Lane detection based on a visual-aided multiple sensors platform

Currently, GPS is the dominating technology for commercial car navigation applications, which offers acceptable navigation service for door to door navigation. However, within GPS degraded or denied areas, GPS standalone may not support sufficient accuracy and availability for a satisfactory user experience. Lane detection is an important and fundamental functionality to complete various future intelligent transportation system applications. In this paper, multiple candidate solutions for lane detection are investigated including single frequency precise point positioning (PPP), low-cost gyroscope, and visual-aided methods. These methods are compared against a traditional standalone GPS solution. The results of driving tests show that single frequency PPP can improve position accuracy by efficiently mitigating the ionospheric error but still cannot fulfill the lane detection functionality while the gyroscope and visual-aided methods show promising results.