4 papers
BF-Map: Crowd-sourced Mapping with Bayesian B-spline Fusion
Yiping Xie, Yuxuan Xia, Erik Stenborg +5
Crowd-sourced mapping offers a scalable alternative to creating maps using traditional survey vehicles. Yet, existing methods either rely on prior high-definition (HD) maps or negl…
Driving with Context: Online Map Matching for Complex Roads Using Lane Markings and Scenario Recognition
Xin Bi, Zhichao Li, Yuxuan Xia +4
Accurate online map matching is fundamental to vehicle navigation and the activation of intelligent driving functions. Current online map matching methods are prone to errors in co…
Towards Accurate Ego-lane Identification with Early Time Series Classification
Yuchuan Jin, Theodor Stenhammar, David Bejmer +3
Accurate and timely determination of a vehicle's current lane within a map is a critical task in autonomous driving systems. This paper utilizes an Early Time Series Classification…
Bayesian Simultaneous Localization and Multi-Lane Tracking Using Onboard Sensors and a SD Map
Yuxuan Xia, Erik Stenborg, Junsheng Fu +1
High-definition map with accurate lane-level information is crucial for autonomous driving, but the creation of these maps is a resource-intensive process. To this end, we present…