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• Examines the perceptions of people with special needs on autonomous public transit. • Points out differences among different special needs populations. • Compares acceptance and concerns between people with different disabilities. Large mobility gaps exist between people with and without disabilities. People with special needs are heavily dependent upon public transportation for their essential needs. Autonomous vehicles (AVs) have the potential to increase mobility for these populations. However, they have been largely absent from AV perception research. To fill this gap, we analyzed their perceptions, willingness to use, and concerns over autonomous public transit (APT) based on an on-board intercept survey of 1861 current bus riders in Michigan, with 40% having some type of special needs. We found significant differences among different special needs groups. While respondents who were visually impaired, mobility restricted, or with multiple accommodation needs were more likely to rely on public transit than those without any special needs, their willingness to use APT varied. Respondents with visual impairment were more likely, but riders with mobility disabilities were less likely to be willing to use APT. In addition, our survey results suggest that respondents with special needs perceive AVs primarily negatively. This was especially true for mobility-restricted groups. Furthermore, there were differences in bus riders' reasons not to use APT. Compared to respondents without special needs, those with multiple accommodation needs hold concerns over APT's safety more, while respondents with mobility disabilities were more likely to distrust AV technology. This study advances our understanding of different special needs populations' perception and acceptance of APT, providing support to policymakers in developing inclusive policies and practices that would bring the promised benefits of AVs to these populations. [ABSTRACT FROM AUTHOR]

Public perception of the next generation of vehicles will affect their design, deployment, and ultimately their use. As the engineering terms of self-driving, driverless, fully automated, and autonomous were introduced to the social sciences and the public at large, the subtle differences among these terms have been lost. However, using them as synonyms even though they may not be interchangeable is problematic. To explore the semantics of different future vehicle terms we surveyed 963 Michigan residents on their understanding of "autonomous" and "self-driving." We found significant differences in perceptions between the terms autonomous and self-driving vehicles. While the former invokes many more uncertain responses, the latter is laden with concerns. These results suggest that the language used to describe the next generation of vehicles may shape public reaction and acceptance. As new mobility options are introduced to the public, our understanding of them will be shaped, in part, by the language used to name and explain the technology. Far from being inconsequential, word choice plays a major, yet underappreciated, role in shaping public opinion. [ABSTRACT FROM AUTHOR]

This article presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles (AVs) at different days and times during 2017–2018. The vehicles traversed an average route of 66 km in Michigan that included a mix of driving scenarios such as the Detroit airport, freeways, city centers, university campus, and suburban neighborhoods. Each vehicle used in this data collection was a Ford Fusion outfitted with an Applanix POS-LV GNSS/INS system, four HDL-32E Velodyne 3D-lidar scanners, six Point Grey 1.3 MP cameras arranged on the rooftop for 360° coverage, and one Point Grey 5 MP camera mounted behind the windshield for the forward field of view. We present the seasonal variation in weather, lighting, construction, and traffic conditions experienced in dynamic urban environments. We also include data from multiple AVs that were driven in close proximity. This dataset can help design robust algorithms for AVs and multi-agent systems. Each log in the dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground-truth pose, and 3D maps. All data is available in rosbag format that can be visualized, modified, and applied using the open-source Robot Operating System (ROS). We also provide the output of reflectivity-based localization for bench-marking purposes. The dataset can be freely downloaded at avdata.ford.com. [ABSTRACT FROM AUTHOR]

• Examines the views of public transit riders including the mobility-challenged. • Determines attitudes towards AVs using a dual sampling survey approach. • Provides empirical evidence on AV willingness to ride between fixed-route and demand-response riders. • Compares the attitudes of seniors and special needs population, against general public transit riders. Autonomous vehicles (AVs) hold great promise to contribute to global sustainability by expanding access to mobility. The introduction of autonomous buses and shuttles could be a turning point for public mobility in the USA, but how autonomous public transit is perceived remains largely unknown. To fill this gap, this study analyzes the willingness to use autonomous buses and shuttles based on two surveys conducted in Michigan. These surveys were a phone-based random-sampling survey of the general public and an on-board intercept survey of public transit riders. We found that autonomous buses might increase willingness to use public transit. 15% of people, who occasionally ride or do not ride public transit, embrace the idea of using autonomous bus service, while fixed-route riders were more likely to accept AVs than demand-response transit riders. However, about half of the public transit riders were hesitant about riding in autonomous buses citing concerns over safety, no human, and distrust in technology. Willingness to ride was higher among younger males than it was for females, seniors, and people with mobility disabilities. In addition, our data suggests that riders' satisfaction with their drivers - be it skill, professionalism, or friendliness - had no impact on willingness to ride in AVs. As AVs become ready for deployment, policymakers and public transportation service providers should consider AV acceptance among vulnerable individuals to bring AV benefits to all. [ABSTRACT FROM AUTHOR]