Performance Analysis of Intelligent Transportation Systems

Performance Analysis of Intelligent Transportation Systems

Implementation plan:

Step 1: Initially, we will construct a Network with 50 Vehicles, 2 – RSU and 1 Edge Server.

Step 2: Then, we collect the 1Hz GPS Tracking data and use Synthetic Minority Over-Sampling Technique (SMOTE) to clean and balance the data.

Step 3: Next, we train the data using FedTOP-A3C (Federated Trust-Optimized Proximal Actor-Critic) with Proximal Policy Optimization (PPO).

Step 4: Next, we detect anomalous data using Adaptive Threshold iForest (AT-iForest) technique.

Step 5: Next, we secure the data using Chinese Remainder Theorem (CRT), and Paillier encryption with Zone-Based Service Provisioning (ZBSP) dynamic shifting.

Step 6: Next, we schedule the tasks dynamically using Emergent Intelligence (EI) technique to efficiently balance the loads.

Step 7: Next, we optimize the data using Constraints aware Federated learning with Min-Max Optimization technique.

Step 8: Next, we route the communication network Edge-based fast decision-making (EFD) with Genetic Algorithm-based Optimal Route Planning (GA-ORP) to reduce latency.

Step 9: Finally, we plot performance for the following metrics:

9.1: Number of vehicles vs. Packet Delivery Ratio (%)
9.2: Number of vehicles vs. Throughput (Mbps)
9.3: Number of vehicles vs. Latency (ms)
9.4: Number of epochs vs. accuracy (%)
9.5: Number of epochs Vs. Precision (%)

Software Requirements:

1. Development Tool: OMNeT++ 4.6 or above with veins
2. Operating System: Windows 10 (64-bit) or above

Note:

1) If the plan does not meet your requirements, provide detailed steps, parameters, models, or expected results in advance. Once implemented, changes won’t be possible without prior input; otherwise, we’ll proceed as per our implementation plan.

2) If the plan satisfies your requirement, Please confirm with us.

3) Project based on Simulation only, not a real time project.

4) Please understand that any modifications made to the confirmed implementation plan will not be made after the project development.

We perform with an Existing Approach Reference 4: Title: A Vehicular Fog Computation Platform for Artificial Intelligence in Internet of Vehicles

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