[9], utilized only vehicle location and ETX as the quality metric for video transmission, which are not enough considering the dynamic situation of VANETs. The ETX is a metric used to estimate the quality of path between two vehicles based on expected transmission count in a wireless network. However, the metric selects a path with minimum ETX between two vehicles but does not consider the hop count from source to destination vehicle. Meanwhile, in the proposed RMF-MVS scheme, the greedy based routing has been employed, which addressed the traversed high number of hop issue. Further, a scheme that considers the future and current position of the vehicle and the decoupling of video content transmission from the relay node transmission has been suggested. However, this is not enough to guarantee the optimal selection of the next forwarder vehicle considering the high video data rate and obstructions in the urban environment. However, in the proposed RMF-MVS scheme the accessible bandwidth availability has been considered to ascertain enough bandwidth for the video data streaming. In addition, the noise ratio in the signal, which is due to obstruction and interference of external objects, is also considered for forwarder vehicle selection. Both [PERSON] et al. [10] and [PERSON] and [PERSON] [11] have suggested a scheme based on a multi-metric map-aware concept in order to achieve efficient data delivery. The suggested scheme in [PERSON] et al. [10] is based on normal data, that is, not video data. However, the video data transmission is considered in [11]. The multi-metric considered includes distance, vehicle density, vehicle trajectory, available bandwidth estimation and MAC layer losses. These metrics are important for the achievement of quality video delivery. However, some fundamental parameters, which are specific to the dynamicity of vehicular ad hoc networks, have not been considered. For example, in their approach, the trajectory of a next forwarding vehicle to the destination is estimated based on its distance and direction towards the destination vehicle. However, in the real vehicular situation, a vehicle moving towards the destination vehicle may decide to exit or stop its movement, the probability of vehicle stoppage needs to be considered when selecting a trajectory vehicle towards the destination vehicle. In this context, in this work, several metrics including vehicle density on the Road (VDR), Vehicle Trajectory (VTJ), Hello message Received rate (H\({}_{\rm{m}}\)R\({}_{\rm{r}}\)), Accessible Bandwidth Estimation (ABE) and Signal to Interference plus Noise Ratio (SINR) have been considered for evaluating next forwarding vehicle selection. The video frames forwarded are split into three different frames, namely, I-frame, P-frame and B-frame, which are forwarded through multipath setting. I-frames are forwarded through a dedicated path, while both P and B frames are forwarded through another path. This concept enables higher priority for I-frames, which are the most important frames that interpret both P and B frames. Consequently, a Road-based Multi-metric Forwarder evaluation for Multipath Video Streaming (RMF-MVS) has been proposed considering link connectivity and bandwidth efficiency of a forwarding vehicle. The RMF-MVS scheme is further enhanced by adapting it to be a Dynamic Self-Weighting (DSW) score for forwarder vehicle selection evaluation. Specifically, the contributions of this study are stated as follows. 1. A link connectivity strategy for forwarder vehicle selection considering vehicle density on the road and vehicle trajectory. An enhanced link connectivity considering response time evaluation based on hello message receive rate for forwarder vehicle selection. * Improved link quality estimation by employing accessible bandwidth estimation and signal to interference plus noise ratio. * Dynamic self-weighting score for multi-metric forwarder vehicle selection evaluation. * Validation based on extensive simulation results and critical analysis in comparison with state-of-the-art techniques.