Abstract
In order to study the driving behaviors, such as lane change and overtaking, which concerns the relationship between ego and all-surrounding vehicles, it is of great demand in developing an automated system to collect the synchronized motion trajectories that characterize the full course of driving maneuvers in real-world traffic scene. This research proposes a measurement and data processing system, where multiple 2D-Lidars are mounted on a vehicle platform to generate an omni-directional horizontal coverage to the ego-vehicle’s surrounding; focusing the driving scenario on motorway, two processing approaches in online and offline procedures are studied for vehicle trajectory extraction by fusing the multi-Lidar data that are acquired during on-road driving. A case study is conducted using a data set collected during 10 min’ driving and lasted for 4.1 km long. The performance of trajectory extraction in online and offline procedures is comparatively examined. In addition, a reference vehicle participated in data collection too. The trajectory is analyzed to study its potential in characterizing the situations during vehicle maneuvers.
This work is partially supported by the Hi-Tech Research and Development Program of China (2012AA011801) and the NSFC Grants (61161130528, 91120010).
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Zhao, H., Wang, C., Yao, W., Cui, J., Zha, H. (2014). Vehicle Trajectory Collection Using On-Board Multi-Lidars for Driving Behavior Analysis. In: Sun, F., Li, T., Li, H. (eds) Knowledge Engineering and Management. Advances in Intelligent Systems and Computing, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37832-4_60
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DOI: https://doi.org/10.1007/978-3-642-37832-4_60
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