A Flexible Multi-Layer Map Model Designed for Lane-Level Route Planning in Autonomous Vehicles

Jiang, Kun; Yang, Diange; Liu, Chaoran; Zhang, Tao; Xiao, Zhongyang

doi:10.1016/j.eng.2018.11.032

Cited by 54 publications

(34 citation statements)

References 14 publications

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“…The planning system of autonomous vehicles can be configured in various ways according to the operating environment, service type, and so on [23][24][25]. This section describes Eurecar's planning system, which is classified into four parts: global path planner, local path planner, behavior planner, and velocity planner.…”

Section: Extended Planning Subsystemmentioning

confidence: 99%

V2X-Communication-Aided Autonomous Driving: System Design and Experimental Validation

Jung

Lee

et al. 2020

Sensors

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In recent years, research concerning autonomous driving has gained momentum to enhance road safety and traffic efficiency. Relevant concepts are being applied to the fields of perception, planning, and control of automated vehicles to leverage the advantages offered by the vehicle-to-everything (V2X) communication technology. This paper presents a V2X communication-aided autonomous driving system for vehicles. It is comprised of three subsystems: beyond line-of-sight (BLOS) perception, extended planning, and control. Specifically, the BLOS perception subsystem facilitates unlimited LOS environmental perception through data fusion between local perception using on-board sensors and communication perception via V2X. In the extended planning subsystem, various algorithms are presented regarding the route, velocity, and behavior planning to reflect real-time traffic information obtained utilizing V2X communication. To verify the results, the proposed system was integrated into a full-scale vehicle that participated in the 2019 Hyundai Autonomous Vehicle Competition held in K-city with the V2X infrastructure. Using the proposed system, the authors demonstrated successful completion of all assigned real-life-based missions, including emergency braking caused by a jaywalker, detouring around a construction site ahead, complying with traffic signals, collision avoidance, and yielding the ego-lane for an emergency vehicle. The findings of this study demonstrated the possibility of several potential applications of V2X communication with regard to autonomous driving systems.

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Section: Extended Planning Subsystemmentioning

confidence: 99%

V2X-Communication-Aided Autonomous Driving: System Design and Experimental Validation

Jung

Lee

et al. 2020

Sensors

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“…Since it is a commercial format, the detail of this model was not open to the public. In previous study [101], the authors proposed a seven-layer lane-level map model based on a traditional road-level navigation electronic map by adding a lane layer. In this model, a lane was abstracted by the centerline of the lane.…”

Section: Lane-level Road Network Logic Representation Of Classic Lanementioning

confidence: 99%

Lane-Level Road Network Generation Techniques for Lane-Level Maps of Autonomous Vehicles: A Survey

Zheng

Yang

et al. 2019

Sustainability

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Autonomous driving is experiencing rapid development. A lane-level map is essential for autonomous driving, and a lane-level road network is a fundamental part of a lane-level map. A large amount of research has been performed on lane-level road network generation based on various on-board systems. However, there is a lack of analysis and summaries with regards to previous work. This paper presents an overview of lane-level road network generation techniques for the lane-level maps of autonomous vehicles with on-board systems, including the representation and generation of lane-level road networks. First, sensors for lane-level road network data collection are discussed. Then, an overview of the lane-level road geometry extraction methods and mathematical modeling of a lane-level road network is presented. The methodologies, advantages, limitations, and summaries of the two parts are analyzed individually. Next, the classic logic formats of a lane-level road network are discussed. Finally, the survey summarizes the results of the review.

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“…Whereas boundary lines are used to provide an abstract road network [10], the centerline of the road is also an important descriptor in lane-level road networks [11]. In general, a mobile mapping system (MMS) is often used to acquire precise road data.…”

Section: Lane-level Data Acquisition Of Road Geometrymentioning

confidence: 99%

Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy

Zheng

Song²,

et al. 2019

IJGI

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With the development of autonomous driving, lane-level maps have attracted significant attention. Since the lane-level road network is an important part of the lane-level map, the efficient, low-cost, and automatic generation of lane-level road networks has become increasingly important. We propose a new method here that generates lane-level road networks using only position information based on an autonomous vehicle and the existing lane-level road networks from the existing road-level professionally surveyed without lane details. This method uses the parallel relationship between the centerline of a lane and the centerline of the corresponding segment. Since the direct point-by-point computation is huge, we propose a method based on a trajectory-similarity-join pruning strategy (TSJ-PS). This method uses a filter-and-verify search framework. First, it performs quick segmentation based on the minimum distance and then uses the similarity of two trajectories to prune the trajectory similarity join. Next, it calculates the centerline trajectory for lanes using the simulation transformation model by the unpruned trajectory points. Finally, we demonstrate the efficiency of the algorithm and generate a lane-level road network via experiments on a real road.

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A Flexible Multi-Layer Map Model Designed for Lane-Level Route Planning in Autonomous Vehicles

Cited by 54 publications

References 14 publications

V2X-Communication-Aided Autonomous Driving: System Design and Experimental Validation

V2X-Communication-Aided Autonomous Driving: System Design and Experimental Validation

Lane-Level Road Network Generation Techniques for Lane-Level Maps of Autonomous Vehicles: A Survey

Generation of Lane-Level Road Networks Based on a Trajectory-Similarity-Join Pruning Strategy

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