Blind channel estimation (CE) methods for OFDM based RF communication provide high-rate transmission by eliminating pilot overhead in conventional pilot-based methods, at the cost of lower accuracy. However, there is no work on the blind CE for OFDM based visible light communication (VLC) systems. In this paper, we propose a novel blind CE method for vehicular VLC with the goal of improving CE accuracy based on the exploitation of the channel statistics derived, by utilizing extensive amount of data collected for different communication angles, distances, and ambient light conditions. First, the normalized channel frequency response (CFR) of the V2LC channel is demonstrated to be invariant of inter-vehicular distance, relative transmitter/receiver zenith angle and ambient light. Then, this channel characteristic is exploited in the blind CE to improve its accuracy with two-step estimation of normalization factor. Extensive simulations at different vehicle speeds show that the proposed method outperforms the pilot-based and superimposed training-based CE methods in terms of spectral efficiency both for all modulation schemes and at all relative speeds. The proposed blind channel estimation (CE) method provides 9.77% increase in the spectral efficiency, compared to the second best method, superimposed training-based CE, at 20 dB signal-to-noise ratio (SNR) and 160 km/h relative speed, for 64-Quadrature Amplitude Modulation (QAM) Direct Current-Biased Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM). Moreover, the real-time performance of the proposed blind CE is demonstrated for a realistic vehicle mobility scenario extracted from SUMO.