In order to increase the accuracy of microscopic traffic flow simulation,two acceleration models are presented to simulate car-following behaviors of the lane-changing vehicle and following putative vehicle during the...In order to increase the accuracy of microscopic traffic flow simulation,two acceleration models are presented to simulate car-following behaviors of the lane-changing vehicle and following putative vehicle during the discretionary lanechanging preparation( DLCP) process, respectively. The proposed acceleration models can reflect vehicle interaction characteristics. Samples used for describing the starting point and the ending point of DLCP are extracted from a real NGSIM vehicle trajectory data set. The acceleration model for a lanechanging vehicle is supposed to be a linear acceleration model.The acceleration model for the following putative vehicle is constructed by referring to the optimal velocity model,in which optimal velocity is defined as a linear function of the velocity of putative leading vehicle. Similar calibration,a hypothesis test and parameter sensitivity analysis were conducted on the acceleration model of the lane-changing vehicle and following putative vehicle,respectively. The validation results of the two proposed models suggest that the training and testing errors are acceptable compared with similar works on calibrations for car following models. The parameter sensitivity analysis shows that the subtle observed error does not lead to severe variations of car-following behaviors of the lane-changing vehicle and following putative vehicle.展开更多
The realization of personalized lane-changing(LC)for intelligent vehicles(IVs)is important for enhancing the social acknowledgment,user acceptance,adaptability,and trust of IVs.The LC style classification of human dri...The realization of personalized lane-changing(LC)for intelligent vehicles(IVs)is important for enhancing the social acknowledgment,user acceptance,adaptability,and trust of IVs.The LC style classification of human drivers represents a crucial foundation for achieving personalized LC.Therefore,this study constructs an LC style classification method based on driving behavioral primitives,which enables the classified LC styles to fully embody the implicit behavioral semantics and patterns of human drivers.First,a disentangled sticky hierarchical Dirichlet process hidden Markov model is proposed for the LC behavioral segment segmentation.The model can suppress frequent transitions of the hidden states,and vector autoregression is used to accurately describe the LC explicit behavioral parameters.Subsequently,the K-shape is employed to cluster all LC behavior segments to obtain interpretable and reasonable LC behavior primitives.Then,clustering features based on the LC behavioral primitives are constructed.Finally,LC styles are classified using density peak clustering,which does not require a manual specification of the number of clustering centers.Verification is performed on the Next Generation Simulation dataset,and the results indicate that this method can accurately and reasonably classify LC styles.The quantitative comparison with four state-of-the-art methods further demonstrates the advantages of the proposed method in LC style classification and confirms the effectiveness of introducing LC behavioral primitives.展开更多
The paper proposes a model of mandatory lane-changing behaviour based on a non-cooperative game in a traditional environment and analyses its applicability in a connected environment.In order to solve the problem of t...The paper proposes a model of mandatory lane-changing behaviour based on a non-cooperative game in a traditional environment and analyses its applicability in a connected environment.In order to solve the problem of traffic safety and traffic congestion caused by mandatory lane-changing on urban roads,this paper applies the non-cooperative game theory to describe the game behaviour of the two parties,the lane-changing vehicle and the vehicle behind the target lane,in the connected and traditional environments respectively,and constructs the model considering the safety gain,speed gain and lane-changing gain to obtain a game model and the Nash equilibrium solution.Themodel is calibrated and tested using NGSIM data,and the results of the study show that themodel has a good performance for the decision behaviour of lane-changing vehicles and lag vehicles for mandatory lane-changing behaviour on urban roads.展开更多
By considering mandatory lane-changing as a collision avoidance measure,this paper presented the corresponding lane-change decision making and trajectory planning algorithm under an emergency scenario.Different from t...By considering mandatory lane-changing as a collision avoidance measure,this paper presented the corresponding lane-change decision making and trajectory planning algorithm under an emergency scenario.Different from the traditional algorithm in which lane-change decision making and trajectory planning are separated,they are here coupled in a proposed algorithm and the related parameters are dynamically adjusted in the whole process.In addition to lane-change collision avoidance feasibility analysis,lanechange time instance and duration time are obtained by solving the constrained convex quadratic optimization programme.By taking lane-change time instance and duration time as inputs,the algorithm then proceeded to propose a kinematic model-based highorder polynomial lane change trajectory.By giving the simulation result compassion with the related algorithm,it is proved that the proposed algorithm has a good robustness and high efficiency.展开更多
Lane-changing is performed either to follow the route to a planned destination(i.e.,mandatory lane-changing)or to achieve better driving conditions(i.e.,discretionary lane-changing).A connected environment is expected...Lane-changing is performed either to follow the route to a planned destination(i.e.,mandatory lane-changing)or to achieve better driving conditions(i.e.,discretionary lane-changing).A connected environment is expected to assist during lane-changing manoeuvres,but it is not known well how driving aids in a connected environment assist lane-changing execution.As such,this study investigates the impact of a connected environment on lanechanging execution time during mandatory and discretionary lane-changing manoeuvres.To this end,this study designed an advanced driving simulator experiment where 78 drivers performed these manoeuvres on a simulated motorway in three randomised driving conditions.The conditions were baseline(without driving aids),a fully functioning connected environment with a perfect supply of driving aids,and an impaired connected environment with delayed driving aids.The lane-changing execution time has been modelled by a random parameters hazard-based duration modelling approach,which accounts for the panel nature of data and captures the unobserved heterogeneity.Results suggest that,compared to the baseline condition(i.e.,a non-connected environment),most of the drivers in the connected environment take more time to complete their lane-changing manoeuvres,indicating drivers’safer lane-changing execution behaviour in the connected environment.The communication delay driving condition has been found to have more deteriorating effects on mandatory lanechanging manoeuvres than discretionary lane-changing manoeuvres.This study concludes that(i)the connected environment increases safety margin during both lane-changing manoeuvres,and(ii)a higher magnitude of safety margin is observed during mandatory lane-changing manoeuvres whereby drivers have a higher need for assistance.展开更多
基金The National Basic Research Program of China(No.2012CB725405)the National Natural Science Foundation of China(No.51308115)+1 种基金the Science and Technology Demonstration Project of Ministry of Transport of China(No.2015364X16030)Fundamental Research Funds for the Central Universities,the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYLX15_0153)
文摘In order to increase the accuracy of microscopic traffic flow simulation,two acceleration models are presented to simulate car-following behaviors of the lane-changing vehicle and following putative vehicle during the discretionary lanechanging preparation( DLCP) process, respectively. The proposed acceleration models can reflect vehicle interaction characteristics. Samples used for describing the starting point and the ending point of DLCP are extracted from a real NGSIM vehicle trajectory data set. The acceleration model for a lanechanging vehicle is supposed to be a linear acceleration model.The acceleration model for the following putative vehicle is constructed by referring to the optimal velocity model,in which optimal velocity is defined as a linear function of the velocity of putative leading vehicle. Similar calibration,a hypothesis test and parameter sensitivity analysis were conducted on the acceleration model of the lane-changing vehicle and following putative vehicle,respectively. The validation results of the two proposed models suggest that the training and testing errors are acceptable compared with similar works on calibrations for car following models. The parameter sensitivity analysis shows that the subtle observed error does not lead to severe variations of car-following behaviors of the lane-changing vehicle and following putative vehicle.
基金jointly supported by the National Natural Science Foundation of China(52172386,52302494)the China Postdoctoral Science Foundation under Grant Number 2023M741339.
文摘The realization of personalized lane-changing(LC)for intelligent vehicles(IVs)is important for enhancing the social acknowledgment,user acceptance,adaptability,and trust of IVs.The LC style classification of human drivers represents a crucial foundation for achieving personalized LC.Therefore,this study constructs an LC style classification method based on driving behavioral primitives,which enables the classified LC styles to fully embody the implicit behavioral semantics and patterns of human drivers.First,a disentangled sticky hierarchical Dirichlet process hidden Markov model is proposed for the LC behavioral segment segmentation.The model can suppress frequent transitions of the hidden states,and vector autoregression is used to accurately describe the LC explicit behavioral parameters.Subsequently,the K-shape is employed to cluster all LC behavior segments to obtain interpretable and reasonable LC behavior primitives.Then,clustering features based on the LC behavioral primitives are constructed.Finally,LC styles are classified using density peak clustering,which does not require a manual specification of the number of clustering centers.Verification is performed on the Next Generation Simulation dataset,and the results indicate that this method can accurately and reasonably classify LC styles.The quantitative comparison with four state-of-the-art methods further demonstrates the advantages of the proposed method in LC style classification and confirms the effectiveness of introducing LC behavioral primitives.
基金Natural science foundation of Heilongjiang Province of China(Grant No.LH2020G002)Jilin Province science and technology development project(Grant No.20210203214SF).
文摘The paper proposes a model of mandatory lane-changing behaviour based on a non-cooperative game in a traditional environment and analyses its applicability in a connected environment.In order to solve the problem of traffic safety and traffic congestion caused by mandatory lane-changing on urban roads,this paper applies the non-cooperative game theory to describe the game behaviour of the two parties,the lane-changing vehicle and the vehicle behind the target lane,in the connected and traditional environments respectively,and constructs the model considering the safety gain,speed gain and lane-changing gain to obtain a game model and the Nash equilibrium solution.Themodel is calibrated and tested using NGSIM data,and the results of the study show that themodel has a good performance for the decision behaviour of lane-changing vehicles and lag vehicles for mandatory lane-changing behaviour on urban roads.
文摘By considering mandatory lane-changing as a collision avoidance measure,this paper presented the corresponding lane-change decision making and trajectory planning algorithm under an emergency scenario.Different from the traditional algorithm in which lane-change decision making and trajectory planning are separated,they are here coupled in a proposed algorithm and the related parameters are dynamically adjusted in the whole process.In addition to lane-change collision avoidance feasibility analysis,lanechange time instance and duration time are obtained by solving the constrained convex quadratic optimization programme.By taking lane-change time instance and duration time as inputs,the algorithm then proceeded to propose a kinematic model-based highorder polynomial lane change trajectory.By giving the simulation result compassion with the related algorithm,it is proved that the proposed algorithm has a good robustness and high efficiency.
基金partly funded by the Australian Research Council grant DP210102970.
文摘Lane-changing is performed either to follow the route to a planned destination(i.e.,mandatory lane-changing)or to achieve better driving conditions(i.e.,discretionary lane-changing).A connected environment is expected to assist during lane-changing manoeuvres,but it is not known well how driving aids in a connected environment assist lane-changing execution.As such,this study investigates the impact of a connected environment on lanechanging execution time during mandatory and discretionary lane-changing manoeuvres.To this end,this study designed an advanced driving simulator experiment where 78 drivers performed these manoeuvres on a simulated motorway in three randomised driving conditions.The conditions were baseline(without driving aids),a fully functioning connected environment with a perfect supply of driving aids,and an impaired connected environment with delayed driving aids.The lane-changing execution time has been modelled by a random parameters hazard-based duration modelling approach,which accounts for the panel nature of data and captures the unobserved heterogeneity.Results suggest that,compared to the baseline condition(i.e.,a non-connected environment),most of the drivers in the connected environment take more time to complete their lane-changing manoeuvres,indicating drivers’safer lane-changing execution behaviour in the connected environment.The communication delay driving condition has been found to have more deteriorating effects on mandatory lanechanging manoeuvres than discretionary lane-changing manoeuvres.This study concludes that(i)the connected environment increases safety margin during both lane-changing manoeuvres,and(ii)a higher magnitude of safety margin is observed during mandatory lane-changing manoeuvres whereby drivers have a higher need for assistance.
