scholarly journals Pedestrian Avoidance Method of Autonomous Personal Mobility Vehicles Considering Passenger Comfort

2021 ◽  
Author(s):  
Yosuke Isono ◽  
Hiroshi Yoshitake ◽  
Motoki Shino
Keyword(s):  
Path Planning ◽  
Planning Method ◽  
Pedestrian Behavior ◽  
Personal Mobility ◽  
Passenger Comfort ◽  
Local Path Planning ◽  
Avoidance Strategies ◽  
Local Path ◽  
Subject Experiment ◽  
Pedestrian Space

Abstract During the autonomous locomotion of personal mobility vehicles (PMVs) in pedestrian space, it is necessary to avoid collisions with pedestrians walking nearby. The avoidance paths of the PMVs are affected by the behavior of the pedestrians, which may also affect passenger comfort. In this study, a local path planning method considering passenger comfort is proposed to design comfortable pedestrian avoidance strategies during autonomous locomotion of PMVs in pedestrian space. First, pedestrian behaviors that affect passenger comfort are investigated by evaluating the comfort in pedestrian avoidance scenarios with different avoidance methods and pedestrian behavior. Next, requirements for a pedestrian avoidance method considering comfort are set based on the behaviors affecting passenger comfort. Finally, a novel path planning method satisfying the requirements is proposed. It is confirmed that the proposed method can generate comfortable paths in pedestrian space, and the validity of the proposed method is examined by a subject experiment.

Integrated local path planning method

2007 ◽  
Author(s):  
HwangRyol Ryu ◽  
KiSung You ◽  
ChinTae Choi
Keyword(s):  
Path Planning ◽  
Planning Method ◽  
Local Path Planning ◽  
Local Path

Local Path Planning for Dual-Arm Mobile Robot Shuttling within Truss

2012 ◽  
Vol 452-453 ◽  
pp. 1220-1224
Author(s):  
Wei Guo Wu ◽  
Peng Wu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Planning Method ◽  
Planning Stage ◽  
Probabilistic Roadmaps ◽  
Local Path Planning ◽  
Smooth Path ◽  
Local Path ◽  
Two Stages ◽  
Dual Arm

A new local path planning method for dual-arm mobile robot shuttling within the truss is presented. Like the probabilistic roadmaps method, this method proceeds in two stages: preprocessing stage and path planning stage. In preprocessing stage, the workspace is divided into a set of non-overlapping cubical cells. The nodes in the free workspace are stored in a matrix. In path planning stage, three query strategies are adopted to search the path from start point to goal point. Take use of vertex query strategy, the smooth path can be acquired in a fraction of a second. The algorithm is simple, and is applicable to any static environment with convex obstacles.

A real-time local path planning method in complex scenes

2021 ◽  
Author(s):  
Cai Wenlin ◽  
Zihui Zhu ◽  
Jianhua Li ◽  
Jiaqi Liu ◽  
Chunxi Wang
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Planning Method ◽  
Local Path Planning ◽  
Complex Scenes ◽  
Local Path

scholarly journals Rollover-Free Path Planning for Off-Road Autonomous Driving

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 614
Author(s):  
Xingyu Li ◽  
Bo Tang ◽  
John Ball ◽  
Matthew Doude ◽  
Daniel W. Carruth
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Autonomous Driving ◽  
Planning Method ◽  
Local Planning ◽  
Planning Stage ◽  
Local Path Planning ◽  
Global Route ◽  
Local Path ◽  
Global Planning

Perception, planning, and control are three enabling technologies to achieve autonomy in autonomous driving. In particular, planning provides vehicles with a safe and collision-free path towards their destinations, accounting for vehicle dynamics, maneuvering capabilities in the presence of obstacles, traffic rules, and road boundaries. Existing path planning algorithms can be divided into two stages: global planning and local planning. In the global planning stage, global routes and the vehicle states are determined from a digital map and the localization system. In the local planning stage, a local path can be achieved based on a global route and surrounding information obtained from sensors such as cameras and LiDARs. In this paper, we present a new local path planning method, which incorporates a vehicle’s time-to-rollover model for off-road autonomous driving on different road profiles for a given predefined global route. The proposed local path planning algorithm uses a 3D occupancy grid and generates a series of 3D path candidates in the s-p coordinate system. The optimal path is then selected considering the total cost of safety, including obstacle avoidance, vehicle rollover prevention, and comfortability in terms of path smoothness and continuity with road unevenness. The simulation results demonstrate the effectiveness of the proposed path planning method for various types of roads, indicating its wide practical applications to off-road autonomous driving.

A novel method of unmanned surface vehicle autonomous cruise

2016 ◽  
Vol 43 (1) ◽  
pp. 121-130 ◽  
Author(s):  
Shaorong Xie ◽  
Peng Wu ◽  
Hengli Liu ◽  
Peng Yan ◽  
Xiaomao Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Detection ◽  
Planning Method ◽  
Dijkstra Algorithm ◽  
Complex Environment ◽  
Unmanned Surface Vehicle ◽  
Content Type ◽  
Global Path Planning ◽  
Local Path Planning ◽  
Local Path

Purpose – This paper aims to propose a new method for combining global path planning with local path planning, to provide an efficient solution for unmanned surface vehicle (USV) path planning despite the changeable environment. Path planning is the key issue of USV navigation. A lot of research works were done on the global and local path planning. However, little attention was given to combining global path planning with local path planning. Design/methodology/approach – A search of shortcut Dijkstra algorithm was used to control the USV in the global path planning. When the USV encounters unknown obstacles, it switches to our modified artificial potential field (APF) algorithm for local path planning. The combinatorial method improves the approach of USV path planning in complex environment. Findings – The method in this paper offers a solution to the issue of path planning in changeable or unchangeable environment, and was confirmed by simulations and experiments. The USV follows the global path based on the search of shortcut Dijkstra algorithm. Both USV achieves obstacle avoidances in the local region based on the modified APF algorithm after obstacle detection. Both the simulation and experimental results demonstrate that the combinatorial path planning method is more efficient in the complex environment. Originality/value – This paper proposes a new path planning method for USV in changeable environment. The proposed method is capable of efficient navigation in changeable and unchangeable environment.

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