# Review of Autonomous Intelligent Vehicles for Urban Driving and Parking
###### Abstract  
With the concept of Internet-of-Things, autonomous vehicles can provide higher driving efficiency, traffic safety, and freedom for the driver to perform other tasks. This paper first covers enabling technology involving a vehicle moving out of parking, traveling on the road, and parking at the destination. The development of autonomous vehicles relies on the data collected for deployment in actual road conditions. Research gaps and recommendations for autonomous intelligent vehicles are included. For example, a sudden obstacle while the autonomous vehicle executes the parking trajectory on the road is discussed. Several aspects of social problems, such as the liability of an accident affecting the autonomous vehicle, are described. A smart device to detect abnormal driving behaviors to prevent possible accidents is briefly discussed. Internet-of-Things; intelligent transport system; fully autonomous vehicle; enabling technology; social dilemma +
Footnote †: journal: 25 April 2021  
V2V consists of multiple vehicles in which any two vehicles can communicate with each other [14; 15]. Thus, allowing the driver to be aware of other cars' speed, acceleration or deceleration, and accidents such as collision and road departure can be avoided [16]. In contrast, V2I communication allows the vehicle to access the roadside infrastructure for vast area information dissemination [17]. Services include infotainment delivery, as well as safety-related information such as speed limits, safe distance warnings, lane-keeping support, intersection safety, traffic jam warnings, and accident warnings [18]. The idea of V2P is the exchange of information between a vehicle and a pedestrian through sensors and smart devices to avoid collision [19; 20; 21]. Finally, V2N puts vehicular user equipment in communication with a server that provides centralized control and traffic, road, and service information [22]. Therefore, the use of V2X communications coupled with existing vehicle-sensing capabilities provides the fundamentals for advanced applications targeted toward road safety, passenger infotainment, manufacturer services, and vehicle traffic optimization [23; 24]. The development of such systems will ultimately rely on the data collected from actual interaction if they are to be effective when deployed in a real-life situation [25]. For example, machine vision uses image processing to monitor rear vehicles [26] and the trajectory analysis of surrounding vehicles [27]. Furthermore, historical data are used to determine the optimal control parameters for maximal fuel efficiency and saving [28]. Without full vehicle autonomy, data collected by in-car sensors can also be used to analyze driver behavior, which reduces the likelihood of impaired or drowsy driving [29]. There exists literature that has surveyed V2X communication and focused on the area of network connectivity and security [30; 31; 32; 33; 34]. Reviews that focus on other areas related to the autonomous vehicle have also been presented. [PERSON] et al. [29] summarized the state of the art of connected vehicles from the need for vehicle data, applications, enabling technologies, and challenges. [PERSON] and [PERSON] [35] reviewed cooperative intersection management where road users, infrastructure, and traffic control centers can communicate and coordinate traffic safely and efficiently. Their paper includes methods for both signalized and nonsignalized intersections with emphasis on nonsignalized intersections. [PERSON] et al. [36] provided a review in the area of autonomous overtaking. The authors showed that the two essential aspects of high-speed overtaking are vehicle dynamics and environmental constraints, as well as accurate knowledge of the environment and surrounding obstacles. [PERSON] et al. [37] provided a survey on localization techniques using onboard sensing systems and their combinations with V2V and V2I systems for autonomous vehicles and investigated their applicability.