Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum.The precise reasons behind the specific degeneration of t...Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum.The precise reasons behind the specific degeneration of these dopamine neurons remain largely elusive.Genetic investigations have identified over 20 causative PARK genes and 90 genomic risk loci associated with both familial and sporadic Parkinson's disease.Notably,several of these genes are linked to the synaptic vesicle recycling process,particularly the clathrinmediated endocytosis pathway.This suggests that impaired synaptic vesicle recycling might represent an early feature of Parkinson's disease,followed by axonal degeneration and the eventual loss of dopamine cell bodies in the midbrain via a"dying back"mechanism.Recently,several new animal and cellular models with Parkinson's disease-linked mutations affecting the endocytic pathway have been created and extensively characterized.These models faithfully recapitulate certain Parkinson's disease-like features at the animal,circuit,and cellular levels,and exhibit defects in synaptic membrane trafficking,further supporting the findings from human genetics and clinical studies.In this review,we will first summarize the cellular and molecular findings from the models of two Parkinson's disease-linked clathrin uncoating proteins:auxilin(DNAJC6/PARK19)and synaptojanin 1(SYNJ1/PARK20).The mouse models carrying these two PARK gene mutations phenocopy each other with specific dopamine terminal pathology and display a potent synergistic effect.Subsequently,we will delve into the involvement of several clathrin-mediated endocytosis-related proteins(GAK,endophilin A1,SAC2/INPP5 F,synaptotagmin-11),identified as Parkinson's disease risk factors through genome-wide association studies,in Parkinson's disease pathogenesis.We will also explore the direct or indirect roles of some common Parkinson's disease-linked proteins(alpha-synuclein(PARK1/4),Parkin(PARK2),and LRRK2(PARK8))in synaptic endocytic trafficking.Additionally,we will discuss the emerging novel functions of these endocytic proteins in downstream membrane traffic pathways,particularly autophagy.Given that synaptic dysfunction is considered as an early event in Parkinson's disease,a deeper understanding of the cellular mechanisms underlying synaptic vesicle endocytic trafficking may unveil novel to rgets for early diagnosis and the development of interventional therapies for Parkinson's disease.Future research should aim to elucidate why generalized synaptic endocytic dysfunction leads to the selective degeneration of nigrostriatal dopamine neurons in Parkinson's disease.展开更多
Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adja...Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.展开更多
在规模化养殖模式下,畜禽在生长过程中会不可避免地面对各种不利因素,导致体内产生氧化应激,严重影响其生长发育。畜禽体内存在多种抗氧化因子来应对氧化应激。其中,帕金森相关蛋白7(Parkinson’s Disease-Associated Protein 7,PARK7)...在规模化养殖模式下,畜禽在生长过程中会不可避免地面对各种不利因素,导致体内产生氧化应激,严重影响其生长发育。畜禽体内存在多种抗氧化因子来应对氧化应激。其中,帕金森相关蛋白7(Parkinson’s Disease-Associated Protein 7,PARK7)基因是细胞氧化应激中重要的调控因子之一。PARK7通过自身半胱氨酸的氧化水平感受氧化应激信号,并通过Nrf2、ERK1/2和PI3K/Akt等途径促进抗氧化酶的生成,提高细胞的抗氧化能力,从而减轻氧化应激引起的损伤。本文对PARK7基因在氧化应激中的调控作用和通路进行综述,将有助于畜禽氧化应激的调节机制研究。展开更多
Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding s...Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.展开更多
Vegetation resilience(VR),providing an objective measure of ecosystem health,has received considerable attention,however,there is still limited understanding of whether the dominant factors differ across different cli...Vegetation resilience(VR),providing an objective measure of ecosystem health,has received considerable attention,however,there is still limited understanding of whether the dominant factors differ across different climate zones.We took the three national parks(Hainan Tropical Rainforest National Park,HTR;Wuyishan National Park,WYS;and Northeast Tiger and Leopard National Park,NTL)of China with less human interference as cases,which are distributed in different climatic zones,including tropical,subtropical and temperate monsoon climates,respectively.Then,we employed the probabilistic decay method to explore the spatio-temporal changes in the VR and their natural driving patterns using Geographically Weighted Regression(GWR)model as well.The results revealed that:(1)from 2000 to 2020,the Normalized Difference Vegetation Index(NDVI)of the three national parks fluctuated between 0.800 and 0.960,exhibiting an overall upward trend,with the mean NDVI of NTL(0.923)>HTR(0.899)>WYS(0.823);(2)the positive trend decay time of vegetation exceeded that of negative trend,indicating vegetation gradual recovery of the three national parks since 2012;(3)the VR of HTR was primarily influenced by elevation,aspect,average annual temperature change(AATC),and average annual precipitation change(AAPC);the WYS'VR was mainly affected by elevation,average annual precipitation(AAP),and AAPC;while the terrain factors(elevation and slope)were the main driving factors of VR in NTL;(4)among the main factors influencing the VR changes,the AAPC had the highest proportion in HTR(66.7%),and the AAP occupied the largest area proportion in WYS(80.4%).While in NTL,elevation served as the main driving factor for the VR,encompassing 64.2%of its area.Consequently,our findings indicated that precipitation factors were the main driving force for the VR changes in HTR and WYS national parks,while elevation was the main factors that drove the VR in NTL.Our research has promoted a deeper understanding of the driving mechanism behind the VR.展开更多
COVID-19 posed challenges for global tourism management.Changes in visitor temporal and spatial patterns and their associated determinants pre-and peri-pandemic in Canadian Rocky Mountain National Parks are analyzed.D...COVID-19 posed challenges for global tourism management.Changes in visitor temporal and spatial patterns and their associated determinants pre-and peri-pandemic in Canadian Rocky Mountain National Parks are analyzed.Data was collected through social media programming and analyzed using spatiotemporal analysis and a geographically weighted regression(GWR)model.Results highlight that COVID-19 significantly changed park visitation patterns.Visitors tended to explore more remote areas peri-pandemic.The GWR model also indicated distance to nearby trails was a significant influence on visitor density.Our results indicate that the pandemic influenced tourism temporal and spatial imbalance.This research presents a novel approach using combined social media big data which can be extended to the field of tourism management,and has important implications to manage visitor patterns and to allocate resources efficiently to satisfy multiple objectives of park management.展开更多
Zero-carbon parks have broad prospects in carbon neutralization.As an energy hub,hydrogen energy storage plays an important role in zero-carbon parks.However,the nonlinear characteristics of hydrogen energy storage sy...Zero-carbon parks have broad prospects in carbon neutralization.As an energy hub,hydrogen energy storage plays an important role in zero-carbon parks.However,the nonlinear characteristics of hydrogen energy storage systems(HESSs)have a significant impact on the system economy.Therefore,considering the variable working condition characteristics of HESSs,a hybrid operation method is proposed for HESS,to support the efficient and economic operation of zero-carbon parks,By analyzing the operating principle of a zero-carbon park with HESS,the system structure framework and variable condition linearization model of the equipment in HESS are established.Moreover,considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions,a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells,effectively meeting the thermoelectric load demand of zero-carbon parks in different scenarios.Finally,the economy of the proposed hybrid operation strategy was verified in typical scenarios,using a zero-carbon park embedded with a HESS.展开更多
Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking acc...Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.展开更多
The recent proliferation of Fifth-Generation(5G)networks and Sixth-Generation(6G)networks has given rise to Vehicular Crowd Sensing(VCS)systems which solve parking collisions by effectively incentivizing vehicle parti...The recent proliferation of Fifth-Generation(5G)networks and Sixth-Generation(6G)networks has given rise to Vehicular Crowd Sensing(VCS)systems which solve parking collisions by effectively incentivizing vehicle participation.However,instead of being an isolated module,the incentive mechanism usually interacts with other modules.Based on this,we capture this synergy and propose a Collision-free Parking Recommendation(CPR),a novel VCS system framework that integrates an incentive mechanism,a non-cooperative VCS game,and a multi-agent reinforcement learning algorithm,to derive an optimal parking strategy in real time.Specifically,we utilize an LSTM method to predict parking areas roughly for recommendations accurately.Its incentive mechanism is designed to motivate vehicle participation by considering dynamically priced parking tasks and social network effects.In order to cope with stochastic parking collisions,its non-cooperative VCS game further analyzes the uncertain interactions between vehicles in parking decision-making.Then its multi-agent reinforcement learning algorithm models the VCS campaign as a multi-agent Markov decision process that not only derives the optimal collision-free parking strategy for each vehicle independently,but also proves that the optimal parking strategy for each vehicle is Pareto-optimal.Finally,numerical results demonstrate that CPR can accomplish parking tasks at a 99.7%accuracy compared with other baselines,efficiently recommending parking spaces.展开更多
As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who vi...As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who visit them.Recently,social media big data has provided new data sources for sentiment analysis.However,there was limited researches that explored the connection between urban parks and individual’s sentiments.Therefore,this study firstly employed a pre-trained language model(BERT,Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media data.Secondly,this study analysed the relationship between urban parks and individual’s sentiment from both spatial and temporal perspectives.Finally,by utilizing structural equation model(SEM),we identified 13 factors and analyzed its degree of the influence.The research findings are listed as below:①It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks;②The urban park type showed an influence on sentiment scores.In this study,higher sentiment scores observed in Eco-parks,comprehensive parks,and historical parks;③The urban parks level showed low impact on sentiment scores.With distinctions observed mainly at level-3 and level-4;④Compared to internal factors in parks,the external infrastructure surround them exerted more significant impact on sentiment scores.For instance,number of bus and subway stations around urban parks led to higher sentiment scores,while scenic spots and restaurants had inverse result.This study provided a novel method to quantify the services of various urban parks,which can be served as inspiration for similar studies in other cities and countries,enhancing their park planning and management strategies.展开更多
文摘Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum.The precise reasons behind the specific degeneration of these dopamine neurons remain largely elusive.Genetic investigations have identified over 20 causative PARK genes and 90 genomic risk loci associated with both familial and sporadic Parkinson's disease.Notably,several of these genes are linked to the synaptic vesicle recycling process,particularly the clathrinmediated endocytosis pathway.This suggests that impaired synaptic vesicle recycling might represent an early feature of Parkinson's disease,followed by axonal degeneration and the eventual loss of dopamine cell bodies in the midbrain via a"dying back"mechanism.Recently,several new animal and cellular models with Parkinson's disease-linked mutations affecting the endocytic pathway have been created and extensively characterized.These models faithfully recapitulate certain Parkinson's disease-like features at the animal,circuit,and cellular levels,and exhibit defects in synaptic membrane trafficking,further supporting the findings from human genetics and clinical studies.In this review,we will first summarize the cellular and molecular findings from the models of two Parkinson's disease-linked clathrin uncoating proteins:auxilin(DNAJC6/PARK19)and synaptojanin 1(SYNJ1/PARK20).The mouse models carrying these two PARK gene mutations phenocopy each other with specific dopamine terminal pathology and display a potent synergistic effect.Subsequently,we will delve into the involvement of several clathrin-mediated endocytosis-related proteins(GAK,endophilin A1,SAC2/INPP5 F,synaptotagmin-11),identified as Parkinson's disease risk factors through genome-wide association studies,in Parkinson's disease pathogenesis.We will also explore the direct or indirect roles of some common Parkinson's disease-linked proteins(alpha-synuclein(PARK1/4),Parkin(PARK2),and LRRK2(PARK8))in synaptic endocytic trafficking.Additionally,we will discuss the emerging novel functions of these endocytic proteins in downstream membrane traffic pathways,particularly autophagy.Given that synaptic dysfunction is considered as an early event in Parkinson's disease,a deeper understanding of the cellular mechanisms underlying synaptic vesicle endocytic trafficking may unveil novel to rgets for early diagnosis and the development of interventional therapies for Parkinson's disease.Future research should aim to elucidate why generalized synaptic endocytic dysfunction leads to the selective degeneration of nigrostriatal dopamine neurons in Parkinson's disease.
基金supported by National Natural Science Foundation of China(52222215, 52272420, 52072051)。
文摘Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.
文摘在规模化养殖模式下,畜禽在生长过程中会不可避免地面对各种不利因素,导致体内产生氧化应激,严重影响其生长发育。畜禽体内存在多种抗氧化因子来应对氧化应激。其中,帕金森相关蛋白7(Parkinson’s Disease-Associated Protein 7,PARK7)基因是细胞氧化应激中重要的调控因子之一。PARK7通过自身半胱氨酸的氧化水平感受氧化应激信号,并通过Nrf2、ERK1/2和PI3K/Akt等途径促进抗氧化酶的生成,提高细胞的抗氧化能力,从而减轻氧化应激引起的损伤。本文对PARK7基因在氧化应激中的调控作用和通路进行综述,将有助于畜禽氧化应激的调节机制研究。
基金Under the auspices of the National Social Science Found of China(No.21XGL019)Hainan Provincial Natural Science Foundation of China(No.421RC1034)Professor/Doctor Research Foundation of Huizhou University(No.2022JB080)。
文摘Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.
基金the National Natural Science Foundation of China(grant no.31971639)the Natural Science Foundation of Fujian Province(grant no.2023J01477)the Special Investigation on Science and Technology Infrastructure Resources(grant no.2019FY202108)for their support of this research。
文摘Vegetation resilience(VR),providing an objective measure of ecosystem health,has received considerable attention,however,there is still limited understanding of whether the dominant factors differ across different climate zones.We took the three national parks(Hainan Tropical Rainforest National Park,HTR;Wuyishan National Park,WYS;and Northeast Tiger and Leopard National Park,NTL)of China with less human interference as cases,which are distributed in different climatic zones,including tropical,subtropical and temperate monsoon climates,respectively.Then,we employed the probabilistic decay method to explore the spatio-temporal changes in the VR and their natural driving patterns using Geographically Weighted Regression(GWR)model as well.The results revealed that:(1)from 2000 to 2020,the Normalized Difference Vegetation Index(NDVI)of the three national parks fluctuated between 0.800 and 0.960,exhibiting an overall upward trend,with the mean NDVI of NTL(0.923)>HTR(0.899)>WYS(0.823);(2)the positive trend decay time of vegetation exceeded that of negative trend,indicating vegetation gradual recovery of the three national parks since 2012;(3)the VR of HTR was primarily influenced by elevation,aspect,average annual temperature change(AATC),and average annual precipitation change(AAPC);the WYS'VR was mainly affected by elevation,average annual precipitation(AAP),and AAPC;while the terrain factors(elevation and slope)were the main driving factors of VR in NTL;(4)among the main factors influencing the VR changes,the AAPC had the highest proportion in HTR(66.7%),and the AAP occupied the largest area proportion in WYS(80.4%).While in NTL,elevation served as the main driving factor for the VR,encompassing 64.2%of its area.Consequently,our findings indicated that precipitation factors were the main driving force for the VR changes in HTR and WYS national parks,while elevation was the main factors that drove the VR in NTL.Our research has promoted a deeper understanding of the driving mechanism behind the VR.
基金This research was supported by the UBC APFNet Grant(Project ID:2022sp2 CAN).
文摘COVID-19 posed challenges for global tourism management.Changes in visitor temporal and spatial patterns and their associated determinants pre-and peri-pandemic in Canadian Rocky Mountain National Parks are analyzed.Data was collected through social media programming and analyzed using spatiotemporal analysis and a geographically weighted regression(GWR)model.Results highlight that COVID-19 significantly changed park visitation patterns.Visitors tended to explore more remote areas peri-pandemic.The GWR model also indicated distance to nearby trails was a significant influence on visitor density.Our results indicate that the pandemic influenced tourism temporal and spatial imbalance.This research presents a novel approach using combined social media big data which can be extended to the field of tourism management,and has important implications to manage visitor patterns and to allocate resources efficiently to satisfy multiple objectives of park management.
基金supported by Natural Science Foundation of China(no.72471087)Natural Science Foundation of Beijing Municipality(no.9242015).
文摘Zero-carbon parks have broad prospects in carbon neutralization.As an energy hub,hydrogen energy storage plays an important role in zero-carbon parks.However,the nonlinear characteristics of hydrogen energy storage systems(HESSs)have a significant impact on the system economy.Therefore,considering the variable working condition characteristics of HESSs,a hybrid operation method is proposed for HESS,to support the efficient and economic operation of zero-carbon parks,By analyzing the operating principle of a zero-carbon park with HESS,the system structure framework and variable condition linearization model of the equipment in HESS are established.Moreover,considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions,a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells,effectively meeting the thermoelectric load demand of zero-carbon parks in different scenarios.Finally,the economy of the proposed hybrid operation strategy was verified in typical scenarios,using a zero-carbon park embedded with a HESS.
基金Supported by National Key R&D Program of China (Grant No.2021YFB2501800)National Natural Science Foundation of China (Grant No.52172384)+1 种基金Science and Technology Innovation Program of Hunan Province of China (Grant No.2021RC3048)State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle of China (Grant No.72275004)。
文摘Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.
基金supported in part by the Natural Science Foundation of Shandong Province of China(ZR202103040180)the Major Scientific and Technological Projects of CNPC under Grant ZD2019-183-004the Fundamental Research Funds for the Central Universities under Grant 20CX05019A.
文摘The recent proliferation of Fifth-Generation(5G)networks and Sixth-Generation(6G)networks has given rise to Vehicular Crowd Sensing(VCS)systems which solve parking collisions by effectively incentivizing vehicle participation.However,instead of being an isolated module,the incentive mechanism usually interacts with other modules.Based on this,we capture this synergy and propose a Collision-free Parking Recommendation(CPR),a novel VCS system framework that integrates an incentive mechanism,a non-cooperative VCS game,and a multi-agent reinforcement learning algorithm,to derive an optimal parking strategy in real time.Specifically,we utilize an LSTM method to predict parking areas roughly for recommendations accurately.Its incentive mechanism is designed to motivate vehicle participation by considering dynamically priced parking tasks and social network effects.In order to cope with stochastic parking collisions,its non-cooperative VCS game further analyzes the uncertain interactions between vehicles in parking decision-making.Then its multi-agent reinforcement learning algorithm models the VCS campaign as a multi-agent Markov decision process that not only derives the optimal collision-free parking strategy for each vehicle independently,but also proves that the optimal parking strategy for each vehicle is Pareto-optimal.Finally,numerical results demonstrate that CPR can accomplish parking tasks at a 99.7%accuracy compared with other baselines,efficiently recommending parking spaces.
基金R&D Program of Beijing Municipal Education Commission(No.KM202211417015)Academic Research Projects of Beijing Union University(No.ZK10202209)+1 种基金The team-building subsidy of“Xuezhi Professorship”of the College of Applied Arts and Science of Beijing Union University(No.BUUCAS-XZJSTD-2024005)Academic Research Projects of Beijing Union University(No.ZKZD202305).
文摘As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who visit them.Recently,social media big data has provided new data sources for sentiment analysis.However,there was limited researches that explored the connection between urban parks and individual’s sentiments.Therefore,this study firstly employed a pre-trained language model(BERT,Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media data.Secondly,this study analysed the relationship between urban parks and individual’s sentiment from both spatial and temporal perspectives.Finally,by utilizing structural equation model(SEM),we identified 13 factors and analyzed its degree of the influence.The research findings are listed as below:①It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks;②The urban park type showed an influence on sentiment scores.In this study,higher sentiment scores observed in Eco-parks,comprehensive parks,and historical parks;③The urban parks level showed low impact on sentiment scores.With distinctions observed mainly at level-3 and level-4;④Compared to internal factors in parks,the external infrastructure surround them exerted more significant impact on sentiment scores.For instance,number of bus and subway stations around urban parks led to higher sentiment scores,while scenic spots and restaurants had inverse result.This study provided a novel method to quantify the services of various urban parks,which can be served as inspiration for similar studies in other cities and countries,enhancing their park planning and management strategies.
