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High-level automated driving on complex urban roads with LiDAR, Vision, and GPS/map based environment representation Kim, Beomjun ; Kim, Dongwook ; Lee, Junyung ; Kim, Kyuwon ; Yi, Kyongsu

By: Contributor(s): Publication details: Göteborg Chalmers University of Technology. SAFER Vehicle and Traffic Safety Centre, 2015Description: s. 657-664Subject(s): Online resources: In: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents: September 9-11, 2015 Gothenburg, Sweden: proceedingsNotes: Konferens: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents, 2015, Gothenburg Abstract: This paper proposes a fully automated driving algorithm which is capable of automated driving on urban roads with guaranteed safety. The proposed algorithm consists of the following three steps: an environment representation, a motion planning, and a vehicle control. An environment representation system consists of three main modules: object classification, vehicle/non-vehicle tracking and map/lane based localization. A motion planning modules derives an optimal trajectory as a function of time, from the environment representation results. A safety envelope definition module determines the complete driving corridor that leads to the destination while assigning all objects to either the left or right corridor bound. In the case of moving objects such as other traffic participants, their behaviors are anticipated in the near future. An optimal trajectory planner uses the safety envelop as a constraint and computes a trajectory that the vehicle stays in its bounds. The vehicle control module feeds back the pose estimate of the localization module to guide the vehicle along the planned trajectory. The effectiveness of the proposed automated driving algorithm is evaluated via vehicle tests. Test results show the robust performance on an inner-city street scenario.
Item type: Reports, conferences, monographs
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Konferens: FAST-zero'15: 3rd International symposium on future active safety technology toward zero traffic accidents, 2015, Gothenburg

This paper proposes a fully automated driving algorithm which is capable of automated driving on urban roads with guaranteed safety. The proposed algorithm consists of the following three steps: an environment representation, a motion planning, and a vehicle control. An environment representation system consists of three main modules: object classification, vehicle/non-vehicle tracking and map/lane based localization. A motion planning modules derives an optimal trajectory as a function of time, from the environment representation results. A safety envelope definition module determines the complete driving corridor that leads to the destination while assigning all objects to either the left or right corridor bound. In the case of moving objects such as other traffic participants, their behaviors are anticipated in the near future. An optimal trajectory planner uses the safety envelop as a constraint and computes a trajectory that the vehicle stays in its bounds. The vehicle control module feeds back the pose estimate of the localization module to guide the vehicle along the planned trajectory. The effectiveness of the proposed automated driving algorithm is evaluated via vehicle tests. Test results show the robust performance on an inner-city street scenario.