The increasing shortage of drivers poses a significant threat to vulnerable populations, particularly seniors and disabled individuals who heavily depend on public transportation for accessing healthcare services and social events. Autonomous Vehicles (AVs) emerge as a promising alternative, offering potential improvements in accessibility and independence for these groups. However, current designs and studies often overlook the unique needs and experiences of these populations, leading to potential accessibility barriers. This paper presents a detailed case study of an autonomous shuttle test specifically tailored for seniors and disabled individuals, conducted during the early stages of the COVID-19 pandemic. The service, which lasted 13 weeks, catered to approximately 1500 passengers in an urban setting, aiming to facilitate access to essential services. Drawing from the safety operator's experiences and direct observations, we identify critical user experience and safety challenges faced by vulnerable passengers. Based on our findings, we propose targeted initiatives to enhance the safety, accessibility, and user education of AV technology for seniors and disabled individuals. These include increasing educational opportunities to familiarize these groups with AV technology, designing AVs with a focus on diversity and inclusion, and improving training programs for AV operators to address the unique needs of vulnerable populations. Through these initiatives, we aim to bridge the gap in AV accessibility and ensure that these technologies benefit all members of society.

The problem of allocating accident responsibility for autonomous driving is a difficult issue in the field of autonomous driving. Due to the complexity of autonomous driving technology, most of the research on the responsibility of autonomous driving accidents has remained at the theoretical level. When encountering actual autonomous driving accidents, a proven and fair solution is needed. To address this problem, this study proposes a multi-subject responsibility allocation optimization method based on the RCModel (Risk Chain Model), which analyzes the responsibility of each actor from a technical perspective and promotes a more reasonable and fair allocation of responsibility.

Robotaxi safety operator is an occupation that exists only in our time, the result of an evolving technology that's advanced enough to get rid of a driver--most of the time, and in controlled environments--but not good enough to convince authorities that they can do away with human intervention altogether. Today, self-driving companies from the US, Europe, and China are racing to bring the technology to commercial application. Most of them, including Apollo, the self-driving arm of Baidu, have started on-demand robotaxi trials on public roads but still need to operate with various constraints. With an associate degree in human resources, Liu has no academic training related to this job, But he has always loved driving, and he acted as the driver for his boss in a previous role. When he heard about the self-driving technologies, his curiosity pushed him to look up related jobs online and apply.

Robotaxi safety operator is an occupation that only exists in our time, the result of an evolving technology that's advanced enough to get rid of a driver--most of the time, and in controlled environments-- but not good enough to convince authorities that they can do away with human intervention altogether. Today, self-driving companies from the US, Europe, and China are racing to bring the technology to commercial application. Most of them, including Apollo, the self-driving arm of Baidu, have started on-demand robotaxi trials on public roads yet still need to operate with various constraints. With an associate degree in human resources, Liu has no academic training related to this job, But he has always loved driving, and he acted as the driver for his boss in a previous role. When he heard about the self-driving technologies, his curiosity pushed him to look up related jobs online and apply.

Chinese internet giant Baidu and autonomous vehicle company Pony.ai To date, numerous cities in China have allowed autonomous vehicle companies to test self-driving vehicles without a human safety operator in the driver's seat, but this is the first time companies are allowed to run a fully driverless service. That said, the permit does require the companies to have a safety operator present in the front passenger seat, so the regulation is not quite as mature as, say, California's driverless permits which require no human in the vehicle aside from the passenger. Neither Pony nor Baidu will be charging a fee for driverless rides yet, although both companies are currently running commercial services with drivered robotaxis in Yizhuang, Beijing, otherwise referred to as Beijing High-level Automated Driving Demonstration Area (BJHAD), according to a Baidu spokesperson. This 60-square-kilometer stretch of Beijing, home to about 300,000 residents, is also where both Baidu's and Pony's driverless service will run.

"I would be shocked if we do not achieve full self-driving safer than a human this year," said Tesla chief executive, Elon Musk, in January. For anyone who follows Musk's commentary, this might sound familiar. In 2020, he promised autonomous cars the same year, saying: "There are no fundamental challenges." In 2019, he promised Teslas would be able to drive themselves by 2020 – converting into a fleet of 1m "robotaxis". He has made similar predictions every year going back to 2014.

FREMONT, California – Self-driving startups like Cruise and Pony.ai have begun testing their driverless cars in some parts of California in the past year with an additional feature: human operators. While there is no driver behind the wheel, the passenger seat is occupied by a safety operator who "has a red button that can stop the vehicle just in case anything happens," Pony.ai The operator will be removed next year when Pony.ai, whose investors include Toyota Motor Corp., plans to deploy its driverless ride-hailing vehicles in certain areas of California. Still, a remote operator will monitor vehicles and provide guidance when the vehicles run into trouble, Peng said. Alphabet Inc.'s Waymo keeps personnel wearing fluorescent yellow vests at the ready to provide roadside assistance for its automated minivans in Phoenix, according to videos and to one of its avid riders, Joel Johnson, who has witnessed this.

Cruise, the autonomous vehicle subsidiary of GM that also has backing from SoftBank Vision Fund, Microsoft and Honda, has secured a permit that will allow the company to shuttle passengers in its test vehicles without a human safety operator behind the wheel. The permit, issued by the California Public Utilities Commission as part of its driverless pilot program, is one of several regulatory requirements autonomous vehicle companies must meet before they can deploy commercially. This permit is important -- and Cruise is the first to land this particular one -- but it does not allow the company to charge passengers for any rides in test AVs. "In order to launch a commercial service for passengers here in the state of California, you need both the California DMV and the California PUC to issue deployment permits. Today we are honored to have been the first to receive a driverless autonomous service permit to test transporting passengers from the California PUC," Prashanthi Raman, Cruise's director of Government Affairs said in an emailed statement to TechCrunch.

Texas A&M University is modifying its self-driving pilot program in the city of Bryan, Texas, to have humans remotely monitor and operate the shuttles starting in September, making it one of the first commercial deployments of teleoperation technology in the country. The teleoperation technology is being provided by a Portland, Oregon-based startup called Designated Driver. It will allow humans at Texas A&M to remotely control the shuttles in situations where the self-driving system may not be up to snuff, and they'll also be able to interact with passengers on board. The new functionality could help solve a problem that similarly nascent autonomous shuttle programs have run into: crashes. The low-speed autonomous shuttles currently whispering their way around a handful of downtown areas and campuses across the country are among the first real-world tests of self-driving technology.

"What was underappreciated by the industry is how long and how difficult it would be to industrialize the technology," said Karl Iagnemma, president of Aptiv's autonomous mobility. "Industrywide that recognition has dawned." The hype that has consumed the nascent driverless-car industry over the past few years has moved into a new period of cautious optimism following the fatal crash of an Uber Technologies Inc. test autonomous vehicle last year and separate crashes involving Tesla Inc.'s driver-assistance system. At both the CES tech show here last week and this week's Detroit auto show, straight talk about robot-vehicle safety and scaled-back expectations replaced past years' boastful claims of fully driverless cars flooding cities. The immediate future of autonomous vehicles is more subdued: plodding shuttles that drive around the block and cars that travel in confined, well-practiced routes with not one but two safety operators inside.