Autonomous vehicles (AVs) are expected to bring significant changes to the mobility of people, especially those with disabilities. Despite the strong potential of AVs to impact the lives of people with disabilities, little attention has been paid to understand their perspectives on this technology. This study aims to fill the gap, by exploring the mobility challenges experienced by people with disabilities and the overall perceptions of autonomous vehicle transportation (AVT) services among people with disabilities. The specific focus is on individuals with physical disabilities and individuals with visual impairments. This study used a three-phase exploratory sequential mixed-methods design. We began by conducting focus groups and analyzing the collected data. From the focus group results, we developed a survey instrument in the second phase. In the third phase, we collected and analyzed the survey data to verify the initial focus group findings. Additionally, the survey included stated preference choice experiments to assess the AV acceptance level of people with disabilities. The results revealed that people with disabilities’ mobility issues with current public transit services and neighborhood built environments may influence their positive attitudes toward AVT services. Despite several concerns raised about AVs regarding accessibility, safety, and reliability, most participants showed a high acceptance level of AVT. The findings provide industry and policy-makers with insights into the expectations, concerns, and needs regarding AVT from the perspectives of people with disabilities.

Transportation systems worldwide are facing numerous challenges, including congestion, environmental impacts, and safety concerns. This study used a systematic literature review to investigate how advanced technologies (e.g., IoT, AI, digital twins, and optimization methods) support smart transportation planning. Specifically, this study examines the interrelationships between transportation challenges, proposed solutions, and enabling technologies, providing insights into how these innovations support smart mobility initiatives. A systematic literature review, following PRISMA guidelines, identified 26 peer-reviewed articles published between 2013 and 2024, including studies that examined smart transportation technologies. To quantitatively assess relationships among key concepts, a Sentence BERT-based natural language processing approach was employed to compute alignment scores between transportation challenges, technological solutions, and implementation strategies. The findings highlight the fact that real-time data collection, predictive analytics, and digital twin simulations significantly enhance traffic flow, safety, and operational efficiency while mitigating environmental impacts. The analysis further reveals strong correlations between traffic congestion and public transit optimization, reinforcing the effectiveness of integrated, data-driven strategies. Additionally, IoT-based sensor networks and AI-driven decision-support systems are shown to play a critical role in sustainable urban mobility by enabling proactive congestion management, multimodal transportation planning, and emission reduction strategies. From a policy perspective, this study underscores the need for investment in urban-scale data infrastructures, the integration of digital twin modeling into long-term planning frameworks, and the alignment of optimization tools with public transit improvements to foster equitable and efficient mobility. These findings offer actionable recommendations for policymakers, engineers, and planners, guiding data-driven resource allocation and legislative strategies that support sustainable, adaptive, and technologically advanced transportation ecosystems.

The Metropolitan Transit Authority of Harris County’s METROLift program implemented several revised fare policies on travel options available to eligible riders at the end of 2015 and the beginning of 2016. Fares changed on the METROLift paratransit single ticket and passes. A premium fare for the expanded service area and a smartcard—Freedom Q Card—that allows free ride on METRO’s fixed-route services were introduced. This paper documents analyses to determine the impact of the revised METROLift fare policies on travel patterns and travel frequency of METROLift riders. The authors used a linear segmented regression analysis to analyze data from an interrupted time series design. The results suggest that the revised fare policies controlled the growth of percentage of riders who use METROLift paratransit service in total ADA-eligible riders, while improved the awareness and willingness to use supplementary paratransit travel options, especially the fixed-route service in the base service area and the subsidy taxi service in the expanded service area.