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    无人驾驶自主换道策略[ZH]

    专利编号: ZL202606080603

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    拟转化方式: 转让;普通许可;独占许可;排他许可;作价投资;开放许可

    交易价格:面议

    专利类型:发明专利

    法律状态:授权

    技术领域:智能网联汽车

    发布日期:2026-06-08

    发布有效期: 2026-06-08 至 2038-10-24

    专利顾问 — 王老师

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    专利基本信息
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    申请号 CN201811244472.6 公开号 CN109754626A
    申请日 2018-10-24 公开日 2019-05-14
    申请人 禾多科技(北京)有限公司 专利授权日期 2020-08-25
    发明人 邢建生 专利权期限届满日 2038-10-24
    申请人地址 100089 北京市海淀区阜外亮甲店1号恩济西园产业园21号楼一层21-14 最新法律状态 授权
    技术领域 智能网联汽车 分类号 G08G1/0967
    技术效果 安全性 有效性 有效(授权、部分无效)
    专利代理机构 北京远大卓悦知识产权代理事务所(普通合伙) 11369 代理人 汤小东
    专利技术详情
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    01

    专利摘要

    本发明公开了一种无人驾驶自主换道策略,主要包括以下步骤:步骤A、根据预设的公式1计算得到无人驾驶车辆所在车道的通畅程度值A以及其他车道的通畅程度值B;步骤B、将通畅程度值A和通畅程度值B进行比较,以选择出拥堵程度最低的车道作为目标车道发送给所述无人驾驶车辆的驾驶系统;其中所述公式1为车道流速模型的公式:Z=X×[1/(1+0.3×Y)],其中,Z表示通畅程度值;X表示各条车道上的车辆的平均车速;Y表示无人驾驶车辆后方的车辆数量。其能够应对各种真实道路场景,实现了无人驾驶车辆在各种道路场景内的高效、安全、可靠的自主换道。
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    02

    专利详情

    技术领域

    本发明涉及无人驾驶技术领域,尤其涉及一种无人驾驶自主换道策略。

    背景技术

    随着人们对汽车智能化要求的不断提高,无人驾驶汽车作为智能驾驶的核心成为
    了最为关注的技术。而车辆换道是车辆行驶过程中一个常见但复杂的行为,很大程度上影
    响道路的流通性,快速而安全的换道操作对减少交通事故具有极强的现实应用意义。

    然而,真实的道路场景是很复杂多变的,因而,如何实现无人驾驶汽车既能高效,
    安全,可靠的完成自主换道,还能覆盖复杂多变的道路场景,无疑是一个很大的挑战。

    发明内容

    本发明针对现有技术中存在的上述问题,提供一种无人驾驶自主换道策略,能够
    应对各种真实道路场景,实现了无人驾驶车辆在各种道路场景内的高效、安全、可靠的自主
    换道。

    为实现上述目的和一些其他的目的,本发明采用如下技术方案:

    一种无人驾驶自主换道策略,主要包括以下步骤:

    步骤A、根据预设的公式1计算得到无人驾驶车辆所在车道的通畅程度值A以及其
    他车道的通畅程度值B;

    步骤B、将通畅程度值A和通畅程度值B进行比较,以选择出拥堵程度最低的车道作
    为目标车道发送给所述无人驾驶车辆的驾驶系统;

    其中所述公式1为车道流速模型的公式:

    Z=X×[1/(1+0.3×Y)] 公式1

    其中,Z表示通畅程度值;X表示各条车道上的车辆的平均车速;Y表示无人驾驶车
    辆后方的车辆数量。

    优选的是,所述的无人驾驶自主换道策略中,所述车道流速模型的公式用于计算
    车道加权平均速度,所述通畅程度值由车道上行驶的车辆数量和平均速度决定。

    优选的是,所述的无人驾驶自主换道策略中,步骤B中将所述通畅程度值A和通畅
    程度值B进行比较以选择出目标车道的方法依据待选的车道相对于所述无人驾驶车辆所行
    驶的车道的通畅程度,所述通畅程度通过公式2表示:

    Vf=0.012V0×V0+0.52×V0 公式2

    其中,Vf表示待选的车道相对于所述无人驾驶车辆所行驶的车道的通畅程度;V0
    表示通畅程度值B。

    优选的是,所述的无人驾驶自主换道策略中,步骤B中将所述通畅程度值A和通畅
    程度值B进行比较以选择出目标车道的方法还依据于经验数据库,所述经验数据库为由司
    机在各种道路上行驶的数据进行收集并整理得到。

    优选的是,所述的无人驾驶自主换道策略中,当通畅程度值B大于19m/s,通畅程度
    值A小于最大通畅程度值的0.92倍,且通畅程度值B大于Vf时,判定所述无人驾驶车辆换道
    至目标车道。

    优选的是,所述的无人驾驶自主换道策略中,当通畅程度值B小于Vf,通畅程度值B
    小于最大通畅程度值时,判定所述无人驾驶车辆在原车道上行驶。

    优选的是,所述的无人驾驶自主换道策略中,步骤B中将所述通畅程度值A和通畅
    程度值B进行比较以选择出目标车道的方法还依据于选择模块,所述选择模块在所述无人
    驾驶车辆满足换道条件,且所述无人驾驶车辆行驶在两边车道时,控制所述无人驾驶车辆
    换道至中间车道行驶。

    本发明至少包括以下有益效果:

    本发明所述的无人驾驶自主换道策略通过车道流速模型的建立,使得所述无人驾
    驶自主换道策略基于车道流速模型,先根据车道流速模型分析出待选车道的通畅程度,然
    后与本车自身车道通畅情况进行衡量比较,从中选择出拥堵程度最低的车道,将其作为最
    优目标车道,车道流速模型根据各条车道上的车辆的平均车速,以及无人驾驶车辆后方的
    车辆数量综合判断,使得得到的车道通畅程度值不受车辆行驶场景的限制,适用于各种道
    路场景,且根据车道上车辆的平均车速以及车辆数量的判断结果与人工判断结果相吻合,
    使得计算结果更为准确且贴合实际,从而为无人驾驶车辆是否换道提供了可靠的依据,使
    得所述无人驾驶车辆能够安全、可靠、高效的完成换道。

    本发明的其它优点、目标和特征将部分通过下面的说明体现,部分还将通过对本
    发明的研究和实践而为本领域的技术人员所理解。

    附图说明

    图1是本发明提供的无人驾驶自主换道策略的车道流速模型的示意图;

    图2是本发明提供的无人驾驶自主换道策略中将通畅程度值A和通畅程度值B进行
    比较以选择出目标车道的方法的坐标图。

    具体实施方式

    下面结合附图对本发明做详细说明,以令本领域普通技术人员参阅本说明书后能
    够据以实施。

    如图1和图2所示,一种无人驾驶自主换道策略,主要包括以下步骤:

    步骤A、根据预设的公式1计算得到无人驾驶车辆所在车道的通畅程度值A以及其
    他车道的通畅程度值B;

    步骤B、将通畅程度值A和通畅程度值B进行比较,以选择出拥堵程度最低的车道作
    为目标车道发送给所述无人驾驶车辆的驾驶系统;

    其中所述公式1为车道流速模型的公式:

    Z=X×[1/(1+0.3×Y)] 公式1

    其中,Z表示通畅程度值;X表示各条车道上的车辆的平均车速;Y表示无人驾驶车
    辆后方的车辆数量。

    在上述方案中,车道流速模型的建立依据每条道路上车的数量,以及车辆的平均
    速度,符合人工驾驶时的判断习惯,实现了模拟人工的决策,使得对于换道决策的判断更加
    可靠且安全。

    通过车道流速模型的建立,使得所述无人驾驶自主换道策略基于车道流速模型,
    先根据车道流速模型分析出待选车道的通畅程度,然后与本车自身车道通畅情况进行衡量
    比较,从中选择出拥堵程度最低的车道,将其作为最优目标车道,车道流速模型根据各条车
    道上的车辆的平均车速,以及无人驾驶车辆后方的车辆数量综合判断,使得得到的车道通
    畅程度值不受车辆行驶场景的限制,可以应对复杂多变的场景,对场景中道路状况进行了
    精确的建模,准备衡量了道路的拥堵情况,为换道策略的选择提供了可靠的依据;且根据车
    道上车辆的平均车速以及车辆数量的判断结果与人工判断结果相吻合,使得计算结果更为
    准确且贴合实际,从而为无人驾驶车辆是否换道提供了可靠的依据,使得所述无人驾驶车
    辆能够安全、可靠、高效的完成换道。

    其中,车道流速模型中各车道上车速、车辆数量,以及各个车辆相对所述无人驾驶
    车辆的位置等数据的获取通过在无人驾驶车辆上装设激光雷达、毫米波雷达、摄像头以及
    GPS定位模块等装置实现,数据的获得通过这些传感器的检测融合得到。

    一个优选方案中,所述车道流速模型的公式用于计算车道加权平均速度,所述通
    畅程度值由车道上行驶的车辆数量和平均速度决定。

    在上述方案中,通过计算车道加权平均速度能够准确的判断无人驾驶车辆进行换
    道的车速、时机等条件,通畅程度值由车道上行驶的车辆数量和平均速度决定符合人工驾
    驶时对于车道通畅程度的判断,因而保证了后续换道策略判断的可靠性。

    一个优选方案中,步骤B中将所述通畅程度值A和通畅程度值B进行比较以选择出
    目标车道的方法依据待选的车道相对于所述无人驾驶车辆所行驶的车道的通畅程度,所述
    通畅程度通过公式2表示:

    Vf=0.012V0×V0+0.52×V0 公式2

    其中,Vf表示待选的车道相对于所述无人驾驶车辆所行驶的车道的通畅程度;V0
    表示通畅程度值B。

    在上述方案中,通过待选的车道相对于所述无人驾驶车辆所行驶的车道的通畅程
    度的计算便于对于各车道间通畅程度的比较,从而利于换道策略的决策。

    一个优选方案中,步骤B中将所述通畅程度值A和通畅程度值B进行比较以选择出
    目标车道的方法还依据于经验数据库,所述经验数据库为由司机在各种道路上行驶的数据
    进行收集并整理得到。

    在上述方案中,通过司机在各种道路上行驶的数据的收集和整理得到的经验数据
    库的指导,使得所述无人驾驶车辆在进行换道决策时能够依据人工驾驶时的经验进行判
    断,从而进一步提高了策略决定的可靠性,提高了无人驾驶车辆的驾驶安全。

    一个优选方案中,当通畅程度值B大于19m/s,通畅程度值A小于最大通畅程度值的
    0.92倍,且通畅程度值B大于Vf时,判定所述无人驾驶车辆换道至目标车道。

    在上述方案中,依据公式2以及经验数据库的计算发现,目标车道的通畅程度必须
    大于19m/s时,本车道小于最大通畅程度的0.92倍,且目标车道的通畅程度值大于Vf时,目
    标车道较为通畅,可进行换道。

    一个优选方案中,当通畅程度值B小于Vf,通畅程度值B小于最大通畅程度值时,判
    定所述无人驾驶车辆在原车道上行驶。

    在上述方案中,依据公式2以及经验数据库的计算发现,在达到上述情况时,本车
    道较为通畅,无人驾驶车辆可以不必换道行驶。

    一个优选方案中,步骤B中将所述通畅程度值A和通畅程度值B进行比较以选择出
    目标车道的方法还依据于选择模块,所述选择模块在所述无人驾驶车辆满足换道条件,且
    所述无人驾驶车辆行驶在两边车道时,控制所述无人驾驶车辆换道至中间车道行驶。

    在上述方案中,通过选择模块的设置,使得该策略可以完成整个超车决策的功能,
    在实际的道路场景中可以准确、可靠、高效的选择出最优的车道,并可以应对复杂多变的道
    路场景。

    结合图2,横坐标表示待选目标车道的通畅程度,纵坐标表示本车道的通畅程度,
    该发明中我们使用车道流速模型中计算的结果来代表车道的通畅程度。a区域由曲线2、3、4
    围成,在a区域中时,目标车道的通畅程度必须大于19(最低限速值),本车道小于最大通畅
    程度的0.92倍(代表本车道速度受到压制,出现拥堵情况),曲线3则衡量了目标车道相对于
    本车道的通畅情况,所以当决策点落在a区域中时,目标车道较为通畅,可进行换道;在b区
    域中时,本车车道较为通畅,不进行换道,保持车道行驶;在c区域,并且该车行驶在两侧车
    道,结合选择模块的作用,要采取中间车道优先选择策略,即在该区域,车辆将从两边车道
    换回中间车道。

    尽管本发明的实施方案已公开如上,但其并不仅仅限于说明书和实施方式中所列
    运用,它完全可以被适用于各种适合本发明的领域,对于熟悉本领域的人员而言,可容易地
    实现另外的修改,因此在不背离权利要求及等同范围所限定的一般概念下,本发明并不限
    于特定的细节和这里所示出与描述的图例。

    无人驾驶自主换道策略

    Technical Field

    The present invention relates to unmanned technical field, in particular to an unmanned autonomous channel switching strategy.

    Background Art

    As people to automobile intelligent requirements increase, the unmanned vehicle as an intelligent driving has become the most concerned about the core technology. The vehicle during running of the vehicle lane is a common but complex acts, to a large extent the liquidity on roads, fast and safe channel switching operation to reducing the traffic accident has extremely strong significance of practical application.

    However, the actual road scene is very complicated and, therefore, how to achieve the unmanned vehicle not only can high-efficient, safe, and reliable accomplish independent channel switching, also can cover the complicated road scene, is undoubtedly a great challenge.

    Content of the invention

    The invention is directed to problems in the prior art of the above-mentioned problems, to provide an unmanned autonomous channel switching strategy, capable of dealing with all kinds of real road scene, the unmanned vehicle in various road scene in the efficient, safe, and reliable independent channel switching.

    In order to achieve the above-mentioned purpose and some of the other purpose, this invention adopts the following technical scheme:

    An unmanned autonomous channel switching strategy, mainly comprises the following steps:

    Step A, according to pre-set the formula 1 calculating to obtain the unmanned vehicle traffic lane of smooth degree value A and other lane the smoothness of the degree value B;

    Step B, will smooth degree value A and the unobstructed degree value B compare, in order to select the lowest level of traffic lane as a target lane is transmitted to the unmanned vehicle driving system;

    Wherein described in 1 lane flow rate model is of the formula:

    Z=X × [1/(1 + 0.3 × Y)] formula 1

    Wherein Z said smooth degree value; X that each lane of the average speed of the vehicle on the; Y said unmanned vehicle number of the rear of the vehicle.

    Preferably, the strategy in the unmanned autonomous lane, the lane model of the flow rate formula is used for calculating the weighted average speed lane, the smooth degree value by the number of vehicles running on the lane of the decision of the average speed.

    Preferably, the unmanned autonomous channel switching strategy, step B in the smooth degree value A and the unobstructed degree value B is compared in order to select the target lane of the method according to the candidate lane relative to the unmanned vehicle by the degree of smoothness of the driving lane, the smooth degree through the formula 2 that:

    Vf =0.012 V0 × V0 + 0.52 × V0 Formula 2

    Wherein Vf that the candidate lane relative to the unmanned vehicle by the degree of smoothness of the running lane; V0 said smooth degree value B.

    Preferably, the unmanned autonomous channel switching strategy, step B in the smooth degree value A and the unobstructed degree value B is compared in order to select the target lane method also on the basis of experience database, the database drivers experience on the ground in various driving on the road and finishing to obtain the data collected.

    Preferably, the unmanned autonomous channel switching strategy, when the smooth degree value B greater than 19 m/s, smooth degree value A is less than the maximum unobstructed [...] of 0.92 times, and smooth degree value B when greater than Vf, judge the lane [...] driving the vehicle to the target lane.

    Preferably, the unmanned autonomous channel switching strategy, when the smooth degree value B less than Vf, smooth degree value B is less than the maximum unobstructed degree value, judging the [...] driving the vehicle running on the original lane.

    Preferably, the unmanned autonomous channel switching strategy, step B in the smooth degree value A and the unobstructed degree value B is compared in order to select the target lane method also on the basis of the selection module, the selection module is in the unmanned vehicle to meet channel switching conditions, and the [...] driving vehicle running at the two sides of a lane, control the [...] driving lane to the middle lane of the vehicle.

    The invention comprises at least the following advantages:

    The invention the unmanned autonomous channel switching strategy by the establishment of a flow rate model lane, so that the [...] driving independent channel switching strategy is based upon lane flow rate model, according to the flow rate of the first lane model to analyze the degree of smoothness of the candidate lane, then the lane the vehicle itself with smooth situation compared to measure, from the chosen in the lowest level of traffic lane, as the optimum target lane, the lane model according to the velocity of the vehicle on the lane of the average vehicle speed, and the unmanned vehicle to judge the number of the rear of the vehicle, so that the obtained value is not affected by the degree of lane smooth vehicle running scene constraints, is suitable for various road scene, and according to the lane on the average speed of the vehicle and the vehicle number of the result of the judgment result of the judgment is matched with the manual, so that the calculation result is more accurate and attaching the actual, so as to whether the unmanned vehicle lane has offered the reliable basis, so that drive the vehicle [...] safe, reliable, and efficient completion of the channel switching.

    Other advantages of the present invention, objectives and features will reflect through the lower part of the note, segment will also be through to the study and practice of this invention is in the field of the technical understood.

    Description of drawings

    Figure 1 is the schematic view of the present invention provides unmanned autonomous channel switching strategy the lane of the velocity model;

    Figure 2 is the coordinates of the present invention provides unmanned autonomous channel switching strategy in the smooth degree value A and smooth degree value B is compared in order to select the target lane of the method.

    Mode of execution

    The Figure below to do a detailed description of this invention, to enable the ordinary skill in the art refer to this specification can be implemented after the basis.

    As shown in Figure 1 and Figure 2, an unmanned autonomous channel switching strategy, mainly comprises the following steps:

    Step A, according to pre-set the formula 1 calculating to obtain the unmanned vehicle traffic lane of smooth degree value A and other lane the smoothness of the degree value B;

    Step B, will smooth degree value A and the unobstructed degree value B compare, in order to select the lowest level of traffic lane as a target lane is transmitted to the unmanned vehicle driving system;

    Wherein described in 1 lane flow rate model is of the formula:

    Z=X × [1/(1 + 0.3 × Y)] formula 1

    Wherein Z said smooth degree value; X that each lane of the average speed of the vehicle on the; Y said unmanned vehicle number of the rear of the vehicle.

    In the above-mentioned scheme, lane flow rate model of each bus according to the number of road, and the average speed of the vehicle, in accordance with the judgment of the manual driving habits, realizes the simulation of manual decision-making, such that for a lane decision-making judgement more reliable and safe.

    The establishment of the flow rate through the lane model, so that the [...] driving independent lane strategy based on lane flow rate model, according to the flow rate of the first lane model to analyze the degree of smoothness of the candidate lane, then the lane the vehicle itself with smooth situation compared to measure, from the chosen in the lowest level of traffic lane, as the optimum target lane, the lane model according to the velocity of the vehicle on the lane of the average vehicle speed, and the unmanned vehicle to judge the number of the rear of the vehicle, so that the obtained value is not affected by the degree of lane smooth vehicle running scene restrictions, can cope with the complicated and changeable scene, the scene of the situation of the regulating accurate modeling, prepared is a measure of the road, for the choice of the channel switching strategy provides a reliable basis; and according to the lane on the average speed of the vehicle and the vehicle number of the result of the judgment result of the judgment is matched with the manual, so that the calculation result is more accurate and attaching the actual, so as to whether the unmanned vehicle lane has offered the reliable basis, so that drive the vehicle [...] safe, reliable, efficient completion of the channel switching.

    Wherein lane flow speed on all lanes in the model, the number of vehicles, each vehicle and [...] drive the vehicle relative to the position of the acquisition of the data such as the unmanned vehicle by is arranged on the laser radar, a millimeter wave radar, camera and GPS positioning module and other device to realize, the availability of data through these sensor detection fused to obtain.

    In one preferred embodiment, the lane model of the flow rate formula is used for calculating the weighted average speed lane, the smooth degree value by the number of vehicles running on the lane of the decision of the average speed.

    In the above-mentioned scheme, by calculating the weighted average speed lane can accurately judge the unmanned vehicle lane change of the vehicle speed, the timing conditions and the like, smooth degree value by the number of vehicles on the lane of the running average speed determine where infectious diseases caused when driving lane smooth for the judgment, thereby ensuring the reliability of the lane strategy determination of follow-up.

    In one preferred embodiment, in step B the smooth degree value A and the unobstructed degree value B is compared in order to select the target lane of the method according to the candidate lane relative to the unmanned vehicle by the degree of smoothness of the driving lane, the smooth degree through the formula 2 that:

    Vf =0.012 V0 × V0 + 0.52 × V0 Formula 2

    Wherein Vf that the candidate lane relative to the unmanned vehicle by the degree of smoothness of the running lane; V0 said smooth degree value B.

    In the above-mentioned scheme in, through the candidate lane relative to the unmanned vehicle by the smoothness of the running lane of the calculation of the degree of convenient for each vehicle track smooth degree of comparison, thereby facilitating the channel switching strategy decision-making.

    In one preferred embodiment, in step B the smooth degree value A and the unobstructed degree value B is compared in order to select the target lane method also on the basis of experience database, the database drivers experience on the ground in various driving on the road and finishing to obtain the data collected.

    In the above-mentioned scheme in, through the drivers in various driving on the road data collection and finishing the experience database guidance, so that the [...] driving the vehicle in the lane decision-making can be according to artificial when driving experience to judge, thus further improving the reliability of the decision strategy, without a person who drives a vehicle driving safety.

    In one preferred embodiment, when the smooth degree value B greater than 19 m/s, smooth degree value A is less than the maximum unobstructed [...] of 0.92 times, and smooth degree value B when greater than Vf, judge the lane [...] driving the vehicle to the target lane.

    In the above-mentioned scheme, according to formula 2 and the calculation of the experience database found, the smoothness of the target lane must be greater than 19 m/s when, the lane is less than the maximum unobstructed degree of 0.92 times, and the smoothness of the target lane when the degree value is more than Vf, target lane more smooth, lane can be carried out.

    In one preferred embodiment, when the smooth degree value B less than Vf, smooth degree value B is less than the maximum unobstructed degree value, judging the [...] driving the vehicle running on the original lane.

    In the above-mentioned scheme, according to formula 2 and the calculation of the experience database found, achieve the above situation, the more smooth the lane, the unmanned vehicle does not need to be changing road.

    In one preferred embodiment, in step B the smooth degree value A and the unobstructed degree value B is compared in order to select the target lane method also on the basis of the selection module, the selection module is in the unmanned vehicle to meet channel switching conditions, and the [...] driving vehicle running at the two sides of a lane, control the [...] driving lane to the middle lane of the vehicle.

    In the above-mentioned scheme in, by selecting the arrangement of the module, so that the strategy to be completed in the overtaking of decision-making functions, in the actual road scene can be accurate, reliable, and efficient to select the optimal lane, and can cope with the complicated and changeable road scene.

    The combination of Figure 2, indicating on an abscissa a candidate target lane of the degree of smooth, indicating on the ordinate a degree of smoothness of the lane, the lane in the invention we use the result of the calculation in the flow model to represent the degree of smoothness of the lane. A region is formed by curves 2, 3, 4 form, in a zone, the smoothness of the target lane must be greater than 19 (minimum of two connecting), the lane is less than the maximum unobstructed degree of 0.92 times (on behalf of the traffic lane velocity to be suppressed, the occurrence of the jamming condition), curve 3 is a measure of the target lane relative to the lane the smoothness of the situation, so when the decision-making is clicked in a zone, the target lane more smooth, can be lane; in the b zone, the vehicle lane is comparatively smooth, does not carry out a channel, keep the lane; in the area c, and the vehicle running on both sides of the lane, the role of the select module, it is necessary to take the middle lane priority selection strategy, in that region, the vehicle will be in the middle of the lane from the two sides of the back lane.

    Although the embodiments of the invention have been disclosed above, but not limited to the specification and embodiments set out in the application, it is fully can be suitable for various suitable for the field of this invention, familiar in the case of the field personnel, can be easily achieved in addition changes, therefore without departing from the claims and the equivalent of the scope of the general concept of defined, the invention is not limited to the specific details shown and described here of the legend.

    Unmanned automatic lane changing policy
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