Autonomous Vehicle Technology: How to Best Realize Its Social Benefits

Anderson, James M.; Kalra, Nidhi; Stanley, Karlyn D.; Sorensen, Paul; Samaras, Constantine; Oluwatola, Tobi A.

doi:10.7249/rb9755

Cited by 43 publications

(57 citation statements)

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“…This number increases by more than 60% for Boston and Washington D.C. which are ranked as the most congested two cities in the United States (“INRIX 2018 Global Traffic Scorecard,” 2018). Researchers have argued that automated driving systems (levels 3-5; SAE International, 2018) have the potential to resolve some of the current transportation challenges and to improve road safety and efficiency (Anderson et al, 2014; Arvin, Kamrani, Khattak, & Rios-Torres, 2018; Bengler, Dietmayer, Maurer, & Winner, 2014; Litman, 2017; Rahimi, Azimi, Asgari, & Jin, 2019).…”

Section: Introductionmentioning

confidence: 99%

Acceptance of Full Driving Automation: Personally Owned and Shared-Use Concepts

et al. 2019

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Objective This study aims to develop user acceptance models for two concepts of full driving automation: personally owned and shared use. Background Many manufacturers have been investing considerably in and actively developing full driving automation. However, factors influencing user acceptance of full driving automation are not yet fully understood. Method This study consisted of two parts: focus group discussions and online surveys. A total of 30 potential users participated in focus groups to discuss their perception of full driving automation acceptance. Based on the findings from focus group discussions, theoretical foundations, and empirical evidence, we hypothesized the acceptance models for both personally owned and shared-use concepts. We tested the models with 310 and 250 participants, respectively, online. Results The results of focus groups indicated that users’ concerns are centered around safety, usefulness, compatibility, trust, and ease of use. The survey results revealed the important roles of perceived usefulness and perceived safety in both models, whereas the direct impact of perceived ease of use was found to be insignificant. The indirect impact of perceived ease of use was less significant in the personally owned than in the shared-use model, whereas usefulness, trust, and compatibility played more important roles in the personally owned when compared with the shared-use model. Conclusion The findings uncovered a chain of constructs that affect behavioral intention to use for both full driving automation concepts. Application The framework and outcome of this study provide valuable guidelines that allow better understanding for government agencies, manufacturers, and automation designers regarding users’ acceptance of full driving automation.

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Section: Introductionmentioning

confidence: 99%

Acceptance of Full Driving Automation: Personally Owned and Shared-Use Concepts

et al. 2019

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“…With the rapid development of automated technologies, future road driving will be largely reformed. Although automated driving has several bottlenecks to overcome, it can reduce crashes, prevent deaths and injuries, and alleviate traffic issues, such as congestion and emission ( Anderson et al, 2014 ). The available automated driving (i.e., conditional automated driving, level 3; SAE International, 2018 ) no longer requires drivers to supervise the traffic environment.…”

Section: Introductionmentioning

confidence: 99%

Optimal Time Intervals in Two-Stage Takeover Warning Systems With Insight Into the Drivers’ Neuroticism Personality

et al. 2021

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Conditional automated driving [level 3, Society of Automotive Engineers (SAE)] requires drivers to take over the vehicle when an automated system’s failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the optimal time intervals of two-stage warning systems with insights into the drivers’ neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism (high vs. low). Each driver experienced takeover under the two-stage warning systems with four time intervals (i.e., 3, 5, 7, and 9 s). The takeover performance (i.e., hands-on-steering-wheel time, takeover time, and maximum resulting acceleration) and subjective opinions (i.e., appropriateness and usefulness) for time intervals and situation awareness (SA) were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation (fast hands-on steering wheel responses and sufficient SA). Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers.

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“…CVs use different communication technologies to communicate with drivers, other cars on the road (vehicle to vehicle) and roadside infrastructure (vehicle to everything) (CAAT, 2016). AVs guide themselves without any human intervention by using technologies such as crash warning systems and lane keeping systems (Anderson et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Low-Cost Receiver and Network Real-Time Kinematic Positioning for use in Connected and Autonomous Vehicles

2019

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Connected and Autonomous Vehicles (CAVs) have been researched extensively for solving traffic issues and for realising the concept of an intelligent transport system. A well-developed positioning system is critical for CAVs to achieve these aims. The system should provide high accuracy, mobility, continuity, flexibility and scalability. However, high-performance equipment is too expensive for the commercial use of CAVs; therefore, the use of a low-cost Global Navigation Satellite System (GNSS) receiver to achieve real-time, high-accuracy and ubiquitous positioning performance will be a future trend. This research used RTKLIB software to develop a low-cost GNSS receiver positioning system and assessed the developed positioning system according to the requirements of CAV applications. Kinematic tests were conducted to evaluate the positioning performance of the low-cost receiver in a CAV driving environment based on the accuracy requirements of CAVs. The results showed that the low-cost receiver satisfied the “Where in Lane” accuracy level (0·5 m) and achieved a similar positioning performance in rural, interurban, urban and motorway areas.

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Autonomous Vehicle Technology: How to Best Realize Its Social Benefits

Cited by 43 publications

References 0 publications

Acceptance of Full Driving Automation: Personally Owned and Shared-Use Concepts

Acceptance of Full Driving Automation: Personally Owned and Shared-Use Concepts

Optimal Time Intervals in Two-Stage Takeover Warning Systems With Insight Into the Drivers’ Neuroticism Personality

Low-Cost Receiver and Network Real-Time Kinematic Positioning for use in Connected and Autonomous Vehicles

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