Vehicle-to-Vehicle Visible Light Communication （V2V-VLC） offers significant advantages in intelligent transportation systems， such as leveraging existing vehicular lighting， spectrum license exemption， low latency， and resistance to multipath interference. By transmitting critical information like vehicle position and driving instructions via LED light sources， V2V-VLC facilitates collaborative decision-making among vehicles. However， the open nature of optical transmissions exposes V2V-VLC to interception risks， leading to privacy breaches and traffic hazards. Current security measures primarily rely on higher-layer encryption and authentication， which fail to address vulnerabilities caused by physical-layer signal exposure. Physical Layer Security （PLS） complements existing methods by providing transparent protection across multiple data types. Yet， PLS research in VLC has been predominantly limited to static indoor environments， which are unsuitable for dynamic road scenarios characterized by high-speed mobility， variable topologies， and wide-beam light coverage. Particularly at intersections， extensive signal exposure and unpredictable eavesdropper locations exacerbate security risks.

This study proposes an Artificial Noise （AN） interference mechanism based on traffic infrastructure collaboration to minimize eavesdroppers' Signal-to-Interference-plus-Noise Ratio （SINR） under worst-case conditions， thereby enhancing V2V-VLC security. To improve the physical-layer security of V2V-VLC in dynamic road environments， a collaborative AN jamming scheme coordinated by traffic infrastructure was introduced. As illustrated in Fig. 2， the source vehicle （S） transmits confidential data to the target vehicle （D） via LED headlights， while the traffic signal （J） concurrently emits controlled artificial noise. The jamming signals are optimized to avoid interference with legitimate vehicles while disrupting eavesdroppers' reception. An optimization problem is formulated to minimize the worst-case SINR of eavesdroppers while maintaining the quality of legitimate communication. The concave-convex procedure （CCP） is employed to derive the optimal solution， ensuring effective suppression of eavesdropper signals and improving the system's secrecy rate without degrading communication performance. Simulations validate the proposed scheme's effectiveness in enhancing V2V-VLC security. Vehicle parameters are configured as follows： the source vehicle's LED headlights are mounted 0.8 m above the ground and spaced 1.6 m apart， while the receiver's photodetector （PD） is installed on the target vehicle's rear bumper， 0.8 m above the ground， with a field of view （FOV） of 60°. Detailed parameters are listed in Table 2. Results indicate that eavesdroppers' SINR is highest near the source vehicle's LED and decreases with distance due to path loss （Fig. 3）. Localized SINR peaks occur near traffic signals due to the directional characteristics of their LEDs. The maximum SINR of eavesdroppers reaches-7.07 dB， 8.77 dB lower than the reference scheme （Table 3）. Compared to traditional spatial jamming methods， the proposed scheme achieves superior SINR suppression across all regions. For near-field eavesdroppers， SINR is reduced by 11.25 dB and 10.61 dB in Scenarios 1 and 2， respectively. For far-field eavesdroppers， reductions of 17.12 dB and 17.41 dB are observed （Fig. 4）. Furthermore， the system's average secrecy capacity improves by 0.68 bits/s/Hz （Fig. 5）. These findings confirm that minimizing the worst-case SINR effectively disrupts eavesdropper reception while preserving legitimate communication quality.

In summary， this study addresses physical-layer security challenges in V2V-VLC systems under dynamic road conditions. An infrastructure-assisted AN interference scheme is proposed to mitigate interception risks， particularly in high-risk areas like intersections. By optimizing interference generation from both source vehicles and traffic signals， the scheme achieves multidimensional suppression of eavesdropper signals while maintaining legitimate communication quality. Simulations show that the proposed method suppresses eavesdroppers' worst-case SINR to-7.07 dB， 8.77 dB lower than traditional spatial jamming methods， with maximum SINR reductions of 11.25 dB and 17.41 dB for near-field and far-field eavesdroppers， respectively. The scheme also improves system secrecy capacity by 0.68 bits/s/Hz.

Compared to conventional methods， this approach offers superior physical-layer security for V2V-VLC systems in complex and dynamic road environments. Key innovations include： 1） Addressing security challenges in V2V-VLC systems with unknown and randomly distributed eavesdroppers at intersections. 2） Proposing a joint jamming scheme utilizing traffic infrastructure as a cooperative interference source， extending the spatial dimension of security. 3） Formulating and solving an optimization problem to minimize the worst-case SINR of eavesdroppers without interfering with legitimate users. This study provides theoretical and technical solutions for enhancing V2V-VLC security， laying a foundation for future research.