Abstract
Traffic flow can be sub-optimal when drivers lack real-time, lane-specific information. This disclosure describes a system for dynamic lane guidance, for example, within a navigation application on a computing device (e.g., a smartphone, smart watch, wearable device, augmented reality glasses, an in-vehicle infotainment system, etc.). In some implementations, the system can utilize a probabilistic inference engine, such as a Bayesian inference engine, to analyze multiple data sources. These sources may include real-time traffic data, historical data, predictive models, and crowdsourced information. This analysis can be used to calculate a probability of congestion, delay, and/or accident risk for individual lanes. These calculations can be used to generate lane-specific recommendations. The recommendations may be presented to the driver through a multimodal interface, for instance, a color-coded visual overlay on a navigation map. This method can be used to improve traffic management and reduce travel times by providing drivers with data-driven guidance for lane selection. The system can also be configured to mitigate driver fatigue from frequent lane changes.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Mouton, Jacques, "Color-Coded Lane Guidance System for Dynamic Traffic Flow Optimization", Technical Disclosure Commons, (July 14, 2025)
https://www.tdcommons.org/dpubs_series/8354