# Autonomous Vehicles in Rural Areas: A Review of Challenges, Opportunities, and Solutions
## 3 Results
### Future of AV Deployment in Rural Areas
#### 3.3.2 Challenges  
The deployment of AVs in rural areas faces challenges across environmental, technological, infrastructure, and policy dimensions. [PERSON] et al. (2020) [13] identified four key barriers to electric AV adoption in rural areas: financial constraints, infrastructure limitations, policy issues, and demographic factors. The study stressed that integrating AVs with public transit must be cost-effective and include an assessment of current mobility technologies. Community engagement with vulnerable groups, including the elderly, minorities, and individuals with disabilities, is critical for shaping inclusive policies and deployment strategies. [PERSON] (2019) [21] examined the challenges of deploying AVs on unpaved roads and in environments with poor weather, limited sight distances, and unpredictable human and animal behavior. The study noted the disparity between high investments in AV technologies and insufficient road infrastructure upgrades, which are essential for safe AV operations. The study proposed a layered infrastructure approach, classifying roads by their AV compatibility, from AV-only roads to shared routes and \"last mile\" access. The findings of the study highlighted the need for concurrent development of AV technology and infrastructure, with public investments recommended to support upgrades. Similarly, [PERSON] and [PERSON] (2019) [23] analyzed AV readiness across nine countries, showing that strong technological infrastructure, supportive policies, and public acceptance drive progress in regions like Singapore, Germany, Japan, and the U.S., while other countries face setbacks due to limited resources and infrastructure. The study recommended fostering partnerships between governments and industry, creating supportive policies, and investing in infrastructure to enhance safety and accessibility. The challenges of AV deployment are listed in Table 3.  
Field-test-based studies highlight that sharp curves, unpaved roads, limited sight distances, extreme weather, and obstacles like slow-moving farming equipment and animals present significant challenges for AVs in rural area field tests [43; 48; 75; 76; 92; 93]. Environmental variability, such as shifts from shaded areas to direct sunlight, limited visibility around curves and hills, and active construction zones, complicates automation. In work zones, visual disturbances, including faded or conflicting lane markings and crack seal lines, can confuse sensors, causing misdetections [68]. Drive MN [43] identified four major issues: poor lane visibility, freeway ramps and turn lanes, construction zones, and low-contrast road markings. Dynamic lanes, faded edge stripes, unclear or inconsistent lane markings, and gravel roads often lead to detection errors and path deviations. Frequent human overrides further stress the need for robust and reliable systems [70]. Additionally, connectivity issues, including poor cellular networks, hamper V2X communication and real-time data sharing in rural areas [49; 68]. Besides physical and digital infrastructure limitations, technological issues, including GPS failures, object detection errors, miscommunication at signalized intersections, and software malfunctions, cause disengagements and reduced reliability concerns [67; 68; 70; 74; 94]. For example, reversing during automated parking [77], navigating unmarked roads [43; 48; 94], and inconsistent responses to obstacles highlight the need for system improvements. Operational challenges include battery issues, particularly in hot weather, where air conditioning strains the battery, requiring midday charging breaks and reducing efficiency [94]. Inclement weather and technical issues also cause service interruptions. Interactions with pedestrians and other vehicles further complicate operations [45; 94]. High infrastructure costs remain a major barrier to quality AV implementation in rural areas [44; 45; 83]. Interview-based studies complement these findings by exploring deployment challenges and potential solutions through qualitative analysis.