CN101833702B - Method for dynamically replacing navigation points based on viewing range of pedestrian - Google Patents
Method for dynamically replacing navigation points based on viewing range of pedestrian Download PDFInfo
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- CN101833702B CN101833702B CN2010100308298A CN201010030829A CN101833702B CN 101833702 B CN101833702 B CN 101833702B CN 2010100308298 A CN2010100308298 A CN 2010100308298A CN 201010030829 A CN201010030829 A CN 201010030829A CN 101833702 B CN101833702 B CN 101833702B
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Abstract
The invention provides a method for dynamically replacing navigation points based on a viewing range of a pedestrian, and relates to a method for simulating a pedestrian traffic behavior in a transportation junction in the technical field of traffic simulation. The method comprises the following steps of: establishing a visual angle by utilizing an angular bisector which takes an advancing direction of the pedestrian as the visual angle, scanning in the visual angle range in real time by using a visual range as a scanning radius, and abandoning a current navigation point and starting the next navigation point if the next navigation point is in the scanning range and no barrier is on the line between the next navigation point and the current position point of the pedestrian, wherein the starting of the next navigation point does not take arrival of the current navigation point as a condition, but takes the visual range of the pedestrian as the condition; and the mode is closer to the actual behavior of the pedestrian. The shortest route for the pedestrian can be better ensured by dynamically replacing the navigation points.
Description
Technical field
The present invention relates to the method for the inner pedestrian's traffic behavior in simulation transport hub in a kind of traffic simulation technical field, specifically a kind of navigation spots based on range of pedestrian is dynamically changed method.
Background technology
The validity of pedestrian's microscopic behavior model is that it whether can the multi-level decision behavior of accurate description pedestrian under the hinge scene, and the motion track of individual pedestrian in subrange.Since late 1980s, artificial intelligence and pedestrian simulation researcher be respectively from the human intelligent behavior of the angle research of intelligence imitation, Behavior modeling, and drawn similarly basic understanding: intelligence control system usually by multi-level hierarchical control (multiresolution or multiple dimensioned under Intelligent Information Processing) realize its target of taking action.S.P.Hoogendoorn (2001) is divided into strategy level, Tactics-level, three ranks of operation level with pedestrian's microscopic behavior, and it is theoretical to have set up classical pedestrian's microscopic behavior based on utility theory.Corresponding with three rank behavioral theories that Hoogendoorn proposes, the research of pedestrian's microscopic behavior concentrates on activity chain generation, path finding and routing, three aspects of microcosmic mobile behavior modeling.
Usually routing is that the supposition pedestrian follows Least-cost or the maximum principle of effectiveness, concentrates from alternative path and selects a practical action path.The generation method of alternative path set has planning and simulates two kinds, planing method generally adopts the shortest path algorithms such as Dijkstra, A* to obtain the alternative path collection by setting a neighborhood value, although the method can be simplified finding the solution of problem, do not meet with pedestrian's path finding mechanism; And adopt the method for simulating, and then needing to study the method in pedestrian's main body searching path in the reality, the pedestrian's path finding model in facility set up in the use such as Martin Raubal (1999,2001) descriptive language.Hoogendoorn and Bovy (2004) supposition pedestrian has the Complete Information in path to be selected, and the factors such as distance, barrier, zig zag, pedestrian density and path circumstances in path are included in pedestrian's microcosmic path Choice Model.Dammen etc. (2004) is incorporated into the discrepancy in elevation factor of path vertical direction in the path Choice Model in addition.The track that pedestrian's routing obtains is broken line or the curve that is made of series of points, and these points are referred to as navigation spots.In simulation process, the pedestrian is successively by each node in the chained list of path, at this time the navigation spots of each node as the current impact point of pedestrian, the pedestrian enables next navigation spots after arriving current navigation spots.
The weak point of the method is, the pedestrian usually departs from current navigation spots direction because hiding other pedestrian or barrier in the process of walking, this moment, the pedestrian was probably more near next navigation spots, if still to the walking of current navigation spots and after arrival, turn to again next navigation spots, will increase travel distance, do not meet the shortest path principle, also do not meet the behavioural habits in the actual walking process of pedestrian.
Summary of the invention
The object of the invention is to overcome deficiency of the prior art, provide a kind of navigation spots based on range of pedestrian dynamically to change method.
A kind of navigation spots based on range of pedestrian is dynamically changed method, may further comprise the steps:
A), generate pedestrian's target logic object;
B), all barriers that are associated between scanning pedestrian current place object logic and the target logic object, utilize path Choice Model in the pedestrian simulation to generate shortest path between two object logics, and each node on the path is pressed in the chained list of path;
C), the angular bisector take pedestrian advancing direction as the visual angle is set up the visual angle
D), take sighting distance L as sweep radius, real time scan in angular field of view judges that next node in the chained list of path is whether in this sweep limit;
E), if not, walk by current navigation spots; If judge on next node and the pedestrian's current location line whether barrier is arranged;
F) if walk by current navigation spots; If not, then pedestrian's navigation spots is replaced by the next node in the chained list of path, turns back to the c step.
Beneficial effect of the present invention:
Next impact point enable not arrival take current goal point as condition, but take pedestrian's visual range as condition, this mode and pedestrian's agenda is comparatively approaching.In simulation process; the pedestrian departs from current navigation spots because hiding other pedestrians or barrier; often can occur this moment pedestrian's current location to the distance of next navigation spots less than the pedestrian to the distance of current navigation spots and current navigation spots to next navigation spots apart from sum; if still adopt current navigation spots this moment, pedestrian's path increases.Adopt method of the present invention can effectively solve problems.
Description of drawings
Fig. 1 computer program realization flow of the present invention figure;
The schematic diagram of Fig. 2 visual range of the present invention;
The navigation spots of Fig. 3 the present embodiment is changed schematic diagram.
Embodiment
Below in conjunction with accompanying drawing embodiments of the invention are elaborated:
The present embodiment is implemented under take technical solution of the present invention as prerequisite, has provided detailed embodiment and process, but protection scope of the present invention is not limited to following embodiment.
Computer program implementation procedure of the present invention is as follows:
Fig. 1 is computer program realization flow figure of the present invention, generated in analogue system on pedestrian's the basis of target logic object, all barriers that are associated between scanning pedestrian current place object logic and the target logic object, utilize the path Choice Model (the present embodiment adopts the A* algorithm) in the pedestrian simulation model to generate the shortest path between two object logics, and each node on the path (being navigation spots) is pressed in the chained list of path, the pedestrian calls the collision prevention algorithm successively by each node in the chained list of path, and judge that in the process of walking next node in the chained list of path is whether in the current visual range of pedestrian, if in scope, then pedestrian's navigation spots is replaced by the next node in the chained list of path.
The pedestrian simulation of embodiment in the S type passage is as example, and specific implementation method is as follows:
The present embodiment, is searched shortest path according to the A* algorithm, and each navigation spots on the path is pressed in the chained list of path to the barrier that exists between the target location by above-mentioned flow process scanning pedestrian current location.The present embodiment is take S type passage shown in Figure 3 as example, A
1, A
2, A
3Be 3 nodes in the chained list of path, establish the pedestrian visual angle and be
The current direction of travel of pedestrian is angular bisector, and getting pedestrian's sighting distance is L, then take L as the radius angle as
The fan-shaped range of pedestrian that is, in the present embodiment, the current navigation spots of pedestrian C is A
1, and because other pedestrians' interference, pedestrian C does not arrive A
1And depart from this direction, and A
2This moment is in pedestrian's visual range, and CA
2There is not barrier on the line, the method according to this invention, pedestrian C abandons current navigation spots A
1, enable navigation spots A
2, directly to A
2The direction walking, as can be seen from the figure,
Dynamically change the shortest path that navigation spots can better guarantee the pedestrian.
Claims (2)
1. the navigation spots based on range of pedestrian is dynamically changed method, may further comprise the steps:
A), generate pedestrian's target logic object;
B), all barriers that are associated between scanning pedestrian current place object logic and the target logic object, utilize path Choice Model in the pedestrian simulation to generate shortest path between two object logics, and each node on the path is pressed in the chained list of path, when the pedestrian walked take a certain node position as target direction, this node was the current navigation spots of pedestrian in the emulation;
It is characterized in that: described method is further comprising the steps of:
C), the angular bisector take pedestrian advancing direction as the visual angle is set up the visual angle
D), take sighting distance L as sweep radius, real time scan in angular field of view judges that next node in the chained list of path is whether in this sweep limit;
E), if not, walk by current navigation spots; If judge on next node and the pedestrian's current location line whether barrier is arranged;
F) if walk by current navigation spots; If not, then pedestrian's navigation spots is replaced by the next node in the chained list of path, turns back to the c step.
2. a kind of navigation spots based on range of pedestrian according to claim 1 is dynamically changed method, it is characterized in that: the path Choice Model in the described pedestrian simulation adopts A
*Algorithm.
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JP5569365B2 (en) * | 2010-11-30 | 2014-08-13 | アイシン・エィ・ダブリュ株式会社 | Guide device, guide method, and guide program |
CN104778500A (en) * | 2014-01-14 | 2015-07-15 | 吉林大学 | Pedestrian macroscopic path planning method based on start marker link |
CN109739219B (en) | 2018-12-05 | 2022-02-11 | 阿波罗智能技术(北京)有限公司 | Method, device and equipment for planning passing path and readable storage medium |
Citations (1)
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CN101075352A (en) * | 2007-06-29 | 2007-11-21 | 中国科学院计算技术研究所 | Laminated barrier-avoiding method for dynamic body |
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CN101075352A (en) * | 2007-06-29 | 2007-11-21 | 中国科学院计算技术研究所 | Laminated barrier-avoiding method for dynamic body |
Non-Patent Citations (5)
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吕永刚等.基于模糊决策法的移动机器人路径规划方法.《机床与液压》.2005,(第06期), * |
曲道奎等.移动机器人路径规划方法研究.《机器人》.2008,第30卷(第02期), * |
袁立行,郑南宁.基于视觉反馈的自主式移动机器人路径规划方法.《西安交通大学学报》.1995,第29卷(第01期), * |
贾洪飞等.综合交通枢纽内部行人微观特性及建模需求研究.《交通运输系统工程与信息》.2009,(第02期), * |
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