There are eight papers presented in this session.
How Much Drivers Know About Adaptive Cruise Control: A Survey of Owners and Non-Owners
Chelsea DeGuzman (email@example.com), University of TorontoShow Abstract
Birsen Donmez, University of Toronto
Much of the existing research on drivers’ understanding of adaptive cruise control (ACC) was conducted several years ago when ACC was less common. Through an online survey, this study aimed to assess ACC knowledge among ACC owners and non-owners now that this system is more widely available. Along with knowledge of ACC features and limitations, demographic information, experience with technology, and experience with ACC (for owners) were also collected to investigate which factors predicted understanding of ACC features and limitations. Results showed that owners today have a better understanding of some of the main limitations of ACC compared to research conducted 10+ years ago. However, a large percentage of owners still had misperceptions about their ACC system. While owners had a slightly higher percentage of correct answers overall, responses were similar among owners and non-owners. As this technology is becoming more common, even non-owners may be becoming aware of the common limitations; owning and using ACC does not seem to result in a better understanding of the system. Higher income was associated with a higher percentage of correct responses on the ACC knowledge questionnaire for both owners and non-owners, and for non-owners, higher education level was also significantly associated with a higher percentage of correct responses. Future research should focus on developing training materials that are accessible to all segments of the population, so that drivers in lower education and income groups are also supported to understand how ACC works and benefit from this technology.
Exploring Public Perception of Level-2 Automation and Full Automation: Interview Based Study
Sanaz Motamedi (firstname.lastname@example.org), University of FloridaShow Abstract
Pei Wang, University of California, Berkeley
Ching-Yao Chan, Lawrence Berkeley National Laboratory
Automated driving systems have the potential to resolve some of current transportation challenges. The extent of improvements depends on public perception which can potentially be observed in the usage of level-2 automation that have been introduced to the market. The level-2 automation that was chosen to be a target system in this study is Autopilot system offered by Tesla, which is the prevalent type of level-2 automation available in the market. In this study, we interviewed 20 Tesla end-users who had relatively extensive experience with Autopilot. The semi-structured interviews to understand end-user’s expectation prior to and post learning experience, their learning process, importance of factors in its adoption and its shared-use concept adoption of full automation. The findings showed that the end-users had a good understanding regarding the benefits of the Autopilot prior to purchase. Since majority of end-users had some concerns only after learning process, we can conclude that the learning experience had opened the end-user’s eyes to the limitations of Autopilot. The primary method for learning the technology was trial-and-error; therefore, the users failed to learn many features of Autopilot thoroughly. End-users expressed more trust issues for full automation in certain driving conditions than level-2 automation. For shared-use concept of full automation, end-users revealed significant preference over existing shared mobility services. This study presented perception of end-users of level-2 automation and shed light on the perception of end-users of full automation. These findings give guidance to researchers and engineers to enhance users’ acceptance for future driving automation.
Effects of Auditory Display Types and Acoustic Variables on Subjective Driver Assessment in a Rail-Crossing Context
Chihab Nadri, Virginia Polytechnic Institute and State University (Virginia Tech)Show Abstract
Seulchan Lee, Gyeongsang National University
Siddhant Kekale, Virginia Polytechnic Institute and State University (Virginia Tech)
Yinjia Li, Virginia Polytechnic Institute and State University (Virginia Tech)
Xuan Li, Virginia Polytechnic Institute and State University (Virginia Tech)
Pasi Lautala, Michigan Technological University
David Nelson, Michigan Technological University
Myounghoon Jeon (email@example.com), Virginia Polytechnic Institute and State University (Virginia Tech)
Highway-Rail Grade Crossings (HRGCs) present multiple collision risks for motorists, suggesting the need for additional countermeasures to increase driver compliance. The use of in-vehicle auditory alerts (IVAA) at HRGCs has been increasing, but there are limited standards or guidelines on how such alerts should be implemented. In the current study, we sought to investigate the effect of different auditory display variables, such as display type and acoustics, on subjective user assessments. We recruited 24 participants and asked them to rate 36 different In-Vehicle Auditory Alerts (IVAAs), belonging to one of three display types (Earcons, Speech alerts, Hybrid alerts consisting of an earcon and speech) along 11 subjective ratings. Results showed that a Hybrid alert led to better overall ratings in terms of acceptance, safety, and semantic understanding when compared to earcons or speech alone. Additional analysis revealed that semantic variables, such as speech order and gender, should be accounted for when designing IVAAs in a HRGC context. Hybrid IVAAs with spatial audio showed lower urgency and hazard level ratings. Findings of the current study can help inform the design of IVAAs for HRGCs.
Perceptions of Multimodal Traffic Safety Concerns in a University Population
Md Rafiur Rahman, Utah State UniversityShow Abstract
Niranjan Poudel, Utah State University
Patrick Singleton, Utah State University
Travelers may have different perceptions of the risks of using various modes and concerns about traffic safety, which may affect their transportation choices and risk-taking behaviors as well as the overall safety performance of multimodal transportation systems. The objective of this study was to examine perceptions and concerns over traffic safety among a multimodal group of travelers. The analysis used data from an online questionnaire survey completed by over 2,000 students and employees at a public university. Four latent variables—concerns about pedestrians and cyclists, auto drivers, modal interactions, and roadway conditions—were developed using factor analysis from 16 questions about traffic safety concerns. These four types of concerns were then analyzed for potential influences of the choice of travel modes, commute behavior, and socio-demographics using a structural equation model. Results showed that perceived safety varies systematically among different mode users and demographic groups. Auto drivers perceived interactions with pedestrians and cyclists as concerning, while non-auto users felt more concerned by automobile traffic. Women and non-white road users perceived risk at a higher level. Findings about perceptions of traffic safety concerns provide insights into designs, plans, and policies for making a safer multimodal transportation system for all road users.
The Effect of Ride Experience on Changing Opinions Toward Autonomous Vehicle Safety
Xiaowei Shi, University of South FloridaShow Abstract
Zhen Wang, Chang'an University
Xiaopeng Li (firstname.lastname@example.org), University of South Florida
Autonomous vehicles (AVs) are a promising emerging technology that is likely to be widely deployed in the near future. People’s perception on AV safety is critical to the pace and success of deploying the AV technology. Existing studies found that people’s perceptions on emerging technologies might change as additional information was provided. To investigate this phenomenon in the AV technology context, this paper studies the factors associated with people’s initial opinions without any AV riding experience and opinion change after a successful AV ride. A series of ordered probit models considering data heterogeneity are employed to estimate the impact of these factors on people’s initial opinions and opinion change. The study finds that people’s initial opinions toward AV safety are significantly associated with people’s age, personal income, monthly fuel cost, education experience, and previous AV experience. Further, the factors dominating people’s opinion change after a successful AV ride include people’s age, personal income, monthly fuel cost, daily commute time, driving alone indicator, willingness to pay for AV technology, and previous AV experience. These results provide important references for future implementations of the AV technology. Additionally, based on the inconsistent effects for variables across different models, suggestions for future transportation survey designs are provided.
Comparison of acceptance of highly automated vehicles between car users and pedestrians
Yu Zhang, Wuhan UniversityShow Abstract
Liu Yang (email@example.com), Wuhan University
Rongkai Su, Wuhan University
Xinyue Wang, Wuhan University
Weijia Sun, Wuhan University
Han Wang, Wuhan University
With the rapid development of the highly automated vehicle technologies, the acceptance of highly automated vehicles has attracted more and more research attention. Many studies have examined the acceptance of highly automated vehicles from the perspective of car users. However, few studies have considered the pedestrian’s perspective, and even fewer have compared the acceptability of car users and pedestrians . To fill these gaps, the study used Theory of Planned Behaviour (TPB) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to construct questionnaire survey on the acceptance of highly automated vehicles from the perspectives of car users and pedestrians respectively. A total of 637 participants completed the survey. Independent sample t test, correlation analysis and multiple linear regression analysis were adopted to explore the relationship between TPB factors and make comparisons between car users and pedestrians . The findings revealed that pedestrians have higher acceptance of highly automated vehicles than car users . Both car users’ and pedestrians’ intentions for highly automated driving vehicles were positively correlated to attitudes (including performance expectations), subjective norms, and perceived behavior control. In addition, subjective norms and perceptual behavior control can be used to predict car users’ intentions for highly automated vehicles, while attitudes, subjective norms and perceptual behavior control can be used to predict pedestrians’ intentions for highly automated vehicles.
Safety Enhancements to Reduce Speeding in School Zones Using Driving Simulation
Yindhira Taveras, Recinto Universitario de Mayaguez Universidad de Puerto RicoShow Abstract
Didier Valdés, Recinto Universitario de Mayaguez Universidad de Puerto Rico
Benjamin Colucci Rios, Recinto Universitario de Mayaguez Universidad de Puerto Rico
Alberto Figueroa-Medina, Recinto Universitario de Mayaguez Universidad de Puerto Rico
Maria Rojas, Recinto Universitario de Mayaguez Universidad de Puerto Rico
Rocío Sotomayor-Irizarry, Recinto Universitario de Mayaguez Universidad de Puerto Rico
Cindy Sierra, Recinto Universitario de Mayaguez Universidad de Puerto Rico
Traffic crashes in school zones continues to be a serious safety concern. Low speed compliance in school zones is a pressing issue that compromises vulnerable road-users creating the possibility of high impact crashes. Four countermeasures designed to reduce speeding in a school zones were evaluated to measure changes in drivers’ speed using a driving simulator. The countermeasures evaluated were Overhead signs, Two-Step Speed Reduction, Reduce Speed Ahead signs, and Speed Monitoring Display. Performance was measured using speed, and speed compliance as dependent variables. Results indicate that all the countermeasures evaluated improved drivers’ compliance with the School Zone speed Limits. Similar improvements were observed with both the overhead signs and the Two-Step Speed Reduction. However, the best results were obtained with the Speed Monitoring Display used as an Advanced Driver Assistance System (ADAS). All the improvements were statistically significant with respect to the base case considering the current signage conditions. Furthermore, the analysis performed demonstrated improving compliance through the combination of overhead signs with the other countermeasures evaluated
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