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Intelligent Road Management System for Vehicles: Comparison
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Please note this is a comparison between Version 2 by Catherine Yang and Version 1 by awad bin Naeem.

Autonomous vehicles, non-autonomous vehicles, and VIP (emergency) autonomous cars are using intelligent road management techniques to interact with one another and enhance the effectiveness of the traffic system. All sorts of vehicles are managed and under control using the intersection management unit approach. 

  • autonomous vehicles
  • non-autonomous vehicle
  • VIP vehicle

1. Introduction

In the modern era, autonomous and non-autonomous vehicles are converting and implementing intelligent road management methods to interact with other vehicles to increase traffic system efficiency. Intersection management units are a system for dealing with and regulating all types of traffic [1]. The computer system design of our commercial autonomous cars is presented in this study, together with thorough performance, energy, and cost assessments. This article has two goals based on our commercial deployment experience. 
The transport management system consists of the few critical components. Routes, transportation, building, and hiring are all aided by a city’s road network, making roads a critical component of every prosperous metropolis. They are also very important in helping to alleviate poverty. The upkeep of roads and other urban infrastructure, such as sidewalks, is now under scrutiny by academics and local officials. The number of years a road has served its intended purpose may be used to estimate its remaining pavement life cycle. The condition of local roads is essential to citizens’ daily life; hence, it is important that this topic receive sufficient attention in educational curricula [4][2].
Soft computing approaches are used in the design and implementation of intelligent evacuation algorithms for crowd control management. Deep reinforcement learning (DRL) is used to learn complex rules in high-dimensional settings, while autonomous vehicle (AV)-based Intelligent Transportation Systems (ITS) offer a great playing ground for policy-driven DR [5][3].
This research focuses on all types of autos in the transportation system, where VIP vehicles join the road and disrupt the whole system. Accidents are a common occurrence in the road system. Junctions account for 40% of all traffic accidents and more than 80% of all road delays. This reduces traffic congestion, reduces the number of cars on the road, and improves road safety. There are various methods for managing junctions, each with its own set of features, restrictions, benefits, and downsides. In the recent age, most of the VIP vehicles makers are from developed nations like the USA, China, Korea, Germany, Italy and the UK, and they have been using quantum computing for industrial manufacturing as zero factory concepts where the VIP vehicles have a better managed inventory; PMA and OEM characteristics are managed in the upcoming quantum computing capabilities.
Autonomous and non-autonomous vehicles, as seen in the road and transport management systems, can be supported by “quantum computing for industrial management” and the “quantum communication theory” in today’s age of technology and quantum computing. Work with quantum computers continues to advance at major automakers including Mercedes, Audi, and the Volkswagen Group. Adopting the quantum computer, they have developed a traffic management system that will replace forecasting for urban traffic volumes, transport demand, and travel times with precise calculations. This is a first for the transportation management and road management systems for the autonomous vehicles. To cut down on customer wait times, public transit agencies, taxi services, and other transport management service providers may more effectively deploy their fleets. Conventional supercomputers cannot compete with the speed at which quantum computers can handle problems like traffic planning. Quantum computers may be the sole option for solving some problems. Automakers believe that there is significant opportunity in using this cutting-edge computer technology to create innovative internal applications and commercial models [5,6][3][4].

2. Intelligent Road Management System for Autonomous, Non-Autonomous, and VIP Vehicles

Conditional automation (TOR) allows human drivers to delegate driving dynamic tasks (DDT) to automated driving systems (ADS) and only be ready to regain control in emergencies It also compiles standards and guidelines for autonomous driving, discusses techniques and limitations, and provides conclusions. In Singapore, the DART system addresses the capacity gap between existing Mass Rapid Transit (MRT) and bus systems by integrating fully autonomous vehicle modules into a high-tech, environmentally friendly, and effective system architecture [7][5]. The authors consider various elements, such as bicycles, pedestrians, public transit indications, shared space, bike lanes, public transit networks, segmentation of modes of transportation, reduced trip time and distance, policy changes, and technological innovation [8][6]. A framework for message broadcasting, intelligent traffic signal control (STSC), and adaptive traffic signal control (ATSC) is proposed for various transportation applications in smart cities [10][7]. A new traffic signal design is created specifically for the E.V.S.P scenario, allowing motorists passing through the intersection of the direction of the emergency assistance vehicle (EAV) [11][8]. V2X correspondences (ITS) are a novel paradigm for intelligent transportation systems with AI-targeted artificial neural networks being assessed for reducing or eliminating traffic volume when non-autonomous vehicles participate in mixed traffic flow circumstances in South Africa [12][9]. This research aims to demonstrate framework flexibility and accommodate multiple moving machine components using simple linkages. Autonomous vehicles are popular due to their safety and efficiency, but unresolved safety issues remain unresolved. Joint analysis of these vehicles’ security and safety is lacking [13][10]. Before they may be used extensively, autonomous vehicle manufacturers must overcome a significant moral quandary: ethical algorithmic performance [14][11]. Similar to other inevitable catastrophes, fundamental dynamic situations in which at least two or more lives are at risk are offered to autonomous vehicles. Moral conundrums occur in certain situations, such as whether to give one’s life to save further fatalities [15][12]. People’s lives are categorized using algorithms based on predetermined standards. This approach uses deletion, insertion, and other operations to prioritize between nodes with various properties. BST is treated as a crucial queue and is placed in a priority queue. In this calculation, the likelihood of survival is also referred to as the probability of endurance. Customers and automakers may now create moral decisions based on their values by introducing an adaptable and unstable algorithm [16][13]. Because of the increased need for mobility, the transport infrastructure has experienced significant changes. Inefficiencies result in large time losses, a decrease in pedestrian and vehicular safety, high levels of pollution, and a decrease in quality of life. The purpose of this essay is to provide cutting-edge capabilities for training automobiles as well as controlling traffic and safety jointly [17][14]. This will be accomplished by designing the proposed functionality, which will include, at a high level, (1) sensor networks made up of nearby vehicles exchanging traffic-related information throughout the transportation infrastructure. The objective of the three basic sections listed above is to offer drivers and the transportation system as whole instructions that are useful for controlling context. [18][15]. The sensors put on roadway surfaces by MTM’s traffic innovations were used to filter and manage the daily passing traffic at the traffic counter [19][16]. The phrase ITS refers to a group of technologies that may improve transportation system management, public transit, and individual travel choices [20][17]. ITS includes modern automated technologies that seek to improve the convenience, efficacy, and safety of surface transportation. Even though it is not one of the primary goals of ITS, reducing energy usage has been proven to be beneficial in some cases. The Intelligent Transport System (ITS) is becoming more and more crucial and necessary for a nation as a result of the quickening pace of current economic and technological growth [22][18]. The reality is that depending only on the growth and building of transport infrastructure does not fundamentally resolve the current transport issues and sometimes makes them worse. Therefore, every nation is currently researching ITS technology to address traffic issues [23][19]. The amount of ITS and research fields development, however, varies owing to the diverse money investment conditions, current technical merit, and various traffic difficulties for each nation. To create an integration model, this study combines the ITS technologies and focuses on comparing and analyzing worldwide ITS research. The communication of technology should be improved, and ITS methods should be updated and improved [24][20]. Transportation systems in modern civilization face substantial issues, such as traffic congestion. Technology for communication and information is becoming more important in modern transportation networks. Automakers are developing in-vehicle sensors for use in several applications, including recreation, traffic management, and safety [25][21]. Government agencies have put in place roadside infrastructure, such as cameras and sensors, to collect weather and traffic data. It is feasible to develop intelligent and smart transportation systems by seamlessly integrating automobiles and sensing equipment and using their detecting and communication capabilities [26][22].

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