Autonomous driving is a rapidly developing technology that also source of debate. People believe autonomous vehicles will provide better future by increasing road safety, lowering infrastructure expenses, and improving mobility for children, the old, disabled. On other hand, many individuals are concerned about incidences automotive hacking, likelihood fatal crashes, loss driving-related professions. is, without question, complex problematic people. To comprehend how safe self-driving cars...

Autonomous vehicles (AVs) are predicted to change transportation; however, it is still difficult maintain robust situation awareness in a variety of driving situations. To enhance AV perception, methods integrate sensor data from the camera, radar, and LiDAR sensors have been proposed. However, due rigidity their fusion implementations, current techniques not sufficiently challenging scenarios (such as inclement weather, poor light, obstruction). These can be divided into two main groups:...

To enhance the level of autonomy in driving, it is crucial to ensure optimal execution critical maneuvers all situations. However, numerous accidents involving autonomous vehicles (AVs) developed by major automobile manufacturers recent years have been attributed poor decision making caused insufficient perception environmental information. AVs employ diverse sensors today’s technology-driven settings gather this due technical and natural factors, data collected these may be incomplete or...

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle plays a crucial role urban planning and management of Intelligent Transportation Systems (ITS). Several approaches have been proposed literature to address this problem. However, resulting detection accuracy still not adequate. This paper proposes efficient approach uses deep learning concepts correlation filters for multi-object tracking. The performance system evaluated...

Higher-level autonomous driving necessitates the best possible execution of important moves under all conditions. Most accidents in recent years caused by AVs launched leading automobile manufacturers are due to inadequate decision-making, which is a result their poor perceivance environmental information. In today’s technology-bound scenarios, versatile sensors used collect Due various technical and natural calamities, information acquired may not be complete clear, misinterpret different...

In recent years, several software and hardware solutions have been proposed for object detection, motion tracking, gesture identification. However, these failed to efficiently identify appropriate gestures track their in a stipulated time range. To overcome the above-mentioned challenges, we propose novel sign language translator application, which uses MediaPipe Holistic model along with Long Short-Term Memory (LSTM), integrated Neural Network (NN) build model. This will pick up from...

Intelligent Transportation system (ITS) aims to improve traffic safety, transportation efficiency and driving experience. To ensure the importance of safety mechanism in ITS, this study has established a simulated vehicular environment analyze two cases. Vehicular data collected from different regions Abu Dhabi are analyzed with simulators which executes (or) without mechanism. Map related using OpenStreetMap. Simulation is SUMO. Message forwarding execution simulation done OMNet++.

Autonomous driving of higher automation levels asks for optimal execution critical maneuvers in all environments. The crucial pre-requisite such decision-making instances is accurate situation awareness the automated and connected vehicles. For this, vehicles rely on sensory data captured from onboard sensors information collected through V2X communication. classical on-board exhibit different capabilities hence a heterogeneous set required to create better situational awareness. Fusion...

Modern technologies like digital spaces, intelligent transportation, and operations are faced with technical challenges related to data capturing, processing, storage, security, communication, etc. Ensuring security reliable message propagation among autonomous vehicles is a major challenging task. Establishing appropriate environment for developing vehicular-based solutions by the vehicle manufactures increases their estimated cost time. Hence, minimize this problem, proposal aims introduce...

Efficient routing to guide the vehicles reach their destinations is a challenging problem in vehicular networks. Many solutions have been proposed literature address However, most of these are graph-based and do not properly dynamic characteristics This paper proposes two novel heuristic algorithms based on Tabu search Neural Networks. The evaluated findings presented using UK RTA roadside dataset. Experimental results along with comparative analysis made other related studies provided prove...

Abstract Higher-level autonomous driving necessitates the best possible execution of important moves under all conditions. Most accidents in recent years caused by AVs launched leading automobile manufacturers are due to inadequate decision-making their poor perceivance environmental information. In todays, technology-bound scenarios, versatile sensors used collect Due various technical and natural calamities, information acquired may not be complete clear, which misinterpret a different...

This paper presents an automated learning process to train the mountain car game model. It proposes Enhanced Dyna-QPC model effectively in stipulated time, based on their perceived environmental conditions. Decision Tree (DT) classification along with Neural Network (NN)) is used this research frame decision rules and self-train respectively. Discrete Finite Deterministic Automata (DFA) concepts are included finalize state transition of training Moreover, Erdos-Renyi Random graph-generating...