# Selecting Remote Driving Locations for Latency Sensitive Reliable Tele-Operation
## 2 Background and Literature Review  
In this section, we briefly discuss the historical perspectives, related works, and issues with remote driving systems. In a remote driving environment, a driver controls a vehicle through tele-operation. In order to control a vehicle in real time, real-time data transmission is needed, which exploits today's networking infrastructure. Latency is a crucial factor for secure and reliable driving. In the following, we describe many related works showing the feasibility of remote driving under the current communication infrastructures such as LTE and Wi-Fi. A truly autonomous vehicle was first suggested by [PERSON] at Japan Tsukuba Mechanical Engineering Laboratory [9]. The vision of \"future highway\" for autonomous vehicles has been proposed back in 1960 to 1975 by Radio Corporation of America (RCA) [10]. Because of the remarkable benefits, local governments and several automobile manufacturers have invested in growing self-driving automobiles since 1977. These days, autonomous vehicles have mature hardware capabilities to allow absolute self-driving, but the driving emphalgorithms are still immature. In Figure 1, the adoption timeline for autonomous vehicles has been given [9]. A luxury automobile has approximately a hundred million lines of software program code, whilst the RF-22 Raptor fighter aircraft has 1.7 million [11]. In what are known as \"disengagement reports\", self-driving cars with large base software code have been confirmed to have 2578 failures. These findings have been compiled by using nine corporations that carried out self-driving car avenue checks in 2016 [12]. A variety of cutting-edge technologies are needed to ensure that everything works together smoothly such as localization, mapping, perception, machine learning, planning, networking, dispatch and routing, and controls [8; 14]. In other words, these features are needed to recognize the world around the car and make decisions for the better driving. We summarize these features in Figure 2. As can be clearly seen in Figure 2, software is at the heart of the self-driving abilities. However, software inevitably contains bugs. To overcome the problems caused by the software bugs, researchers explore special strategies to involve human beings within the control loop to manipulate diverse gadgets until the software in autonomous cars is sufficiently capable of preventing fatal failures. One example of such fatal failures is the crash happened on a divided toll road with a horizontal line [15]. According to the official accident report, cameras and radar are used by the autopilot to track and avoid obstacles, and the cameras were unable to discern \"the white side of the tractor trailer against a brightly lit sky\". The radar should have detected the trailer without issue, but, according to [PERSON], \"radar tunes out what appears to be an overhead road sign to stop false braking events\". Remote driving can be implemented through high speed communication networks. Huawei, China Mobile, and SAIC Motor have demonstrated 5G-based vehicles. In a remote driving test, the driver was 30 km away from the automobile and the latency for control functions was 10 ms [6]. Telefonica and Ericsson also confirm remote driving as a reality, where they ensure the reliability of driving a car located 70 km away through 4K videos using sensory perception [16]. The researchers have peered into the future of tele-operated devices, examining device architecture while considering network delay as a primary constraint. A previous research  
Figure 1: Adoption timeline for autonomous vehicles [13]. Figure 2: Technologies used in AVs. found that the major factor that affects remote driving efficiency is the magnitude and the variability of the feedback [17]. A delay of 170 ms has been found a minor impact on remote driving efficiency [18]. As the delay reaches 700 ms, driving performance suffers significantly.