Assessing public opinions of and interest in new vehicle technologies: An Austin perspective

Bansal, Prateek; Kockelman, Kara M.; Singh, A. K.

doi:10.1016/j.trc.2016.01.019

Cited by 837 publications

(615 citation statements)

References 4 publications

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“…It is also important to note the effect of vehicle automation on the travel characteristics of the elderly and those with a travel-restrictive medical condition will highly depend on the cost of an automated vehicle and their willingness to adopt the new technology (Bansal et al, 2016) It will also depend on the time of day and location that new demand from these populations is generated. In addition, in a fully automated environment comprising mostly of taxis, there would be additional VMT when the vehicles have no occupants.…”

Section: Discussionmentioning

confidence: 99%

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Harper

Hendrickson

Mangones

et al. 2016

Transportation Research Part C: Emerging Technologies

359

168

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Automated vehicles represent a technology that promises to increase mobility for many groups, including the senior population (those over age 65) but also for non-drivers and people with medical conditions. This paper estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. In addition, these bounding estimates indicate which of these demographics could have the greatest increases in annual vehicle miles traveled (VMT) and highlight those age groups and genders within these populations that could contribute the most to the VMT increases. The data source is the 2009 National Household Transportation Survey (NHTS), which provides information on travel characteristics of the U.S. population. The changes to light-duty VMT are estimated by creating and examining three possible travel demand wedges. In demand wedge one, non-drivers are assumed to travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly (those over age 65) without medical conditions will travel as much as a younger population within each gender. Demand wedge three makes the assumption that working age adult drivers (19-64) with medical conditions will travel as much as working age adults without medical conditions within each gender, while the driving elderly with medical any travel-restrictive conditions will travel as much as a younger demographic within each gender in a fully automated vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 295 billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. Since traveling has other costs besides driving effort, these estimates serve to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios.

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Section: Discussionmentioning

confidence: 99%

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Harper

Hendrickson

Mangones

et al. 2016

Transportation Research Part C: Emerging Technologies

359

168

View full text Add to dashboard Cite

show abstract

“…Widely adopting AD could dramatically reduce the number of traffic crashes caused by human error (NHTSA, ). Other benefits include an increase in mobility for those currently unable to drive, the reduction of air pollution, higher fuel efficiency, and better space utilization (Anderson et al., ; Bansal, Kockelman, & Singh, ; Fagnant & Kockelman, ; Howard & Dai, ). However, many people are highly concerned about the safety, security, legal liability, and regulation issues connected with AD (Bansal et al., ; Howard & Dai, ; Kyriakidis, Happee, & de Winter, ).…”

Section: Introductionmentioning

confidence: 99%

Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions

2018

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Automated driving (AD) is one of the most significant technical advances in the transportation industry. Its safety, economic, and environmental benefits cannot be realized if it is not used. To explain, predict, and increase its acceptance, we need to understand how people perceive and why they accept or reject AD technology. Drawing upon the trust heuristic, we tested a psychological model to explain three acceptance measures of fully AD (FAD): general acceptance, willingness to pay (WTP), and behavioral intention (BI). This heuristic suggests that social trust can directly affect acceptance or indirectly affect acceptance through perceived benefits and risks. Using a survey (N = 441), we found that social trust retained a direct effect as well as an indirect effect on all FAD acceptance measures. The indirect effect of social trust was more prominent in forming general acceptance; the direct effect of social trust was more prominent in explaining WTP and BI. Compared to perceived risk, perceived benefit was a stronger predictor of all FAD acceptance measures and also a stronger mediator of the trust-acceptance relationship. Predictive ability of the proposed model for the three acceptance measures was confirmed. We discuss the implications of our results for theory and practice.

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“…23,24 Roadside units (RSUs), 25 cellular network, 26,27 mobile cloud computing, 28 and fog vehicular computing 29 are examples of solutions that have been presented recently. In many of these studies, information security breaches and privacy violation have been mentioned as one of the main concerns that originates from resource-constraint.…”

Section: Case Studymentioning

confidence: 99%

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

Safa

Maple

Haghparast

et al. 2018

Concurrency and Computation

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Experts believe that the Internet of Things (IoT) is a new revolution in technology and has brought many advantages for our society. However, there are serious challenges in terms of information security and privacy protection. Smart objects usually do not have malware detection due to resource limitations and their intrusion detection work on a particular network. Low computation power, low bandwidth, low battery, storage, and memory contribute to a resource-constrained effect on information security and privacy protection in the domain of IoT. The capacity of fog and cloud computing such as efficient computing, data access, network and storage, supporting mobility, location awareness, heterogeneity, scalability, and low latency in secure communication positively influence information security and privacy protection in IoT. This study illustrates the positive effect of fog and cloud computing on the security of IoT systems and presents a decision-making model based on the object's characteristics such as computational power, storage, memory, energy consumption, bandwidth, packet delivery, hop-count, etc. This helps an IoT system choose the best nodes for creating the fog that we need in the IoT system. Our experiment shows that the proposed approach has less computational, communicational cost, and more productivity in compare with the situation that we choose the smart objects randomly to create a fog.KEYWORDS cloud, Fog, information security, Internet of Things, privacy, resource INTRODUCTIONThe Internet has provided a backbone for connecting different objects to each other and has changed human life significantly. The ubiquitous things is a new concept that has been created by the interconnection and intercommunication amongst smart objects. 1 We are faced with a huge volume of data in this environment. Network traffic, increasing demands of real time, latency-sensitive applications, resource-constraints (computational power, storage, memory, etc) in actuators, mobility and geo-distribution of smart objects, and heterogeneity that are new challenges in the domain of IoT. 2 These weaknesses directly or indirectly influence information security and privacy violation in IoT systems. 3Resource-constraint in actuators jeopardises secure communication between different smart objects. 4 Messages need to be sent encrypted;they will be decrypted for process in the target. The result of the process should be encrypted and send to the same object or other smart objects.We have latency; this delays not only creates risk for information security, but it may also impact human safety in some applications of IoT, such as smart vehicles. Lightweight cryptography has been presented to overcome this challenge in vehicle-to-vehicle (V2V) communication and in many other secure communications in IoT. 5 Smart objects usually do not have malware detection due to limitation in resources; their intrusion detection only can detect attacks in particular networks (not hybrid). These are examples of common problems in the IoT domain.Cloud...

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Assessing public opinions of and interest in new vehicle technologies: An Austin perspective

Cited by 837 publications

References 4 publications

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Estimating potential increases in travel with autonomous vehicles for the non-driving, elderly and people with travel-restrictive medical conditions

Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

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