An Efficient Driver Selection Algorithm for Controlling Multiple Vehicles in Remote Driving

Zulqarnain, Syed Qamar; Lee, Sanghwan

doi:10.1109/icoin50884.2021.9333930

Cited by 5 publications

(8 citation statements)

References 11 publications

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“…One interesting concept which can help circumvent this challenge is the use of remote driving [103][104][105] and remote testing [102] procedures. Remote driving can be seen as an augmentation of autonomous driving.…”

Section: Prospective Solutionsmentioning

confidence: 99%

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Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

Njoku

Nwakanma

Amaizu

et al. 2022

IET Intelligent Trans Sys

132

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The Metaverse is a concept used to refer to a virtual world that exists in parallel to the physical world. It has grown from a conceptual level to having real applications in virtual reality games. The applicability of the Metaverse in numerous sectors like marketing, education, social, and even advertising exists. However, there exists little or no work on Metaverse applicability to the transportation industry. Data‐driven intelligent transportation systems (DDITS) aim to provide more intelligent systems based on exploiting data. This paper reviews the concepts and features of the Metaverse. Also, the review goes over three dominant DDITS challenges: vehicle fault detection and repair, testing new technologies, and anti‐theft systems. In addition, it highlights prospective Metaverse solutions that apply to the DDITS. Buttressing the utility of Metaverse in DDITS, this paper presents two major case studies: the invisible to visible (I2V) and the Metaverse on Wheels (MoW) technologies. Finally, the influence, limitations, and open issues of Metaverse applications to DDITS are discussed.

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Section: Prospective Solutionsmentioning

confidence: 99%

“…In [103], the authors show that there is room to improve the latency situation while driving remotely. [104] was concerned with increasing the efficiency of remote controllers in remote driving schemes. Metaverse allows remote access to and from a virtual environment [25].…”

Section: Prospective Solutionsmentioning

confidence: 99%

Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

Njoku

Nwakanma

Amaizu

et al. 2022

IET Intelligent Trans Sys

132

View full text Add to dashboard Cite

show abstract

“…Second, the work in [72] proposes a greedy approach to driver selection called Longest Advance First, where drivers are chosen according to the potential length of the segment they will cover and thus have fewer drivers in a trip. Finally, authors in the same team propose an algorithm called ''Remote Driver Selection for Multiple Paths'' in [73]. When compared to their greedy approach, the authors find a balance between latency and the number of required drivers to handle a Driving-as-a-Service operation.…”

Section: ) Human Factorsmentioning

confidence: 99%

“…The differences between physical and logical distances (e.g., network round-trip times) is one of the factors that affect scalability. The works in [71], [72], and [73] already consider that, for remote driving, a set of drivers has to take over the control of a vehicle at different times within one trip. This acquires more complexity when remote driving occurs between countries, even when data roaming is possible.…”

Section: Regulatory Challengesmentioning

confidence: 99%

A Survey on Remote Operation of Road Vehicles

2022

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In recent years, the use of remote operation has been proposed as a bridge towards driverless mobility by providing human assistance remotely when an automated driving system finds a situation that is ambiguous and requires input from a remote operator. The remote operation of road vehicles has also been proposed as a way to enable drivers to operate vehicles from safer and more comfortable locations. While commercial solutions for remote operation exist, remaining challenges are being tackled by the research community, who is continuously testing and validating the feasibility of deploying remote operation of road vehicles on public roads. These tests range from the technological scope to social aspects such as acceptability and usability that affect human performance. This survey presents a compilation of works that approach the remote operation of road vehicles. We start by describing the basic architecture of remote operation systems and classify their modes of operation depending on the level of human intervention. We use this classification to organize and present recent and relevant work on the field from industry and academia. Finally, we identify the challenges in the deployment of remote operation systems in the technological, regulatory, and commercial scopes.

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“…We then propose several algorithms to achieve the two objectives and evaluate the performance of the algorithms. We compare the proposed algorithms with some baseline algorithms and two preliminary algorithms proposed in [7,8], respectively. The contributions of the paper can be summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

Selecting Remote Driving Locations for Latency Sensitive Reliable Tele-Operation

Zulqarnain

Lee

2021

Applied Sciences

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These days, autonomous vehicles (AVs) technology has been improved dramatically. However, even though the AVs require no human intervention in most situations, AVs may fail in certain situations. In such cases, it is desirable that humans can operate the vehicle manually to recover from a failure situation through remote driving. Furthermore, we believe that remote driving can enhance the current transportation system in various ways. In this paper, we consider a revolutionary transportation platform, where all the vehicles in an area are controlled by some remote controllers or drivers so that transportation can be performed in a more efficient way. For example, road capacity can be effectively utilized and fuel efficiency can be increased by centralized remote control. However, one of the biggest challenges in such remote driving is the communication latency between the remote driver and the vehicle. Thus, selecting appropriate locations of the remote drivers is very important to avoid any type of safety problem that might happen due to large communication latency. Furthermore, the selection should reflect the traffic situation created by multiple vehicles in an area. To tackle these challenges, in this paper, we propose several algorithms that select remote drivers’ locations for a given transportation schedules of multiple vehicles. We consider two objectives in this system and evaluate the performance of the proposed algorithms through simulations. The results show that the proposed algorithms perform better than some baseline algorithms.

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An Efficient Driver Selection Algorithm for Controlling Multiple Vehicles in Remote Driving

Cited by 5 publications

References 11 publications

Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

Prospects and challenges of Metaverse application in data‐driven intelligent transportation systems

A Survey on Remote Operation of Road Vehicles

Selecting Remote Driving Locations for Latency Sensitive Reliable Tele-Operation

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