frontlichtdat

Frontlichtdat is a term used in automotive data science and lighting research to describe a dataset that records information about front lighting systems and related conditions. The name is a portmanteau of the Dutch words for front light (frontlicht) and data (dat), and it is often used in Dutch-speaking research contexts. As a concept, frontlichtdat can refer to either a defined standard for front lighting data or to a collection comprising multiple sources. The goal is to enable analysis of how headlamps perform under varied conditions and how lighting configurations influence road safety and energy use.

A typical frontlichtdat record includes: timestamp, vehicle_id or sensor_id, headlight_mode (low beam, high beam, adaptive/auto), beam_pattern metrics (spread, intensity distribution), maximum luminance, color temperature, calibration status, along with contextual data such as weather (fog, rain), time of day, location or road type, and observer or measurement method. Data can originate from onboard vehicle sensors, laboratory measurements, field tests, or surveillance campaigns. Aggregated versions may use anonymization and aggregation to protect privacy.

Uses and impact: Researchers use frontlichtdat to assess headlamp effectiveness, calibrate adaptive lighting systems, model glare exposure for pedestrians and other drivers, and inform standards or regulation. It can support simulations of traffic scenarios, energy efficiency analyses, and design decisions for new lighting technologies. Challenges include data standardization, sensor calibration, privacy concerns, and cross-manufacturer comparability.