# INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications

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## Abstract

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## 1. Introduction

- 1
- We propose a highly scalable bi-directionally coupled integrated simulator that incorporates the analytical model of C-V2X LTE-V release 14 communication standard in the INTEGRATION traffic simulator.
- 2
- In the proposed integrated simulator, we used the spatial notion of density (see Section 5.3) for calculating the traffic density, which is a generalization of the linear notion of traffic density. We generalize the assumption in the analytical model [3] where vehicles are equally spaced and the traffic density is fixed in the highway scenario (as density was assumed to be the inverse of the inter-vehicle distance).
- 3
- We developed a scalable implementation by applying the techniques of vectorization and precomputations of different values used in the calculation of the Packet Delivery Ratio (PDR) at predefined distances, using FORTRAN programming language which is much faster than Matlab (the original implementation).
- 4
- We further enhance the computational time by utilizing a highly scalable, accurate, and efficient spatial index for two important tasks: (1) storing, retrieving, and updating vehicle positions, and (2) searching for vehicles around a given point within a specified range. The spatial index allowed us to track, during the simulation, the position of hundreds of thousands of vehicles at a 10 Hz frequency. In addition, using the spatial index, we managed to find only the vehicles that will be in communication range and could receive the message of a transmitting vehicle. Thus, the PDR calculations are computed for those vehicles only, instead of all vehicles in the road network.

## 2. Related Work

## 3. Analytical Communication Model

## 4. The INTEGRATION Traffic Simulator

#### 4.1. Traffic Modeling Levels

#### 4.2. Simulator Basic Concept

**Vehicle Departures:**It creates individual vehicle trip departures based on an aggregate time-varying origin–destination (OD) matrix.**Traffic Assignment:**It moves vehicles onto subsequent links using ten different traffic assignment methods. Traffic assignment establishes the chain of links that connects the trip origin to its destination while balancing traffic congestion in the network.**Longitudinal Vehicle Motion:**It moves vehicles along links based on desired speeds for each candidate distance headway tempered by prevailing vehicle dynamics and collision avoidance constraints that are only invoked when the lead vehicle is traveling slower than the following vehicle and the following vehicle is relatively close to the lead vehicle. Specifically, INTEGRATION uses the Rakha–Pasumarthy–Adjerid car-following model to capture the longitudinal movement of the vehicles [16]. Vehicle movement is constrained by a vehicle dynamic model described in [17].**Lateral Vehicle Motion:**It considers vehicle discretionary lane changing in selecting lanes that maximizes their speed. This model captures biases to stay on the rightmost lane and pass on the left. In mandatory lane changing, vehicles must be in specific lanes in order to follow their path and comply with lane restrictions [18].

## 5. Integrated Simulator

#### 5.1. Simulator Architecture

#### 5.2. Vehicle Position Database

#### 5.2.1. Range Query

#### 5.2.2. Update Vehicle Positions

#### 5.3. Modified Analytical Communication Model

#### Dynamic Density Calculation

#### 5.4. Bidirectional Dynamic Coupling

#### 5.5. Large-Scale Implementation

#### 5.6. Spatial-Temporal Analysis

## 6. Results and Discussion

#### 6.1. QNET Network Layout

#### 6.2. QNET Results

#### 6.3. Downtown LA Network Layout

- Free-flow speed: HERE GIS files using speed class
- Speed-at-capacity: empirical data
- 80% free-flow speed
- Base saturation flow rate: Highway Capacity Manual

#### 6.4. Downtown LA Results

## 7. Summary and Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## Abbreviations

PDR | Packet Delivery Ratio |

C-V2X | Cellular-Vehicle to everything |

DSRC | Dedicated Short Range Communication |

VNS | Vehicular Network Simulator |

LMP | Level of Market Penetration |

CV | Connected Vehicle |

OD | Origin Destination |

## References

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**Figure 3.**Grid-cells-based index, adapted from [23].

**Figure 11.**LA spatial analysis of PDR for the entire simulation period. Green cells have high PDR and red cells have low PDR. Yellow cells have in-between PDRs.

Integrated Simulator | Simulation Scale | Network Simulator | Comm. Standard | Vehicle Positions | Traffic Simulator | Simulator Coupling | Spatial Analysis |
---|---|---|---|---|---|---|---|

Proposed | Large scale | Analytical model | Direct C-V2X | Grid cell and update index | INTEGRATION | Dynamic interval | Yes |

VNS [9] | Large scale | NS-3 | DSRC (802.11b) | Quad Tree | DIVERT | Fixed interval | No |

VEINS [4] | Small scale | OMNET++ | IEEE 802.11b | NA | SUMO | Fixed interval | No |

Open C-V2X [5] | Small scale | OMNET++ | C-V2X | NA | SUMO | Fixed interval | No |

Open Source C-V2X [6] | Medium Scale | NS-3 | C-V2X | NA | SUMO | Fixed interval | No |

VNetIntSim [2,7] | Medium scale | OPNET | IEEE 82.11g | NA | INTEGRATION | Fixed interval | No |

Elbery [10,11] | Large scale | Analytical model | DSRC (IEEE 802.11p) | NA | INTEGRATION | Fixed interval | No |

IDCVS [8] | Large scale | OMNET++ | DSRC (IEEE 802.11p) | NA | SUMO | Fixed interval | Yes |

Road Network | Simulation Time | Number of Vehicles | Execution Time | |
---|---|---|---|---|

Proposed system | Downtown LA. Area 133 km${}^{2}$. A total of 1624 nodes, 3556 links, and 457 traffic signals | 1.8 h | 145,000 vehicles with a maximum of 30,000 concurrent vehicles | 1.5 h |

Elbery [10,11] | Downtown LA. Area 133 km${}^{2}$. 1625 nodes, 3561 links, and 459 traffic signals (42 RSUs) | 8.3 h | 563,626 vehicles with a maximum of 30,000 concurrent vehicles | 8.3 h |

VNS [9] | Road network of city of Porto | 40 min | 130,000 vehicles with a maximum of 15,000 concurrent vehicles | 7 h |

VNetIntSim [2,7] | An intersection and four zones. Each zone serves as a vehicle origin and destination location. Each road link is 2 km long | Not reported | 3000 vehicles with 180 concurrent vehicles | Not reported |

Open Source C-V2X [6] | A 100 m × 100 m intersection, and an urban Manhattan grid scenario as used by 3GPP (750 m × 1299 m). | 30 s | 250 vehicles | Not reported |

Open CV2X [5] | A 2700 m six-lane highway section, lane width of 4 m, vehicular speeds of 140 km/h (70 km/h). The inter-vehicle distance of 2.5 s × maximum speed. | Not reported | 200 (380) vehicles in the simulation at its most dense stage | Not reported |

VEINS [4] | Single-lane Manhattan Grid with intersections spaced 1 km apart. Grid sizes 5 × 5 roads and 16 × 16 roads | Not reported | 30 and 1000 vehicles | Not reported |

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**MDPI and ACS Style**

Farag, M.M.G.; Rakha, H.A.; Mazied, E.A.; Rao, J. INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications. *Sensors* **2021**, *21*, 2127.
https://doi.org/10.3390/s21062127

**AMA Style**

Farag MMG, Rakha HA, Mazied EA, Rao J. INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications. *Sensors*. 2021; 21(6):2127.
https://doi.org/10.3390/s21062127

**Chicago/Turabian Style**

Farag, Mohamed M. G., Hesham A. Rakha, Emadeldin A. Mazied, and Jayanthi Rao. 2021. "INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications" *Sensors* 21, no. 6: 2127.
https://doi.org/10.3390/s21062127