Human rights, as a great term and lofty goal, have unquestionably become a topic of mainstream talk in the present-day world.2 Such mainstream talk has been internal- ized into part of the social structure. The curren...Human rights, as a great term and lofty goal, have unquestionably become a topic of mainstream talk in the present-day world.2 Such mainstream talk has been internal- ized into part of the social structure. The current international society is experiencing a profound reorganization and transition in values. All kinds of new interactions under the context of globalization have resulted in the development of the current norms of international human rights, which are constructed on the basis of law and ethics. Therefore, analyzing the dynamic factors of socialization that support the operation of human rights norms in international society has become increasingly important in today＇s mutually dependent society.展开更多
The implementation of the Western China Development Strategy is a concrete expression of accelerating the economic development and social progress and sateguarding and protecting the right to subsistence and developme...The implementation of the Western China Development Strategy is a concrete expression of accelerating the economic development and social progress and sateguarding and protecting the right to subsistence and development of the people in that part of the country,展开更多
To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This st...To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This study proposes a probabilistic decision-making and trajectory planning framework for the autonomous heavy trucks. Firstly, the driving decision process is divided into intention generation and feasibility evaluations, which are realized using the utility theory and risk assessment, respectively. Subsequently the driving decision is made and sent to the trajectory planning module. In order to reflect the greater risks of the truck to other surrounding vehicles, the aggressiveness index(AI) is proposed and quantified to infer the asymmetrical risk level of lane-change maneuver. In the planning stage, the lateral and roll dynamics stability domains are developed as the constraints to exclude the candidate trajectories that would cause vehicle instability. Finally, the simulation results are compared between the proposed model and the artificial potential filed model in the scenarios extracted from the naturalistic driving data. It is shown that the proposed framework can provide the human-like lane-change decisions and truck-friendly trajectories, and performs well in dynamic driving environments.展开更多
In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes.Howe...In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes.However, few studies detected the factors unique to single and multiple crashes, and none have examined these underlying factors to severe truck crashes in conjunction with violation data. The current research assessed all of these factors using two approaches to improve truck safety.The first approach used ordinal logistic regression to investigate the contributory factors that increased the odds of severe single-truck and multiple-vehicle crashes, with involvement of at least one truck. The literature has indicated that past violations can be used to predict future violations and crashes. Therefore, the second approach used risky violations, related to truck crashes, to identify the contributory factors to the risky violations and truck crashes. Driver actions of failure to keep proper lane following too close and driving too fast for conditions accounted for about 40% of all the truck crashes. Therefore, the same violations as the aforementioned driver actions were included in the analysis. Based on ordinal logistic regression, the analysis for the first approach indicated that being under non-normal conditions at the time of crash, driving on dry-road condition and having a distraction in the cabin are some of the factors that increase the odds of severe single-truck crashes. On the other hand,speed compliance, alcohol involvement, and posted speed limits are some of the variables that impacted the severity of multiple-vehicle, truck-involved crashes. With the second approach, the violations related to risky driver actions,which were underlying causes of severe truck crashes, were identified and analysis was run to identify the groups at increased risk of truck-involved crashes. The results of violations indicated that being nonresident, driving offpeak hours, and driving on weekends could increase the risk of truck-involved crashes. This paper offers an insight into the capability of using violation data, in addition to crash data, in identification of possible countermeasures to reduce crash frequency.展开更多
Professional truck drivers are an essential part of transportation in keeping the global economy alive and commercial products moving. In order to increase productivity and improve safety, an increasing amount of auto...Professional truck drivers are an essential part of transportation in keeping the global economy alive and commercial products moving. In order to increase productivity and improve safety, an increasing amount of automation is implemented in modern trucks. Transition to automated heavy good vehicles is intended to make trucks accident-free and, on the other hand, more comfortable to drive. This motivates the automotive industry to bring more embedded ICT into their vehicles in the future. An avenue towards autonomous vehicles requires robust environmental perception and driver monitoring technologies to be introduced. This is the main motivation behind the DESERVE project. This is the study of sensor technology trials in order to minimize blind spots around the truck and, on the other hand, keep the driver’s vigilance at a sufficiently high level. The outcomes are two innovative truck demonstrations: one R & D study for bringing equipment to production in the future and one implementation to the driver training vehicle. The earlier experiments include both driver monitoring technology which works at a 60% - 80% accuracy level and environment perception (stereo and thermal cameras) whose performance rates are 70% - 100%. The results are not sufficient for autonomous vehicles, but are a step forward, since they are in-line even if moved from the lab to real automotive implementations.展开更多
露天矿无人矿车在装卸载作业区内运输过程中的长时间停车等待是制约露天矿无人运输系统效率提升的瓶颈。为提高无人矿车的运输效率,本文结合作业区内的运输作业流程,提出一种基于动态可行驶距离的多车协同通行决策方法。首先,将决策模...露天矿无人矿车在装卸载作业区内运输过程中的长时间停车等待是制约露天矿无人运输系统效率提升的瓶颈。为提高无人矿车的运输效率,本文结合作业区内的运输作业流程,提出一种基于动态可行驶距离的多车协同通行决策方法。首先,将决策模型建模为混合整数线性规划(Mixed Integer Linear Programming, MILP)模型,表述优化目标和问题约束;其次,考虑到求解MILP模型存在难以满足动态决策实时性的问题,基于蒙特卡洛树搜索(Monte Carlo Tree Search,MCTS)实现多车冲突消解,核心思想是利用搜索树的推演能力进行多车通行前瞻模拟,计算多车的最优通行优先级,动态调整多车的可行驶距离;此外,根据无人矿车在作业区内的作业特征设计不同的MCTS节点价值函数,实现综合考虑运输效率与作业特征的通行优先级排序;最后,设计作业区4,8,12个停车位场景下的多车通行仿真实验,与基于先到先服务(First-Come-FirstServed, FCFS)的方法进行对比,吞吐量提升22.03%~28.00%,平均停车等待时间缩短31.71%~50.79%。同时,搭建微缩智能车辆的6停车位作业区场景实验平台,多车单次运输作业总用时相比FCFS缩短了18.84%。仿真与微缩智能车辆的实验结果表明,本文提出的方法能够提升露天矿作业区多车运输效率。展开更多
With the high older-related accident ratio and increasing population aging problem, understanding older drivers＇ driving behaviors has become more and more important for building and improving transportation system. ...With the high older-related accident ratio and increasing population aging problem, understanding older drivers＇ driving behaviors has become more and more important for building and improving transportation system. This paper examines older driver＇s driving behavior which includes road selection, left/right turn and driving speed. A two-month experiment of 108 participants was carried out in Aichi Prefecture, Japan. Since apparently contradictory statements were often drawn in survey-based or simulators-based studies, this study collected not only drivers＇ basic information but also GPS data. Analysis of road selection demonstrates that older drivers are reluctant to drive on expressway not only in short trips but also in long trips. The present study did not find significant difference be- tween older drivers and others while turning at the intersections. To investigate the impact factors on driving speed, a random-effects regression model is constructed with explan- atory variables including age, gender, road types and the interaction terms between age and road types. Compared with other variables, it fails to find that age （60 years old or over） has significant impact on driving speed. Moreover, the results reflect that older drivers drive even faster than others at particular road types： national road and ordinary municipal road. The results in this study are expected to help improve transportation planning and develop driving assistance systems for older drivers.展开更多
文摘Human rights, as a great term and lofty goal, have unquestionably become a topic of mainstream talk in the present-day world.2 Such mainstream talk has been internal- ized into part of the social structure. The current international society is experiencing a profound reorganization and transition in values. All kinds of new interactions under the context of globalization have resulted in the development of the current norms of international human rights, which are constructed on the basis of law and ethics. Therefore, analyzing the dynamic factors of socialization that support the operation of human rights norms in international society has become increasingly important in today＇s mutually dependent society.
文摘The implementation of the Western China Development Strategy is a concrete expression of accelerating the economic development and social progress and sateguarding and protecting the right to subsistence and development of the people in that part of the country,
基金supported by the National Natural Science Foundation of China(5187051675)。
文摘To improve the safety and driving stability of the autonomous heavy truck, it is necessary to consider the differences of driving behavior and drivable trajectories between the heavy trucks and passenger cars. This study proposes a probabilistic decision-making and trajectory planning framework for the autonomous heavy trucks. Firstly, the driving decision process is divided into intention generation and feasibility evaluations, which are realized using the utility theory and risk assessment, respectively. Subsequently the driving decision is made and sent to the trajectory planning module. In order to reflect the greater risks of the truck to other surrounding vehicles, the aggressiveness index(AI) is proposed and quantified to infer the asymmetrical risk level of lane-change maneuver. In the planning stage, the lateral and roll dynamics stability domains are developed as the constraints to exclude the candidate trajectories that would cause vehicle instability. Finally, the simulation results are compared between the proposed model and the artificial potential filed model in the scenarios extracted from the naturalistic driving data. It is shown that the proposed framework can provide the human-like lane-change decisions and truck-friendly trajectories, and performs well in dynamic driving environments.
文摘In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes.However, few studies detected the factors unique to single and multiple crashes, and none have examined these underlying factors to severe truck crashes in conjunction with violation data. The current research assessed all of these factors using two approaches to improve truck safety.The first approach used ordinal logistic regression to investigate the contributory factors that increased the odds of severe single-truck and multiple-vehicle crashes, with involvement of at least one truck. The literature has indicated that past violations can be used to predict future violations and crashes. Therefore, the second approach used risky violations, related to truck crashes, to identify the contributory factors to the risky violations and truck crashes. Driver actions of failure to keep proper lane following too close and driving too fast for conditions accounted for about 40% of all the truck crashes. Therefore, the same violations as the aforementioned driver actions were included in the analysis. Based on ordinal logistic regression, the analysis for the first approach indicated that being under non-normal conditions at the time of crash, driving on dry-road condition and having a distraction in the cabin are some of the factors that increase the odds of severe single-truck crashes. On the other hand,speed compliance, alcohol involvement, and posted speed limits are some of the variables that impacted the severity of multiple-vehicle, truck-involved crashes. With the second approach, the violations related to risky driver actions,which were underlying causes of severe truck crashes, were identified and analysis was run to identify the groups at increased risk of truck-involved crashes. The results of violations indicated that being nonresident, driving offpeak hours, and driving on weekends could increase the risk of truck-involved crashes. This paper offers an insight into the capability of using violation data, in addition to crash data, in identification of possible countermeasures to reduce crash frequency.
基金European Commission under the ECSEL Joint Undertaking and TEKES–the Finnish Funding Agency for Innovation
文摘Professional truck drivers are an essential part of transportation in keeping the global economy alive and commercial products moving. In order to increase productivity and improve safety, an increasing amount of automation is implemented in modern trucks. Transition to automated heavy good vehicles is intended to make trucks accident-free and, on the other hand, more comfortable to drive. This motivates the automotive industry to bring more embedded ICT into their vehicles in the future. An avenue towards autonomous vehicles requires robust environmental perception and driver monitoring technologies to be introduced. This is the main motivation behind the DESERVE project. This is the study of sensor technology trials in order to minimize blind spots around the truck and, on the other hand, keep the driver’s vigilance at a sufficiently high level. The outcomes are two innovative truck demonstrations: one R & D study for bringing equipment to production in the future and one implementation to the driver training vehicle. The earlier experiments include both driver monitoring technology which works at a 60% - 80% accuracy level and environment perception (stereo and thermal cameras) whose performance rates are 70% - 100%. The results are not sufficient for autonomous vehicles, but are a step forward, since they are in-line even if moved from the lab to real automotive implementations.
文摘露天矿无人矿车在装卸载作业区内运输过程中的长时间停车等待是制约露天矿无人运输系统效率提升的瓶颈。为提高无人矿车的运输效率,本文结合作业区内的运输作业流程,提出一种基于动态可行驶距离的多车协同通行决策方法。首先,将决策模型建模为混合整数线性规划(Mixed Integer Linear Programming, MILP)模型,表述优化目标和问题约束;其次,考虑到求解MILP模型存在难以满足动态决策实时性的问题,基于蒙特卡洛树搜索(Monte Carlo Tree Search,MCTS)实现多车冲突消解,核心思想是利用搜索树的推演能力进行多车通行前瞻模拟,计算多车的最优通行优先级,动态调整多车的可行驶距离;此外,根据无人矿车在作业区内的作业特征设计不同的MCTS节点价值函数,实现综合考虑运输效率与作业特征的通行优先级排序;最后,设计作业区4,8,12个停车位场景下的多车通行仿真实验,与基于先到先服务(First-Come-FirstServed, FCFS)的方法进行对比,吞吐量提升22.03%~28.00%,平均停车等待时间缩短31.71%~50.79%。同时,搭建微缩智能车辆的6停车位作业区场景实验平台,多车单次运输作业总用时相比FCFS缩短了18.84%。仿真与微缩智能车辆的实验结果表明,本文提出的方法能够提升露天矿作业区多车运输效率。
文摘With the high older-related accident ratio and increasing population aging problem, understanding older drivers＇ driving behaviors has become more and more important for building and improving transportation system. This paper examines older driver＇s driving behavior which includes road selection, left/right turn and driving speed. A two-month experiment of 108 participants was carried out in Aichi Prefecture, Japan. Since apparently contradictory statements were often drawn in survey-based or simulators-based studies, this study collected not only drivers＇ basic information but also GPS data. Analysis of road selection demonstrates that older drivers are reluctant to drive on expressway not only in short trips but also in long trips. The present study did not find significant difference be- tween older drivers and others while turning at the intersections. To investigate the impact factors on driving speed, a random-effects regression model is constructed with explan- atory variables including age, gender, road types and the interaction terms between age and road types. Compared with other variables, it fails to find that age （60 years old or over） has significant impact on driving speed. Moreover, the results reflect that older drivers drive even faster than others at particular road types： national road and ordinary municipal road. The results in this study are expected to help improve transportation planning and develop driving assistance systems for older drivers.
