论文通过真实道路试验获得乘用车驾驶员特性试验数据,得到不同类型驾驶员跟车行为特性参数,提出了适应驾驶员特性的基于避撞时间TTC(Time to Collision)的报警算法,确定了报警-避撞启动逻辑,并且根据驾驶员异常行为的试验数据统计得到报...论文通过真实道路试验获得乘用车驾驶员特性试验数据,得到不同类型驾驶员跟车行为特性参数,提出了适应驾驶员特性的基于避撞时间TTC(Time to Collision)的报警算法,确定了报警-避撞启动逻辑,并且根据驾驶员异常行为的试验数据统计得到报警-避撞阈值。试验结果表明,所提出的追尾报警-避撞算法能够体现不同类型的驾驶员特性,有效提高汽车追尾报警-避撞系统的可接受性。展开更多
Sm-Nd isotopic ages for C-type eclogite (243.9±5.6 Ma) and mafic and ultramafic rocks(230.6±30.7 Ma and 402.6±17.4 Ma) from the Qinling-Dabieshan orogenic belt are reported.These ages suggest that at th...Sm-Nd isotopic ages for C-type eclogite (243.9±5.6 Ma) and mafic and ultramafic rocks(230.6±30.7 Ma and 402.6±17.4 Ma) from the Qinling-Dabieshan orogenic belt are reported.These ages suggest that at the early Triassic, the North and South China Blocks have beenunited along the Qinling-Dabieshan collision zone, and before the final collision, a se-ries of ophiolite obductions took place successively away from the continental marginduring the Paleozoic.展开更多
Multiple Uninhabited Aerial Vehicles (multi-UAVs) coordinated trajectory replanning is one of the most complicated global optimum problems in multi-UAVs coordinated control. Based on the construction of the basic mode...Multiple Uninhabited Aerial Vehicles (multi-UAVs) coordinated trajectory replanning is one of the most complicated global optimum problems in multi-UAVs coordinated control. Based on the construction of the basic model of multi-UAVs coordinated trajectory replanning, which includes problem description, threat modeling, constraint conditions, coordinated function and coordination mechanism, a novel Max-Min adaptive Ant Colony Optimization (ACO) approach is presented in detail. In view of the characteristics of multi-UAVs coordinated trajectory replanning in dynamic and uncertain environments, the minimum and maximum pheromone trails in ACO are set to enhance the searching capability, and the point pheromone is adopted to achieve the collision avoidance between UAVs at the trajectory planner layer. Considering the simultaneous arrival and the air-space collision avoidance, an Estimated Time of Arrival (ETA) is decided first. Then the trajectory and flight velocity of each UAV are determined. Simulation experiments are performed under the complicated combating environment containing some static threats and popup threats. The results demonstrate the feasibility and the effectiveness of the proposed approach.展开更多
针对一般车辆碰撞时间(time to collision,TTC)算法预警阈值固定造成车辆低速行驶中出现预警过早及高速行驶出现预警不及时的问题,该文提出一种基于行驶车速的车辆防撞时间预警方法。行驶车辆通过车载设备实时获取自车与他车的状态信息...针对一般车辆碰撞时间(time to collision,TTC)算法预警阈值固定造成车辆低速行驶中出现预警过早及高速行驶出现预警不及时的问题,该文提出一种基于行驶车速的车辆防撞时间预警方法。行驶车辆通过车载设备实时获取自车与他车的状态信息,根据车辆状态信息建立高斯平面坐标系获取车辆位置坐标,对车辆可能发生的碰撞进行分类处理,依据车辆行驶速度设定相应的安全防撞时间,然后将车辆发生碰撞需要的时间与安全防撞时间进行比较,存在碰撞危险则通过预警显示提醒驾驶员。试验结果表明:该方法预警准确率达88.89%,而一般TTC固定阈值方法则预警过早率达81.48%,预警过晚率达70.37%,故该方法对进行车辆危险预警更有效,更符合实际车辆防撞情形,提高了车辆行驶的安全性,可为车辆的及时预警提供参考。展开更多
In this paper, we consider the local time and the self-intersection local time for a bifractional Brownian motion, and the collision local time for two independent bifractional Brownian motions. We mainly prove the ex...In this paper, we consider the local time and the self-intersection local time for a bifractional Brownian motion, and the collision local time for two independent bifractional Brownian motions. We mainly prove the existence and smoothness of the self-intersection local time and the collision local time, through the strong local nondeterminism of bifractional Brownian motion, L2 convergence and Chaos expansion.展开更多
跟驰行为是微观交通流中最基本的交通行为之一,选用NGSIM轨迹数据对车辆跟驰行为的微观特性进行研究,分析跟驰行为由安全状态变为危险状态的影响因素及原因。选取碰撞时间(time to collision,TTC)为安全指标,将TTC处于不同状态下的帧数...跟驰行为是微观交通流中最基本的交通行为之一,选用NGSIM轨迹数据对车辆跟驰行为的微观特性进行研究,分析跟驰行为由安全状态变为危险状态的影响因素及原因。选取碰撞时间(time to collision,TTC)为安全指标,将TTC处于不同状态下的帧数作为因变量,将速度、加速度、加速度差分等微观特性变量作为自变量,并设定4种阈值回归分析。结果表明:对跟驰行为由安全状态变为危险状态,影响最大的因素为前后车速度差,前后车平均车头间距次之,但当存在大量跟驰行为时,前后车平均车头间距的影响更大,后车的微观特征对此产生的影响多于前车;为使跟驰行为保持在安全状态,应增加前车的速度、加速度、加速度差分和前后车平均车头间距,同时应减小后车的加速度、加速度差分和前后车速度差值;考虑到车流连续性,整体而言应使前后车保持相近的速度,避免突然加速或减速,且应保持适当的车头间距,并加强后车的管控。展开更多
Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajec...Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.展开更多
Camellia is the final winner of 128-bit block cipher in NESSIE. In this paper, we construct some efficient distinguishers between 4-round Camellia and a random permutation of the blocks space. By using collision-searc...Camellia is the final winner of 128-bit block cipher in NESSIE. In this paper, we construct some efficient distinguishers between 4-round Camellia and a random permutation of the blocks space. By using collision-searching techniques, the distinguishers are used to attack on 6, 7, 8 and 9 rounds of Camellia with 128-bit key and 8, 9 and 10 rounds of Camellia with 192/256-bit key. The 128-bit key of 6 rounds Camellia can be recovered with 210 chosen plaintexts and 215 encryptions. The 128-bit key of 7 rounds Camellia can be recovered with 212 chosen plaintexts and 254.5 encryptions. The 128-bit key of 8 rounds Camellia can be recovered with 213 chosen plaintexts and 2112.1 encryptions. The 128-bit key of 9 rounds Camellia can be recovered with 2113.6 chosen plaintexts and 2121 encryptions. The 192/256-bit key of 8 rounds Camellia can be recovered with 213 chosen plaintexts and 2111.1 encryptions. The 192/256-bit key of 9 rounds Camellia can be recovered with 213 chosen plaintexts and 2175.6 encryptions. The 256-bit key of 10 rounds Camellia can be recovered with 214 chosen plaintexts and 2239.9 encryptions.展开更多
文摘论文通过真实道路试验获得乘用车驾驶员特性试验数据,得到不同类型驾驶员跟车行为特性参数,提出了适应驾驶员特性的基于避撞时间TTC(Time to Collision)的报警算法,确定了报警-避撞启动逻辑,并且根据驾驶员异常行为的试验数据统计得到报警-避撞阈值。试验结果表明,所提出的追尾报警-避撞算法能够体现不同类型的驾驶员特性,有效提高汽车追尾报警-避撞系统的可接受性。
文摘Sm-Nd isotopic ages for C-type eclogite (243.9±5.6 Ma) and mafic and ultramafic rocks(230.6±30.7 Ma and 402.6±17.4 Ma) from the Qinling-Dabieshan orogenic belt are reported.These ages suggest that at the early Triassic, the North and South China Blocks have beenunited along the Qinling-Dabieshan collision zone, and before the final collision, a se-ries of ophiolite obductions took place successively away from the continental marginduring the Paleozoic.
基金supported by the Natural Science Foundation of China (Grant no.60604009)Aeronautical Science Foundation of China (Grant no.2006ZC51039,Beijing NOVA Program Foundation of China (Grant no.2007A017)+1 种基金Open Fund of the Provincial Key Laboratory for Information Processing Technology,Suzhou University (Grant no KJS0821)"New Scientific Star in Blue Sky"Talent Program of Beihang University of China
文摘Multiple Uninhabited Aerial Vehicles (multi-UAVs) coordinated trajectory replanning is one of the most complicated global optimum problems in multi-UAVs coordinated control. Based on the construction of the basic model of multi-UAVs coordinated trajectory replanning, which includes problem description, threat modeling, constraint conditions, coordinated function and coordination mechanism, a novel Max-Min adaptive Ant Colony Optimization (ACO) approach is presented in detail. In view of the characteristics of multi-UAVs coordinated trajectory replanning in dynamic and uncertain environments, the minimum and maximum pheromone trails in ACO are set to enhance the searching capability, and the point pheromone is adopted to achieve the collision avoidance between UAVs at the trajectory planner layer. Considering the simultaneous arrival and the air-space collision avoidance, an Estimated Time of Arrival (ETA) is decided first. Then the trajectory and flight velocity of each UAV are determined. Simulation experiments are performed under the complicated combating environment containing some static threats and popup threats. The results demonstrate the feasibility and the effectiveness of the proposed approach.
文摘针对一般车辆碰撞时间(time to collision,TTC)算法预警阈值固定造成车辆低速行驶中出现预警过早及高速行驶出现预警不及时的问题,该文提出一种基于行驶车速的车辆防撞时间预警方法。行驶车辆通过车载设备实时获取自车与他车的状态信息,根据车辆状态信息建立高斯平面坐标系获取车辆位置坐标,对车辆可能发生的碰撞进行分类处理,依据车辆行驶速度设定相应的安全防撞时间,然后将车辆发生碰撞需要的时间与安全防撞时间进行比较,存在碰撞危险则通过预警显示提醒驾驶员。试验结果表明:该方法预警准确率达88.89%,而一般TTC固定阈值方法则预警过早率达81.48%,预警过晚率达70.37%,故该方法对进行车辆危险预警更有效,更符合实际车辆防撞情形,提高了车辆行驶的安全性,可为车辆的及时预警提供参考。
基金supported by National Natural Science Foundation of China (Grant No.10871103)
文摘In this paper, we consider the local time and the self-intersection local time for a bifractional Brownian motion, and the collision local time for two independent bifractional Brownian motions. We mainly prove the existence and smoothness of the self-intersection local time and the collision local time, through the strong local nondeterminism of bifractional Brownian motion, L2 convergence and Chaos expansion.
文摘跟驰行为是微观交通流中最基本的交通行为之一,选用NGSIM轨迹数据对车辆跟驰行为的微观特性进行研究,分析跟驰行为由安全状态变为危险状态的影响因素及原因。选取碰撞时间(time to collision,TTC)为安全指标,将TTC处于不同状态下的帧数作为因变量,将速度、加速度、加速度差分等微观特性变量作为自变量,并设定4种阈值回归分析。结果表明:对跟驰行为由安全状态变为危险状态,影响最大的因素为前后车速度差,前后车平均车头间距次之,但当存在大量跟驰行为时,前后车平均车头间距的影响更大,后车的微观特征对此产生的影响多于前车;为使跟驰行为保持在安全状态,应增加前车的速度、加速度、加速度差分和前后车平均车头间距,同时应减小后车的加速度、加速度差分和前后车速度差值;考虑到车流连续性,整体而言应使前后车保持相近的速度,避免突然加速或减速,且应保持适当的车头间距,并加强后车的管控。
基金financial support from the Civil Aviation Joint Funds of the National Natural Science Foundation of China (No’s.U1533203,61179069)
文摘Conflict Detection and Resolution（CD＆R） is the key to ensure aviation safety based on Trajectory Prediction（TP）. Uncertainties that affect aircraft motions cause difficulty in an accurate prediction of the trajectory, especially in the context of four-dimensional（4D） Trajectory-Based Operation（4DTBO）, which brings the uncertainty of pilot intent. This study draws on the idea of time geography, and turns the research focus of CD＆R from TP to an analysis of the aircraft reachable space constrained by 4D waypoint constraints. The concepts of space–time reachability of aircraft and space–time potential conflict space are proposed. A novel pre-CD＆R scheme for multiple aircraft is established. A key advantage of the scheme is that the uncertainty of pilot intent is accounted for via a Space-Time Prism（STP） for aircraft. Conflict detection is performed by verifying whether the STPs of aircraft intersect or not, and conflict resolution is performed by planning a conflict-free space–time trajectory avoiding intersection. Numerical examples are presented to validate the efficiency of the proposed scheme.
基金supported by the National Natural Science Foundation of China(Grant No.60373047)the State 863 Project(Grant No.2003AA144030)973 Project(Grant No.2004CB318004)
文摘Camellia is the final winner of 128-bit block cipher in NESSIE. In this paper, we construct some efficient distinguishers between 4-round Camellia and a random permutation of the blocks space. By using collision-searching techniques, the distinguishers are used to attack on 6, 7, 8 and 9 rounds of Camellia with 128-bit key and 8, 9 and 10 rounds of Camellia with 192/256-bit key. The 128-bit key of 6 rounds Camellia can be recovered with 210 chosen plaintexts and 215 encryptions. The 128-bit key of 7 rounds Camellia can be recovered with 212 chosen plaintexts and 254.5 encryptions. The 128-bit key of 8 rounds Camellia can be recovered with 213 chosen plaintexts and 2112.1 encryptions. The 128-bit key of 9 rounds Camellia can be recovered with 2113.6 chosen plaintexts and 2121 encryptions. The 192/256-bit key of 8 rounds Camellia can be recovered with 213 chosen plaintexts and 2111.1 encryptions. The 192/256-bit key of 9 rounds Camellia can be recovered with 213 chosen plaintexts and 2175.6 encryptions. The 256-bit key of 10 rounds Camellia can be recovered with 214 chosen plaintexts and 2239.9 encryptions.
