with highly innovative communication and sensing capabilities, in turn paving the way for the next-generation connected and autonomous vehicles. Today, vehicles communicate wirelessly with other vehicles and vulnerable pedestrians in their immediate vicinity to share timely safety-critical information primarily for collision mitigation. Furthermore, vehicles connect with the traffic management entities via their supporting network infrastructure to become more aware of any potential hazards on the roads and for guidance pertinent to their current and anticipated speeds and travelling course to ensure more efficient traffic flows. Therefore, a secure and low-latency communication is highly indispensable in order to meet the stringent performance requirements of such safety-critical vehicular applications. However, the heterogeneity of diverse radio access technologies and inflexibility in their deployment results in network fragmentation and inefficient resource utilization, and these, therefore, act as bottlenecks in realizing the aims for a highly efficient vehicular networking architecture. In order to overcome such sorts of bottlenecks, this article brings forth the current state-of-the-art in the context of intelligent transportation systems (ITS) and subsequently proposes a software-defined heterogeneous vehicular networking (SDHVNet) architecture for ensuring a highly agile networking infrastructure to ensure rapid network innovation on-demand. Finally, a number of potential architectural challenges and their probable solutions are discussed.

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