Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional ...Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.展开更多
With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.T...With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.The pedestrian naviga-tion based on radio is subject to environmental occlusion lead-ing to the degradation of positioning accuracy.The pedestrian navigation based on micro-electro-mechanical system inertial measurement unit(MIMU)is less susceptible to environmental interference,but its errors dissipate over time.In this paper,a chest card pedestrian navigation improvement method based on complementary correction is proposed in order to suppress the error divergence of inertial navigation methods.To suppress atti-tude errors,optimal feedback coefficients are established by pedestrian motion characteristics.To extend navigation time and improve positioning accuracy,the step length in subsequent movements is compensated by the first step length.The experi-mental results show that the positioning accuracy of the pro-posed method is improved by more than 47%and 44%com-pared with the pure inertia-based method combined with step compensation and the traditional complementary filtering com-bined method with step compensation.The proposed method can effectively suppress the error dispersion and improve the positioning accuracy.展开更多
Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns.Understanding the differential influences of road physical design attributes on crash frequencies for these two gr...Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns.Understanding the differential influences of road physical design attributes on crash frequencies for these two groups is critical for developing targeted safety interventions.Considering that the zero-truncated characteristic of the data is uncertain,the results of the zero-truncated negative binomial models and traditional negative binomial models are calculated to seek the better model.The result revealed that the road surface conditions and vertical and horizontal curvature have greater influence on both pedestrian and driver compared to number of lanes and speed limit.And speed limits were more pronounced for pedestrian crash frequency than driver group.Conversely,the effect of different types of intersections was stronger for driver crash frequency.The differential influences of road physical design attributes on traffic crash frequencies for pedestrians versus drivers highlight the importance of adopting a user-centric approach to transportation safety planning and infrastructure design.Tailoring interventions to address the unique needs and vulnerabilities of different road user groups can lead to more effective safety improvements and better overall traffic safety outcomes.展开更多
The roundabouts are widely used in China,some of which have central islands as scenic spots.The crosswalks connecting to the central islands,normally full of pedestrians,have negative impact on roundabout capability a...The roundabouts are widely used in China,some of which have central islands as scenic spots.The crosswalks connecting to the central islands,normally full of pedestrians,have negative impact on roundabout capability and pedestrian safety.Therefore,this study proposes a fuzzy cellular automata(FCA)model to explore the safety and efficiency impacts of pedestrian-vehicle conflicts at a two-lane roundabout.To reason the decision-making process of individual drivers before crosswalks,membership functions in the fuzzy inference system were calibrated with field data conducted in Changsha,China.Using specific indicators of efficiency and safety performance,it was shown that circulating vehicles can move smoothly in low traffic flow,but the roundabout system is prone to the traffic congestion if traffic flow reaches to a certain level.Also,the high yielding rate of drivers has a negative impact on the traffic efficiency but can improve pedestrian safety.Furthermore,a pedestrian restriction measure was deduced for the roundabout crosswalk from the FCA model and national guideline of setting traffic lights.展开更多
Focusing on data imbalance and intraclass variation,an improved pedestrian detection with a cascade of complex peer AdaBoost classifiers is proposed.The series of the AdaBoost classifiers are learned greedily,along wi...Focusing on data imbalance and intraclass variation,an improved pedestrian detection with a cascade of complex peer AdaBoost classifiers is proposed.The series of the AdaBoost classifiers are learned greedily,along with negative example mining.The complexity of classifiers in the cascade is not limited,so more negative examples are used for training.Furthermore,the cascade becomes an ensemble of strong peer classifiers,which treats intraclass variation.To locally train the AdaBoost classifiers with a high detection rate,a refining strategy is used to discard the hardest negative training examples rather than decreasing their thresholds.Using the aggregate channel feature(ACF),the method achieves miss rates of 35%and 14%on the Caltech pedestrian benchmark and Inria pedestrian dataset,respectively,which are lower than that of increasingly complex AdaBoost classifiers,i.e.,44%and 17%,respectively.Using deep features extracted by the region proposal network(RPN),the method achieves a miss rate of 10.06%on the Caltech pedestrian benchmark,which is also lower than 10.53%from the increasingly complex cascade.This study shows that the proposed method can use more negative examples to train the pedestrian detector.It outperforms the existing cascade of increasingly complex classifiers.展开更多
The route optimization problem for road networks was applied to pedestrian flow.Evacuation path networks with nodes and arcs considering the traffic capacities of facilities were built in metro hubs,and a path impedan...The route optimization problem for road networks was applied to pedestrian flow.Evacuation path networks with nodes and arcs considering the traffic capacities of facilities were built in metro hubs,and a path impedance function for metro hubs which used the relationships among circulation speed,density and flow rate for pedestrians was defined.Then,a route optimization model which minimizes the movement time of the last evacuee was constructed to optimize evacuation performance.Solutions to the proposed mathematical model were obtained through an iterative optimization process.The route optimization model was applied to Xidan Station of Beijing Metro Line 4 based on the actual situations,and the calculation results of the model were tested using buildingExodus microscopic evacuation simulation software.The simulation result shows that the proposed model shortens the evacuation time by 16.05%,3.15% and 2.78% compared with all or none method,equally split method and Logit model,respectively.Furthermore,when the population gets larger,evacuation efficiency in the proposed model has a greater advantage.展开更多
Pedestrian's road-crossing model is the key part of micro-simulation for mixed traffic at signalized intersection.To reproduce the crossing behavior of pedestrians,the microscopic behaviors of the pedestrians pass...Pedestrian's road-crossing model is the key part of micro-simulation for mixed traffic at signalized intersection.To reproduce the crossing behavior of pedestrians,the microscopic behaviors of the pedestrians passing through the crosswalk at signalized intersection were analyzed.A pedestrian's decision making model based on gap acceptance theory was proposed.Based on the field data at three typical intersections in Beijing,China,the critical gaps and lags of pedestrians were calibrated.In addition,considering pedestrian's required space,a modification of the social force model that consists of a self-deceleration mechanism prevents a simulated pedestrian from continuously pushing over other pedestrians,making the simulation more realistic.After the simple change,the modified social force model is able to reproduce the fundamental diagram of pedestrian flows for densities less than 3.5 m-2 as reported in the literature.展开更多
A good understanding of pedestrian movement in the transfer corridor is vital for the planning and design of the station,especially for efficiency and safety.A multi-force vector grid model was presented to simulate t...A good understanding of pedestrian movement in the transfer corridor is vital for the planning and design of the station,especially for efficiency and safety.A multi-force vector grid model was presented to simulate the movement of bidirectional pedestrian flow based on cellular automata and forces between pedestrians.The model improves rule-based characteristics of cellular automata,details forces between pedestrians and solves pedestrian collisions by a several-step updating method to simulate pedestrian movements.Two general scenarios in corridor were simulated.One is bidirectional pedestrian flow simulation with isolation facility,and the other is bidirectional pedestrian flow simulation without isolation facility,where there exists disturbance in the middle.Through simulation,some facts can be seen that pedestrians in the case with isolation facility have the largest speed and pedestrians in the case without isolation facility have the smallest speed; pedestrians in the case of unidirectional flow have the largest volume and pedestrians in the case of without isolation facility have the smallest volume.展开更多
This work aims at finding pedestrian walking characteristics at U-type stairs according to the width change of stairs and appropriate spot for installing piezoelectric energy harvesting.The number of pedestrian at two...This work aims at finding pedestrian walking characteristics at U-type stairs according to the width change of stairs and appropriate spot for installing piezoelectric energy harvesting.The number of pedestrian at two kinds of stairs(one is stairs with 1.5 m in width and the other is stairs with 3 m in width) was estimated by calculating the number of steps on the stairs by a zone which is divided into 30 cm×30 cm.The result shows high density in the middle in the case of narrow stairs but traffic is concentrated on stair inside(pillar side) in stairs with large width.In conclusion,the location for installation of piezoelectric energy harvesting system should be considered differently on stairs width and the number of installation depends on total expected traffic and the expected traffic for a device.展开更多
A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow ...A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.展开更多
基金supported by the National Natural Science Foundation of China under(Grant No.52175531)in part by the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant(Grant Nos.KJQN202000605 and KJZD-M202000602)。
文摘Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.
文摘With the development of positioning technology,loca-tion services are constantly in demand by people.As a primary location service pedestrian navigation has two main approaches based on radio and inertial navigation.The pedestrian naviga-tion based on radio is subject to environmental occlusion lead-ing to the degradation of positioning accuracy.The pedestrian navigation based on micro-electro-mechanical system inertial measurement unit(MIMU)is less susceptible to environmental interference,but its errors dissipate over time.In this paper,a chest card pedestrian navigation improvement method based on complementary correction is proposed in order to suppress the error divergence of inertial navigation methods.To suppress atti-tude errors,optimal feedback coefficients are established by pedestrian motion characteristics.To extend navigation time and improve positioning accuracy,the step length in subsequent movements is compensated by the first step length.The experi-mental results show that the positioning accuracy of the pro-posed method is improved by more than 47%and 44%com-pared with the pure inertia-based method combined with step compensation and the traditional complementary filtering com-bined method with step compensation.The proposed method can effectively suppress the error dispersion and improve the positioning accuracy.
基金Projects(52102407,52472354)supported by the National Natural Science Foundation of China。
文摘Traffic accidents involving pedestrians and drivers pose significant public health and safety concerns.Understanding the differential influences of road physical design attributes on crash frequencies for these two groups is critical for developing targeted safety interventions.Considering that the zero-truncated characteristic of the data is uncertain,the results of the zero-truncated negative binomial models and traditional negative binomial models are calculated to seek the better model.The result revealed that the road surface conditions and vertical and horizontal curvature have greater influence on both pedestrian and driver compared to number of lanes and speed limit.And speed limits were more pronounced for pedestrian crash frequency than driver group.Conversely,the effect of different types of intersections was stronger for driver crash frequency.The differential influences of road physical design attributes on traffic crash frequencies for pedestrians versus drivers highlight the importance of adopting a user-centric approach to transportation safety planning and infrastructure design.Tailoring interventions to address the unique needs and vulnerabilities of different road user groups can lead to more effective safety improvements and better overall traffic safety outcomes.
基金Project(2020YFB1600400)supported by the National Key Research and Development Program of ChinaProject(2019JJ50837)supported by the Natural Science Foundation of Hunan Province,ChinaProject(71801227)supported by the National Natural Science Foundation of China。
文摘The roundabouts are widely used in China,some of which have central islands as scenic spots.The crosswalks connecting to the central islands,normally full of pedestrians,have negative impact on roundabout capability and pedestrian safety.Therefore,this study proposes a fuzzy cellular automata(FCA)model to explore the safety and efficiency impacts of pedestrian-vehicle conflicts at a two-lane roundabout.To reason the decision-making process of individual drivers before crosswalks,membership functions in the fuzzy inference system were calibrated with field data conducted in Changsha,China.Using specific indicators of efficiency and safety performance,it was shown that circulating vehicles can move smoothly in low traffic flow,but the roundabout system is prone to the traffic congestion if traffic flow reaches to a certain level.Also,the high yielding rate of drivers has a negative impact on the traffic efficiency but can improve pedestrian safety.Furthermore,a pedestrian restriction measure was deduced for the roundabout crosswalk from the FCA model and national guideline of setting traffic lights.
基金Project(2018AAA0102102)supported by the National Science and Technology Major Project,ChinaProject(2017WK2074)supported by the Planned Science and Technology Project of Hunan Province,China+1 种基金Project(B18059)supported by the National 111 Project,ChinaProject(61702559)supported by the National Natural Science Foundation of China。
文摘Focusing on data imbalance and intraclass variation,an improved pedestrian detection with a cascade of complex peer AdaBoost classifiers is proposed.The series of the AdaBoost classifiers are learned greedily,along with negative example mining.The complexity of classifiers in the cascade is not limited,so more negative examples are used for training.Furthermore,the cascade becomes an ensemble of strong peer classifiers,which treats intraclass variation.To locally train the AdaBoost classifiers with a high detection rate,a refining strategy is used to discard the hardest negative training examples rather than decreasing their thresholds.Using the aggregate channel feature(ACF),the method achieves miss rates of 35%and 14%on the Caltech pedestrian benchmark and Inria pedestrian dataset,respectively,which are lower than that of increasingly complex AdaBoost classifiers,i.e.,44%and 17%,respectively.Using deep features extracted by the region proposal network(RPN),the method achieves a miss rate of 10.06%on the Caltech pedestrian benchmark,which is also lower than 10.53%from the increasingly complex cascade.This study shows that the proposed method can use more negative examples to train the pedestrian detector.It outperforms the existing cascade of increasingly complex classifiers.
基金Project(51078086)supported by the National Natural Science Foundation of China
文摘The route optimization problem for road networks was applied to pedestrian flow.Evacuation path networks with nodes and arcs considering the traffic capacities of facilities were built in metro hubs,and a path impedance function for metro hubs which used the relationships among circulation speed,density and flow rate for pedestrians was defined.Then,a route optimization model which minimizes the movement time of the last evacuee was constructed to optimize evacuation performance.Solutions to the proposed mathematical model were obtained through an iterative optimization process.The route optimization model was applied to Xidan Station of Beijing Metro Line 4 based on the actual situations,and the calculation results of the model were tested using buildingExodus microscopic evacuation simulation software.The simulation result shows that the proposed model shortens the evacuation time by 16.05%,3.15% and 2.78% compared with all or none method,equally split method and Logit model,respectively.Furthermore,when the population gets larger,evacuation efficiency in the proposed model has a greater advantage.
基金Project(70972041)supported by the National Natural Science Foundation of ChinaProject(20100009110010)supported by the PhD Programs Foundation of Ministry of Education of ChinaProject(2011YJS246)supported by Fundamental Research Funds for the Central Universities of China
文摘Pedestrian's road-crossing model is the key part of micro-simulation for mixed traffic at signalized intersection.To reproduce the crossing behavior of pedestrians,the microscopic behaviors of the pedestrians passing through the crosswalk at signalized intersection were analyzed.A pedestrian's decision making model based on gap acceptance theory was proposed.Based on the field data at three typical intersections in Beijing,China,the critical gaps and lags of pedestrians were calibrated.In addition,considering pedestrian's required space,a modification of the social force model that consists of a self-deceleration mechanism prevents a simulated pedestrian from continuously pushing over other pedestrians,making the simulation more realistic.After the simple change,the modified social force model is able to reproduce the fundamental diagram of pedestrian flows for densities less than 3.5 m-2 as reported in the literature.
基金Project(51238008)supported by the National Natural Science Foundation of ChinaProject(CXZZ13_0116)supported by the Fundamental Research Funds for the Central Universities of ChinaProject(YBJJ1344)supported by the Scientific Research Foundations of Graduate School of Southeast University,China
文摘A good understanding of pedestrian movement in the transfer corridor is vital for the planning and design of the station,especially for efficiency and safety.A multi-force vector grid model was presented to simulate the movement of bidirectional pedestrian flow based on cellular automata and forces between pedestrians.The model improves rule-based characteristics of cellular automata,details forces between pedestrians and solves pedestrian collisions by a several-step updating method to simulate pedestrian movements.Two general scenarios in corridor were simulated.One is bidirectional pedestrian flow simulation with isolation facility,and the other is bidirectional pedestrian flow simulation without isolation facility,where there exists disturbance in the middle.Through simulation,some facts can be seen that pedestrians in the case with isolation facility have the largest speed and pedestrians in the case without isolation facility have the smallest speed; pedestrians in the case of unidirectional flow have the largest volume and pedestrians in the case of without isolation facility have the smallest volume.
基金Project(NRF-2011-0000868)supported by the National Research Foundation of Korea(NRF)funded by the Korea government(MEST)Project(2011-0003968)supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)
文摘This work aims at finding pedestrian walking characteristics at U-type stairs according to the width change of stairs and appropriate spot for installing piezoelectric energy harvesting.The number of pedestrian at two kinds of stairs(one is stairs with 1.5 m in width and the other is stairs with 3 m in width) was estimated by calculating the number of steps on the stairs by a zone which is divided into 30 cm×30 cm.The result shows high density in the middle in the case of narrow stairs but traffic is concentrated on stair inside(pillar side) in stairs with large width.In conclusion,the location for installation of piezoelectric energy harvesting system should be considered differently on stairs width and the number of installation depends on total expected traffic and the expected traffic for a device.
基金Project(50778015)supported by the National Natural Science Foundation of ChinaProject(2012CB725403)supported by the Major State Basic Research Development Program of China
文摘A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.
