Prediction of Lane Number Using Results From Lane Detection
This paper tackles the problem of accurately determining the lane number for intelligent vehicle systems, particularly when existing lane detection methods are insufficient, representing an incremental improvement in this domain.
This paper addresses the challenge of predicting the lane number a vehicle is traveling in, especially when lane detection algorithms underperform. The authors propose combining drive recorder images with lane detection results to predict the lane number, achieving outstanding results on their dataset without significant computational cost increase.
The lane number that the vehicle is traveling in is a key factor in intelligent vehicle fields. Many lane detection algorithms were proposed and if we can perfectly detect the lanes, we can directly calculate the lane number from the lane detection results. However, in fact, lane detection algorithms sometimes underperform. Therefore, we propose a new approach for predicting the lane number, where we combine the drive recorder image with the lane detection results to predict the lane number. Experiments on our own dataset confirmed that our approach delivered outstanding results without significantly increasing computational cost.