## 5 Energy-Efficient Dynamic Routing Using C-V2X Communication
Figure 2 shows the resulting fitted curves using the PRR data and Equation (5). We can observe that the fitted PRR curves demonstrate the same behavior as the original data. There are many advantages of using PRR data in this way. First, the data were produced from a communication network simulator that was calibrated using real-world-connected vehicles data, thus providing the most high fidelity and accurate data. Second, this approach allows for running large-scale simulations of hundreds of thousands of vehicles in city-scale road networks in an efficient and reasonable time. This is in contrast to the other approach of using a communication network simulator, where the simulation time is very long due to the huge computation time of the communication network simulators, as it runs at the scale of milliseconds with a high level of details. Similarly, using an analytical communication model can save a huge amount of time but without the high fidelity and accurate results that are produced by a communication network simulator. Thus, our approach combines the advantages of both worlds: the high fidelity of the communication network simulators and the large scale and scalability of the analytical models. Figure 2: PRR of C-V2X communication fitted the data in the previous figure. During each time step in the simulation, the traffic simulator identifies for each transmitting vehicle the set of the receiving vehicles and their corresponding distances, as well as the vehicle density around each receiving vehicle in an efficient manner using a spatial index data structure. Using these two pieces of information, we used the PRR Equation (5) to compute the PRR value for each transmitting-receiving vehicle pair. We then draw a random value (0-1), and if the PRR value is bigger than the random value, then the message that contains the fuel consumption cost will be delivered. Otherwise, the message will be lost. For the C-EEDR application to work correctly, the road segment's fuel consumption cost needs to be communicated to a central server. Using C-V2X Vehicle-to-Infrastructure (V2I) technology, every vehicle that leaves a road segment transmits its fuel consumption cost on the road segment to the nearest Road-Side Unit (RSU) if there is one. We assume that the RSUs are capable of delivering the information to the central server (using fiber or wireless wide area connectivity). One important factor for the C-EEDR application is the placement of the RSUs. We chose to place the RSUs at the traffic signals to minimize the infrastructure cost. We modeled the problem of choosing the subset of the traffic signals as a set cover problem [21] and used a greedy algorithm to find the minimum number of traffic signals that maximize the coverage of all the traffic signals in the road network within a 500 m communication range. By placing the RSUs at the selected traffic signals, we guarantee that most of the road network will be covered by these RSUs and thus most of the vehicles will be able to transmit their information to the central server through one of these RSUs during their trip anywhere in the road network.