## 1 Introduction
### Related Works  
There are many research directions in outdoor VLC. In [7; 8; 9], [PERSON] et al. verified the feasibility of VLC in vehicular networks and ITS and also did some hardware experiments and prototype system simulations. In [10], [PERSON] et al. improved their previous work and presented a cooperative vehicular traffic scenario. Similarly, [PERSON] et al. also investigated cooperative communication between vehicles and road infrastructure and demonstrated that the proposed device is suitable for transmitting data using VLC technology [11]. In [12], [PERSON] et al. investigated a hybrid communication system based on VLC and radio frequency (RF). The system can provide location-based services as well as improve the broadcasting downlink efficiency of the traffic broadcast system. In [13; 14], [PERSON] et al. studied the effect of realistic optical interference on vehicular VLC and proposed different models for analyzing the performance of VLC systems. In [15; 16], [PERSON] et al. investigated reflecting intelligent surfaces (RISs)-assisted vehicular VLC. The application of optical RIS can overcome the practical limitation of LOS blockage in V2V-VLC and enhance the reliability of transmission. In [17; 18], [PERSON] et al. introduced the application and development of V2V-VLC, utilizing Multiple-Input Multiple-Output (MIMO). In addition, they analyzed the effect of lateral movement of the vehicle and refracted light on the system. In [19], [PERSON] et al. studied the effect of using different lens combinations on vehicular VLC systems in outdoor environments. In addition, there are many other research directions in vehicular VLC, such as system architecture [20; 21; 22], signal modulation and demodulation methods [23; 24; 25], multi-user networks [26; 27], MAC layer protocols [28], angle diversity reception [29], etc. Among the numerous research directions of VLC, one of the important research issues is to develop realistic outdoor VLC channel models for analyzing various performance metrics of vehicular VLC networks. To this end, some efforts have been made in [30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40]. From the perspective of VLC scenarios, in [30], [PERSON] et al. performed channel modeling and performance analysis of I2V-VLC, and also focused on the performance of I2V-VLC systems with access points in the form of streetlights, and derived an approximate closed-form bit error rate (BER) expression. In [31], to study ITS suitable for road safety applications, [PERSON] et al. used the Lambertian radiation model to model the VLC channel and implemented hardware system simulation using two development kits in field programmable gate array (FPGA). In [32], unlike the general studies using PDs as Rx, [PERSON] et al. employed an image sensor-based Rx for vehicle VLC and simultaneously performed optical flow measurements for vehicles in three VLC scenarios: I2V, V2I, and V2V. Moreover, most of the existing studies are based on V2V-VLC scenarios. In [33; 34], [PERSON] et al. derived a system model for V2V-VLC and conducted a performance evaluation study using empirical data obtained from real-world or measured headlight beam models. The results show that the existing optical channel models cannot accurately estimate the system channel behavior. In [35; 36; 37], [PERSON] et al. focused on the effect of fog and rain on V2V-VLC performance. In [35], experimental demonstrations on V2V-VLC under fog conditions were conducted and a solution to effectively alleviate the effects of fog by using Fresnel lenses and multiple PDs was proposed. However, the authors only simulated and analyzed the hardware system without giving the channel modeling. In [36], [PERSON] et al. quantified the performance of the V2V-VLC link using the ray tracing optical design software Zemax(r). The proposed link used car high beams as Txs under clear weather, rain, and fog conditions.