An Experimental Analysis of Object Recognition Performance Under Different Lighting Scenes for Varying CCT of LED Light Sources

For understanding the drivers’ response on degree of object identification under varying CCT (Correlated Color Temperature), this study is done in a controlled laboratory environment by using a smart CCT tunable LED as source with similar two LEDs as peripheral sources. This study analyses every particular artificially generated lighting scene by following Likert Chart using the marks given to the scene by the participants based upon some questions asked to the participant about color and shape rendering capability, subjective visibility and feeling of the participants at that particular lighting scene. It is seen that at 4000K CCT of main source object recognition is best, while peripheral sources are off. It is also found that 5000K CCT of main source and 6000K CCT of peripheral sources are optimum for best object recognition output. Most importantly, it is evident from the study that CCT plays a key role in object recognition. From the experimental results, we can easily identify perfect or close to perfect lighting scenarios with respect to user of the streets and from that it would be very easier to design a street lighting scheme.