# Autonomous Vehicles in Rural Areas: A Review of Challenges, Opportunities, and Solutions
## 3 Results
### Future of AV Deployment in Rural Areas
#### 3.3.5 User Perception and Acceptance  
Technology reliability and road safety are key factors influencing rural residents' acceptance of AVs, alongside accessibility, enjoyment, and ease of use, although privacy concerns negatively impact adoption [64]. [PERSON] et al. (2024) [59] highlighted key differences between rural and urban areas. Rural residents are less likely to adopt AVs due to affordability issues, poor infrastructure, and low population density, which limits benefits like reduced congestion and pollution. Many prefer conventional vehicles, feel uneasy sharing roads with AVs, and exhibit cautious attitudes, whereas urban residents are more open, driven by greater exposure to congestion and shared mobility. Urban residents value time savings but weigh anticipated benefits against costs and technological uncertainties. According to a study by [PERSON] (2023) [95], the acceptance of autonomous vehicles (AVs) and the perceived risks associated with them are multifaceted phenomena shaped by the interplay of personal and cultural contexts. The study emphasizes the importance of considering both demographic and cultural factors when designing strategies to promote the acceptance of AVs. Field test-based, simulation-based, and survey-based studies have comprehensively evaluated AV acceptance factors. User perception and acceptance of ADS also vary depending on system performance during different deployment phases, particularly in complex tasks like intersections and parking [73]. Gradual improvements in AV technology have helped build trust, although unpredictable conditions remain a concern. Studies show that direct exposure and experience enhance acceptance, as demonstrated in CASSI pilots, where 83% of users at UNC Charlotte and 92% at Cary expressed positive experiences [93; 94]. Users valued safety and convenience but noted issues such as slow speeds, limited accessibility features, and unstable ramps that struggled with varying device sizes and weights. The goMARTI project found strong acceptance among users without reliable transportation, reflecting the potential for AV services to address rural mobility needs [37]. Community engagement and enhanced accessibility features foster user trust, as seen in national park pilots (TEDDY and CASSI pilots), where 98% of users felt safe despite requesting smoother operations and avoiding jerky stops [73]. In the ADS for rural areas project, trust in AVs rose from 60% to 75% post-ride, with perceived reliability increasing from 63% to 81% [77; 92]. These findings align with the results of [PERSON] et al. (2020) [96], who examined survey data from non-motorists in Pittsburgh. Their study found that AV perceptions varied across stakeholder groups, with those having prior AV interaction expressing greater interest and higher expectations. In contrast, participants skeptical about AV safety were opposed to using the city as a proving ground. The DriveOhio project emphasized rural residents' concerns about AVs navigating unmarked roads, sharp curves, and limited infrastructure. Older adults and those with lower education initially had less trust but showed increased acceptance after demonstrations [68]. The MN Drive Project [43] and [PERSON] et al. (2022) [50] highlighted rising acceptance through exposure. Surveys from events like the 2022 Drive MN survey and earlier studies (2018 Minnesota State Fair and 2020 Live CAV Minnesota) proved this fact as well. However, issues like slow speeds, indirect routes, and limited accessibility features reduced usability, particularly for individuals with disabilities. [PERSON] et al. found that older adults experienced reduced suspicion and increased trust after riding autonomous shuttles, though anxiety spiked during high-speed maneuvers like highway merging. Over time, participants became more comfortable with AV interactions involving pedestrians and cyclists [50]. Regarding simulation-based studies, [PERSON] et al. (2015) [11] evaluated AV performance in simulated rural environments with low traffic and sudden diversions.