Abstract
Currently, digital maps and navigation systems do not provide sufficient information about lighting conditions for roads and lanes. The lack of reliable information can negatively impact route selection and driving speed if a road is poorly lit). This disclosure describes techniques to automatically determine the lighting level of a road or road segment by analyzing speed variation of vehicles that traverse it at late night (when it is dark) and early morning (when there is adequate light), under otherwise similar conditions (traffic levels, road surface quality, etc.). A significant difference in speed between these periods suggests poor road lighting, as drivers feel less confident and drive slower at night. Conversely, a minimal difference corresponds to adequate lighting, as drivers maintain similar speeds regardless of artificial or natural light. Statistical analyses of the data, including the use of clustering algorithms, is performed to associate lighting ratings (e.g., well-lit, poorly-lit) with road segments which can be used for route planning and navigation.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Garg, Priyank, "Assessing Road Lighting Conditions Using Speed Variation Analysis", Technical Disclosure Commons, (April 02, 2025)
https://www.tdcommons.org/dpubs_series/7959