SPAS: Smart Pothole-Avoidance Strategy for Autonomous Vehicles

Raja, Gunasekaran; Anbalagan, Sudha; Senthilkumar, Senbagapriya; Dev, Kapal; Qureshi, Nawab Muhammad Faseeh

doi:10.1109/tits.2022.3161589

Cited by 15 publications

(5 citation statements)

References 38 publications

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“…Authors [28] proposed a novel self-adaptive framework for detecting black hole and wormhole attacks in WSN using a modified AODV protocol for 6LoWPAN (low-power wireless personal area networks). Authors [29] proposed a novel SPAS algorithm using DDPG and HRM-SG for real-time audio and video generation and used this for predating driver's comfort in lane changing, speed, and others to achieve accuracy in pothole avoidance. The existing approaches failed to address the following issues:…”

Section: Related Workmentioning

confidence: 99%

Enhancing VANET Security: Efficient Communication and Wormhole Attack Detection using VDTN Protocol and TD3 Algorithm

2024

KSII TIIS

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Due to the rapid evolution of vehicular ad hoc networks (VANETs), effective communication and security are now essential components in providing secure and reliable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. However, due to their dynamic nature and potential threats, VANETs need to have strong security mechanisms. This paper presents a novel approach to improve VANET security by combining the Vehicular Delay-Tolerant Network (VDTN) protocol with the Deep Reinforcement Learning (DRL) technique known as the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. A store-carry-forward method is used by the VDTN protocol to resolve the problems caused by inconsistent connectivity and disturbances in VANETs. The TD3 algorithm is employed for capturing and detecting Worm Hole Attack (WHA) behaviors in VANETs, thereby enhancing security measures. By combining these components, it is possible to create trustworthy and effective communication channels as well as successfully detect and stop rushing attacks inside the VANET. Extensive evaluations and simulations demonstrate the effectiveness of the proposed approach, enhancing both security and communication efficiency.

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Section: Related Workmentioning

confidence: 99%

Enhancing VANET Security: Efficient Communication and Wormhole Attack Detection using VDTN Protocol and TD3 Algorithm

2024

KSII TIIS

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“…where κ is the soft update factor. Of course, what deserves more attention is the design of the reward function, which has been shown in many simulation experiments [38], [39] using the DDPG algorithm to be related to the goodness of the final decision.So we formulate the reward function as (34) and (35),where β, ζ 1 , ζ 2 , ζ 3 and ζ 4 represent the coefficients and their specific values will be set according to different conditions.…”

Section: A Ddpg Algorithm Based On Noma Systemmentioning

confidence: 99%

“…And the probabilities corresponding to the actions obtained by sampling can be denoted as ρ old,i and ρ new,i , respectively. We can then obtain the loss value function for updating the new-actor network, which can be expressed as (38), where ε is the clipping factor. And, ρ new (r i |s i ) and ρ old (r i |s i ) denote the probability that the new actor network and the old actor network in the i-th time slot give out the action as r i based on the channel stat s i , respectively.Since the PPO algorithm introduces a clipping factor, it is easier to converge and update the network more stable than the DDPG algorithm.…”

Section: B Ppo Algorithm Based On Noma Systemmentioning

confidence: 99%

Energy-Efficient Transmission Strategy for Delay Tolerable Services in NOMA-Based Downlink With Two Users

Bai,

Zhu,

Guo

et al. 2023

IEEE Access

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With the continuous development of the communication industry, there is a shift in real-time services from 4G networks to Delay Tolerable (DT) services in the context of 5G/B5G networks. Additionally, energy consumption control poses significant challenges in the current communication industry. Therefore, we study algorithms and schemes to improve the Energy Efficiency (EE) of DT services in the context of Non-Orthogonal Multiple Access (NOMA) downlink two-user communication system.First, we transformed the EE enhancement problem into a convex optimization problem based on transmission power by derivation. Secondly, we propose to use Approximate Statistical Dynamic Programming (ASDP) algorithm, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) to solve the problem that convex optimization cannot be decided in real time. Finally, we perform an interpretability analysis on whether the decision schemes of the agents trained by the DDPG algorithm and the PPO algorithm are reasonable. The simulation results show that the decisions made by the agent trained by the DDPG algorithm perform better compared to the ASDP algorithm and the PPO algorithm.

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“…The emergence of various intelligent on-vehicle applications in the Internet of Vehicles (IoV), such as autonomous driving, online games, augmented reality, intelligent guidance of traffic behavior, and voice-based dynamic human-vehicle interaction, makes resourceconstrained vehicles face significant challenges in supporting these intelligent services [1][2][3][4][5]. Vehicular Edge Computing Networks (VECNs) extend computation capability to the edge of the wireless network by providing additional computation resources close to mobile vehicles, which can ease the burden on vehicles.…”

Section: Introductionmentioning

confidence: 99%

Multi-User Computation Offloading and Resource Allocation Algorithm in a Vehicular Edge Network

Liu,

Zheng,

Zhang

et al. 2024

Sensors

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In Vehicular Edge Computing Network (VECN) scenarios, the mobility of vehicles causes the uncertainty of channel state information, which makes it difficult to guarantee the Quality of Service (QoS) in the process of computation offloading and the resource allocation of a Vehicular Edge Computing Server (VECS). A multi-user computation offloading and resource allocation optimization model and a computation offloading and resource allocation algorithm based on the Deep Deterministic Policy Gradient (DDPG) are proposed to address this problem. Firstly, the problem is modeled as a Mixed Integer Nonlinear Programming (MINLP) problem according to the optimization objective of minimizing the total system delay. Then, in response to the large state space and the coexistence of discrete and continuous variables in the action space, a reinforcement learning algorithm based on DDPG is proposed. Finally, the proposed method is used to solve the problem and compared with the other three benchmark schemes. Compared with the baseline algorithms, the proposed scheme can effectively select the task offloading mode and reasonably allocate VECS computing resources, ensure the QoS of task execution, and have a certain stability and scalability. Simulation results show that the total completion time of the proposed scheme can be reduced by 24–29% compared with the existing state-of-the-art techniques.

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SPAS: Smart Pothole-Avoidance Strategy for Autonomous Vehicles

Cited by 15 publications

References 38 publications

Enhancing VANET Security: Efficient Communication and Wormhole Attack Detection using VDTN Protocol and TD3 Algorithm

Enhancing VANET Security: Efficient Communication and Wormhole Attack Detection using VDTN Protocol and TD3 Algorithm

Energy-Efficient Transmission Strategy for Delay Tolerable Services in NOMA-Based Downlink With Two Users

Multi-User Computation Offloading and Resource Allocation Algorithm in a Vehicular Edge Network

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