How many crashes can connected vehicle and automated vehicle technologies prevent: A meta-analysis

2020 ◽  
Vol 136 ◽  
pp. 105299 ◽  
Author(s):  
Ling Wang ◽  
Hao Zhong ◽  
Wanjing Ma ◽  
Mohamed Abdel-Aty ◽  
Juneyoung Park
Keyword(s):  
Meta Analysis ◽  
Connected Vehicle ◽  
Automated Vehicle ◽  
Vehicle Technologies

scholarly journals Safety improvements by intelligent connected vehicle technologies: A meta-analysis considering market penetration rates

2021 ◽  
Vol 159 ◽  
pp. 106234
Author(s):  
Guiming Xiao ◽  
Jaeyoung Lee ◽  
Qianshan Jiang ◽  
Helai Huang ◽  
Mohamed Abdel-Aty ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Vehicle Technologies

Unsettled Topics Concerning the Impact of Quantum Technologies on Automotive Cybersecurity

2020 ◽  
Author(s):  
Joachim Taiber ◽  
Keyword(s):  
Quantum Computing ◽  
Quantum Cryptography ◽  
Research Report ◽  
Quantum Computers ◽  
Encrypted Data ◽  
Automated Vehicle ◽  
Vehicle Technologies ◽  
Post Quantum Cryptography ◽  
Vehicle Sensors ◽  
The Impact

Quantum computing is considered the “next big thing” when it comes to solving computational problems impossible to tackle using conventional computers. However, a major concern is that quantum computers could be used to crack current cryptographic schemes designed to withstand traditional cyberattacks. This threat also impacts future automated vehicles as they become embedded in a vehicle-to-everything (V2X) ecosystem. In this scenario, encrypted data is transmitted between a complex network of cloud-based data servers, vehicle-based data servers, and vehicle sensors and controllers. While the vehicle hardware ages, the software enabling V2X interactions will be updated multiple times. It is essential to make the V2X ecosystem quantum-safe through use of “post-quantum cryptography” as well other applicable quantum technologies. This SAE EDGE™ Research Report considers the following three areas to be unsettled questions in the V2X ecosystem: How soon will quantum computing pose a threat to connected and automated vehicle technologies? What steps and measures are needed to make a V2X ecosystem “quantum-safe?” What standardization is needed to ensure that quantum technologies do not pose an unacceptable risk from an automotive cybersecurity perspective?

scholarly journals Modelling Uptake Sensitivities of Connected and Automated Vehicle Technologies

2021 ◽  
Vol 10 (2) ◽  
pp. 88-106
Author(s):  
Gillian Harrison ◽  
Simon P. Shepherd ◽  
Haibo Chen
Keyword(s):  
Internet Of Things ◽  
Dynamic Modelling ◽  
Transport Systems ◽  
The Internet ◽  
Sensitivity Testing ◽  
Automated Vehicle ◽  
Vehicle Technologies ◽  
The Internet Of Things

Connected and automated vehicle (CAV) technologies and services are rapidly developing and have the potential to revolutionise the transport systems. However, like many innovations, the uptake pathways are uncertain. The focus of this article is on improving understanding of factors that may affect the uptake of highly and fully automated vehicles, with a particular interest in the role of the internet of things (IoT). Using system dynamic modelling, sensitivity testing towards vehicle attributes (e.g., comfort, safety, familiarity) is carried out and scenarios were developed to explore how CAV uptake can vary under different conditions based around the quality of IoT provision. Utility and poor IoT are found to have the biggest influence. Attention is then given to CAV ‘services' that are characterized by the attributes explored earlier in the paper, and it is found that they could contribute to a 20% increase in market share.

User Acceptance and Willingness to Pay for Connected Vehicle Technologies: Adaptive Choice-Based Conjoint Analysis

2015 ◽  
Vol 2531 (1) ◽  
pp. 54-62 ◽  
Author(s):  
Hyeon-Shic Shin ◽  
Michael Callow ◽  
Seyedehsan Dadvar ◽  
Young-Jae Lee ◽  
Z. Andrew Farkas
Keyword(s):  
Willingness To Pay ◽  
Online Survey ◽  
Connected Vehicle ◽  
Purchasing Decisions ◽  
Important Constraint ◽  
Trade Offs ◽  
Collision Prevention ◽  
Adaptive Choice ◽  
The Difference ◽  
Vehicle Technologies

The preferences of drivers and their willingness to pay (WTP) for connected vehicle (CV) technologies were estimated with the use of adaptive choice-based conjoint (ACBC) analysis, the newest such method available. More than 500 usable surveys were collected through an online survey. Respondents were asked to choose from variously priced CV technology bundles (e.g., collision prevention, roadway information system). The study found that the acceptance level of the CV technologies was high, given that an absolute majority of survey respondents had the highest preferences for the most comprehensive technology bundle in each attribute. However, a comparison of the average importance of each attribute, including bundle prices, implied that price would be an important constraint and would influence CV deployment rates. At the attribute level, collision prevention technology received the highest importance score (i.e., the safety benefits most appealed to drivers). The ACBC analysis seemed to mimic well the trade-offs that people would consider in their actual purchasing decisions. The difference between WTP and self-explicated prices obtained before preferences were estimated was statistically significant (i.e., participants chose bundles after they considered product attributes and prices). This finding also affirmed that the ACBC analysis was a more appropriate method than the direct questioning methods used in past studies. Finally, certain socioeconomic characteristics were positively related to WTP. Those respondents that were knowledgeable about CV technologies and showed more innovativeness had higher WTP as well.

Anticipatory Dynamic Traffic Sensor Location Problems with Connected Vehicle Technologies

2018 ◽  
Vol 52 (6) ◽  
pp. 1299-1326 ◽  
Author(s):  
Hyoshin (John) Park ◽  
Ali Haghani ◽  
Song Gao ◽  
Michael A. Knodler ◽  
Siby Samuel
Keyword(s):  
Location Problems ◽  
Connected Vehicle ◽  
Sensor Location ◽  
Dynamic Traffic ◽  
Vehicle Technologies

scholarly journals Review of Usage of Real-World Connected Vehicle Data

2020 ◽  
Vol 2674 (10) ◽  
pp. 939-950
Author(s):  
Yun Zhou ◽  
Raj Bridgelall
Keyword(s):  
Real World ◽  
Large Scale ◽  
The United States ◽  
Connected Vehicles ◽  
United States Department ◽  
Connected Vehicle ◽  
Pilot Model ◽  
Vehicle Data ◽  
World Information ◽  
Vehicle Technologies

GPS loggers and cameras aboard connected vehicles can produce vast amounts of data. Analysts can mine such data to decipher patterns in vehicle trajectories and driver–vehicle interactions. Ability to process such large-scale data in real time can inform strategies to reduce crashes, improve traffic flow, enhance system operational efficiencies, and reduce environmental impacts. However, connected vehicle technologies are in the very early phases of deployment. Therefore, related datasets are extremely scarce, and the utility of such emerging datasets is largely unknown. This paper provides a comprehensive review of studies that used large-scale connected vehicle data from the United States Department of Transportation Connected Vehicle Safety Pilot Model Deployment program. It is the first and only such dataset available to the public. The data contains real-world information about the operation of connected vehicles that organizations are testing. The paper provides a summary of the available datasets and their organization, and the overall structure and other characteristics of the data captured during pilot deployments. Usage of the data is then classified into three categories: driving pattern identification, development of surrogate safety measures, and improvements in the operation of signalized intersections. Finally, some limitations experienced with the existing datasets are identified.

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