Modern vehicles are no longer just machines on wheels. Through Vehicle-to-Everything (V2X) communication , they are becoming active participants in intelligent transport systems, enabling safer driving, smoother traffic, and progress toward automation. DSRC: The First Step The earliest V2X technology was Dedicated Short-Range Communications (DSRC) , based on IEEE 802.11p. Operating in the 5.9 GHz band , it allowed onboard units (OBUs) in vehicles to exchange safety and infotainment data with roadside units (RSUs) . While DSRC was effective for short-range messaging, it faced limits in coverage, data rate, and quality of service (QoS) . These challenges motivated researchers to explore new solutions. D2D and the Cellular Shift A key breakthrough came with Device-to-Device (D2D) communication , where vehicles exchange information directly without always relying on infrastructure. This reduces latency, eases network congestion, and helps maintain reliability in crow...

In the realm of connected vehicles, two primary technologies facilitate communication: Dedicated Short Range Communications (DSRC) and Cellular Vehicle-to-Everything (C-V2X) . While both aim to enhance road safety and traffic efficiency, they differ in several key aspects. This post delves into these differences, providing a clearer understanding of each technology's capabilities and applications. Key Differences Between DSRC and C-V2X Feature DSRC (IEEE 802.11p) C-V2X (3GPP LTE & 5G) Technology Standard Based on IEEE 802.11p (Wi-Fi-like) Based on 3GPP LTE & 5G (cellular-based) Communication Mode Direct V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) Direct (PC5) & Network-based (Uu) V2N (vehicle-to-network) Range Typically up to 300 meters Up to 1 km direct; longer via network Latency Very low, suitable for safety-critical messages Low, may vary depending on network conditions Deployment Requires dedicated short-range spe...

The complete source files for this analysis, including the NS-3 simulation script, the generated dataset, and the Python analysis notebook, are available for download. This allows for full reproduction of our results. You can access all the project files [ in our shared folder here ].

% Random Silent Period Algorithm - Multi-Vehicle Simulation with Overhead Estimation % Author: Abdulhameed Idris % Date: [Insert Date] % -------- Input Parameters -------- num_vehicles = 5; % Number of vehicles T_min = 5; % Min silent period (sec) T_max = 15; % Max silent period (sec) T_total = 60; % Total simulation time (sec) T_sys = 0; % System time % Communication overhead estimates (in bytes) IT_request_size = 100; IT_response_size = 120; blockchain_entry_size = 80; overhead = 0; % Total communication overhead % Initialize vehicle states silent_mode = true(num_vehicles, 1); T_silent = zeros(num_vehicles, 1); T_end_silent = zeros(num_vehicles, 1); % Assign random silent periods for i = 1:num_vehicles R_f = rand(); T_silent(i) = T_min + R_f * (T_max - T_min); T_end_silent(i) = T_sys + T_silent(i); end % -------- Simulation Loop -------- disp('Simulation Start'); while T_sys = T_end_silent(i) fprintf('\n...

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"CAD" stands for Comuter Aided Drawing. It helps in creating massive piles of drawings, as people love it since it has been absolutely great. As a starter, you can read more about it