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Road crashes cause serious loss of life and property. Among all vehicles, buses are more likely to encounter crashes. In recent years, the advanced driving assistance system (ADAS) has been widely used in buses to improve safety. The warning system is one of the key functions and has proven effective in reducing crashes. However, drivers often ignore or overreact to ADAS warnings during naturalistic driving scenarios. Therefore, reactions of bus drivers to warnings need further investigation. In this study, bus drivers’ responses to lane departure warning (LDW) and forward collision warning (FCW) were investigated using 20-day naturalistic driving data. These reactions could be classified into three categories, namely positive, negative, and overreaction or emergency, by employing the Gaussian mixture model. The authors constructed a framework to quantify drivers’ reactions to the warning and study the reaction characteristics in different environments. The results indicate that drivers’ reactions to FCW were more positive than to LDW, drivers reacted more positively to LDW and FCW while driving on highways than on urban roads, and drivers reacted more positively at night to LDW and FCW than during daytime. This study gives support to an adaptive ADAS considering varying bus driver characteristics and environments.
Wei Ye; Yueru Xu; Feixiang Zhou; Xiaomeng Shi; Zhirui Ye. Investigation of Bus Drivers’ Reaction to ADAS Warning System: Application of the Gaussian Mixed Model. Sustainability 2021, 13, 8759 .
AMA StyleWei Ye, Yueru Xu, Feixiang Zhou, Xiaomeng Shi, Zhirui Ye. Investigation of Bus Drivers’ Reaction to ADAS Warning System: Application of the Gaussian Mixed Model. Sustainability. 2021; 13 (16):8759.
Chicago/Turabian StyleWei Ye; Yueru Xu; Feixiang Zhou; Xiaomeng Shi; Zhirui Ye. 2021. "Investigation of Bus Drivers’ Reaction to ADAS Warning System: Application of the Gaussian Mixed Model." Sustainability 13, no. 16: 8759.
Traffic crashes are geographical events, and their spatial patterns are strongly linked to the regional characteristics of road network, sociodemography, and human activities. Different human activities may have different impacts on traffic exposures, traffic conflicts and speeds in different transportation geographic areas, and accordingly generate different traffic safety outcomes. Most previous researches have concentrated on exploring the impacts of various road network attributes and sociodemographic characteristics on crash occurrence. However, the spatial impacts of human activities on traffic crashes are unclear. To fill this gap, this study attempts to investigate how human activities contribute to the spatial pattern of the traffic crashes in urban areas by leveraging multi-source big data. Three kinds of big data sources are used to collect human activities from the New York City. Then, all the collected data are aggregated into regional level (ZIP Code Tabulation Areas). Geographically Weighted Poisson Regression (GWPR) method is applied to identify the relationship between various influencing factors and regional crash frequency. The results reveal that human activity variables from multi-source big data significantly affect the spatial pattern of traffic crashes, which may bring new insights for roadway safety analyses. Comparative analyses are further performed for comparing the GWPR models which consider human activity variables from different big data sources. The results of comparative analyses suggest that multiple big data sources could complement with each other in the coverage of spatial areas and user groups, thereby improving the performance of zone-level crash models and fully unveiling the spatial impacts of human activities on traffic crashes in urban areas. The results of this study could help transportation authorities better identify high-risky regions and develop proactive countermeasures to effectively reduce crashes in these regions.
Jie Bao; Zhao Yang; Weili Zeng; Xiaomeng Shi. Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data. Journal of Transport Geography 2021, 94, 103118 .
AMA StyleJie Bao, Zhao Yang, Weili Zeng, Xiaomeng Shi. Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data. Journal of Transport Geography. 2021; 94 ():103118.
Chicago/Turabian StyleJie Bao; Zhao Yang; Weili Zeng; Xiaomeng Shi. 2021. "Exploring the spatial impacts of human activities on urban traffic crashes using multi-source big data." Journal of Transport Geography 94, no. : 103118.
The automatic detection and tracking of pedestrians under high-density conditions is a challenging task for both computer vision fields and pedestrian flow studies. Collecting pedestrian data is a fundamental task for the modeling and practical implementations of crowd management. Although there are many methods for detecting pedestrians, they may not be easily adopted in the high-density situations. Therefore, we utilized one emerging method based on the deep learning algorithm. Based on the top-view video data of some pedestrian flow experiments recorded by an unmanned aerial vehicle (UAV), we produce our own training datasets. We train the detection model by using Yolo v3, a very popular deep learning model among many available detection models in recent years. We find the detection results are good; e.g., the precisions, recalls, and F1 scores could be larger than 0.95 even when the pedestrian density is as high as 9.0 ped / m 2 . We think this approach could be used for the other pedestrian flow experiments or field data which have similar configurations and can also be useful for automatic crowd density estimation.
Cheng-Jie Jin; Xiaomeng Shi; Ting Hui; Dawei Li; Ke Ma. The Automatic Detection of Pedestrians under the High-Density Conditions by Deep Learning Techniques. Journal of Advanced Transportation 2021, 2021, 1 -11.
AMA StyleCheng-Jie Jin, Xiaomeng Shi, Ting Hui, Dawei Li, Ke Ma. The Automatic Detection of Pedestrians under the High-Density Conditions by Deep Learning Techniques. Journal of Advanced Transportation. 2021; 2021 ():1-11.
Chicago/Turabian StyleCheng-Jie Jin; Xiaomeng Shi; Ting Hui; Dawei Li; Ke Ma. 2021. "The Automatic Detection of Pedestrians under the High-Density Conditions by Deep Learning Techniques." Journal of Advanced Transportation 2021, no. : 1-11.
Crowd egress at narrow exit is a popular research topic, due to its intrinsic importance in architectural designs and building codes. However, relatively few studies have been conducted to verify the performance of pedestrian models for crowd escape at exits, especially relating to different exit designs. This paper aims to verify the applicability of a microscopic pedestrian simulation model, Social Force Model (SFM), embedded in Viswalk software to reproduce the effect of exit design on egress flow under normal and emergency conditions. Empirical data from controlled experiments considering the effects of obstacles size and location of exits under normal and emergency conditions were tested and compared with the simulation from the SFM. Results indicated that after parameter optimization, Viswalk simulation model can provide reasonable estimates for crowd escape under normal situations with a mean RMSE value 1.97s for total evacuation time. However, the simulation model was less capable in reproducing the emergency condition. As compared to the empirical data, clogging events were less spotted under emergency in the simulation. Faster-is-slower effects were not found in both empirical and simulation scenarios. In addition, the exit location effects from simulation data agreed with empirical data, corner exits were more efficient than middle exits under both situations. Meanwhile, the obstacle effects, as observed in empirical data, were less reproduced in the simulation, especially under emergency conditions. The results suggest that the application of the Viswalk model in simulating emergency situations needs scrutiny and further investigations in the future with empirical data.
Xiaomeng Shi; Shuqi Xue; Claudio Feliciani; Nirajan Shiwakoti; Junkai Lin; Dawei Li; Zhirui Ye. Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions. Physica A: Statistical Mechanics and its Applications 2020, 562, 125347 .
AMA StyleXiaomeng Shi, Shuqi Xue, Claudio Feliciani, Nirajan Shiwakoti, Junkai Lin, Dawei Li, Zhirui Ye. Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions. Physica A: Statistical Mechanics and its Applications. 2020; 562 ():125347.
Chicago/Turabian StyleXiaomeng Shi; Shuqi Xue; Claudio Feliciani; Nirajan Shiwakoti; Junkai Lin; Dawei Li; Zhirui Ye. 2020. "Verifying the applicability of a pedestrian simulation model to reproduce the effect of exit design on egress flow under normal and emergency conditions." Physica A: Statistical Mechanics and its Applications 562, no. : 125347.
Over the past decade, the rapid development of e-commerce and express industries in China has resulted in huge environmental costs. Compared with manufacturing industries, the values of green innovation are less recognized in logistics industries. To promote the green practices in logistic enterprises, it is imperative to have a thorough understanding of the determinants of green innovation adoption. To this end, this paper performs an empirical investigation into the intentions to adopt green innovation from 196 Chinese express companies. The determinant variables were constructed from the perspective of technology characteristics (perceived green usefulness and perceived integration ease of use), stakeholder pressure (government, customer, and platform pressures), and social influence. Then, a 20-item scale was designed based on the literature review and expert opinions. The results revealed the significant positive effects of technology characteristics and social influence on the intentions to adopt green innovation. Meanwhile, only the platform pressure was significant with the adopting intentions among the variables from stakeholder pressure. Moreover, variables from technology characteristics were found to have meditation effects between social influence and adopting intentions. Based on the findings, theoretical and practical implications are proposed to promote the green and sustainable development of express companies in China.
Hao Zhang; Jie He; Xiaomeng Shi; Qiong Hong; Jie Bao; Shuqi Xue. Technology Characteristics, Stakeholder Pressure, Social Influence, and Green Innovation: Empirical Evidence from Chinese Express Companies. Sustainability 2020, 12, 2891 .
AMA StyleHao Zhang, Jie He, Xiaomeng Shi, Qiong Hong, Jie Bao, Shuqi Xue. Technology Characteristics, Stakeholder Pressure, Social Influence, and Green Innovation: Empirical Evidence from Chinese Express Companies. Sustainability. 2020; 12 (7):2891.
Chicago/Turabian StyleHao Zhang; Jie He; Xiaomeng Shi; Qiong Hong; Jie Bao; Shuqi Xue. 2020. "Technology Characteristics, Stakeholder Pressure, Social Influence, and Green Innovation: Empirical Evidence from Chinese Express Companies." Sustainability 12, no. 7: 2891.
Freeway diverge segment has significant impacts on current traffic flow, and could affect the heterogeneous traffic flow consisting of manual and intelligent vehicles. The primary objective of this study is to evaluate how intelligent vehicles equipped with cooperative adaptive cruise control (CACC) improve freeway efficiency and safety at an off-ramp bottleneck. Applying randomized forest and back-propagation neural network (BPNN) algorithms, lane-changing characteristics are obtained based on ground-truth vehicle trajectory data extracted from the NGSIM dataset. A microscopic simulation testbed is constructed, in which the realistic PATH CACC models and surrogate safety measures of time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) are used. The results show that both CACC penetration rate and length of diverge influence areas exert considerable influence on road capacity and traffic safety. Overall, the capacity will peak after an initial decrease as the CACC penetration rate increases. The maximum capacity obtained in 100% of CACC vehicle scenario is improved by over 60%, compared with 50% CACC penetration rate scenario. The proposed integration system with 100% CACC penetration rate significantly reduce the rear-end collision risks, decreasing TIT and TET by 70.8%-97.5%. Moreover, the transport system with longer range of lane-changing area has better performance as all other parameters remain unchanged. Findings of this study can support management and operations of Automated Highway Systems in the future.
Changyin Dong; Hao Wang; Ye Li; Xiaomeng Shi; Daiheng Ni; Wei Wang. Application of machine learning algorithms in lane-changing model for intelligent vehicles exiting to off-ramp. Transportmetrica A: Transport Science 2020, 17, 124 -150.
AMA StyleChangyin Dong, Hao Wang, Ye Li, Xiaomeng Shi, Daiheng Ni, Wei Wang. Application of machine learning algorithms in lane-changing model for intelligent vehicles exiting to off-ramp. Transportmetrica A: Transport Science. 2020; 17 (1):124-150.
Chicago/Turabian StyleChangyin Dong; Hao Wang; Ye Li; Xiaomeng Shi; Daiheng Ni; Wei Wang. 2020. "Application of machine learning algorithms in lane-changing model for intelligent vehicles exiting to off-ramp." Transportmetrica A: Transport Science 17, no. 1: 124-150.
Shuqi Xue; Claudio Feliciani; Xiaomeng Shi; Tongfei Li. Corrigendum to ‘Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model’ [Simulation Modelling Practice and Theory 100 (2020) 1–16/102044]. Simulation Modelling Practice and Theory 2020, 103, 102081 .
AMA StyleShuqi Xue, Claudio Feliciani, Xiaomeng Shi, Tongfei Li. Corrigendum to ‘Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model’ [Simulation Modelling Practice and Theory 100 (2020) 1–16/102044]. Simulation Modelling Practice and Theory. 2020; 103 ():102081.
Chicago/Turabian StyleShuqi Xue; Claudio Feliciani; Xiaomeng Shi; Tongfei Li. 2020. "Corrigendum to ‘Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model’ [Simulation Modelling Practice and Theory 100 (2020) 1–16/102044]." Simulation Modelling Practice and Theory 103, no. : 102081.
Wall-following is an important means for pedestrians to navigate during evacuation under limited visibility. Empirical and experimental results regarding wall-following behaviour are scarce in the literature. How pedestrians approach a wall, how they decide on a wall-following direction, and how they address conflicts are still poorly understood. To these ends, we performed evacuation experiments in a mock room. Each participant wore a baseball cap covered with an opaque veil to create a limited visibility condition. Experiment results showed the participants stretched out their arms and attempted to search for the wall tactually in 205 of 270 cases, and in the remaining cases, the participants searched for the wall visually rather than tactually. The findings also reveal underlying behaviour pattern of pedestrians on the decision of wall-following direction. Finally, we propose a wall-following model based on the social force model. The simulation results are consistent with the experimental outcomes.
Shuqi Xue; Rui Jiang; Sze Chun Wong; Claudio Feliciani; Xiaomeng Shi; Bin Jia. Wall-following behaviour during evacuation under limited visibility: experiment and modelling. Transportmetrica A: Transport Science 2020, 16, 626 -653.
AMA StyleShuqi Xue, Rui Jiang, Sze Chun Wong, Claudio Feliciani, Xiaomeng Shi, Bin Jia. Wall-following behaviour during evacuation under limited visibility: experiment and modelling. Transportmetrica A: Transport Science. 2020; 16 (3):626-653.
Chicago/Turabian StyleShuqi Xue; Rui Jiang; Sze Chun Wong; Claudio Feliciani; Xiaomeng Shi; Bin Jia. 2020. "Wall-following behaviour during evacuation under limited visibility: experiment and modelling." Transportmetrica A: Transport Science 16, no. 3: 626-653.
The floor field cellular automaton model (FFCA) has been widely adopted to simulate pedestrian and evacuation dynamics. Many self-organized phenomena could be reproduced with the FFCA model, such as the lane formation in bidirectional pedestrian flow. However, as presented in this study, when we tried to use the FFCA model to simulate an experiment on bidirectional pedestrian flows performed in discrete space and time, we found the model failed to agree with the empirical results. The gridlock formation (not observed in the experiment) was unavoidable in the FFCA model and the clearance time in simulation was much larger than that of the experiment. From the experiments, we observed that people would like to stop if they would foresee a benefit in the near feature and consequently give way to people coming from the opposite direction. This inspired us to incorporate such behavioral rules for modeling pedestrian movements in bidirectional flows. To this end, we introduced a waiting time rule to the original FFCA model. Results showed the performance of the model could be significantly improved. The gridlock probability could be reduced to zero, with clearance time agreeing well with the experimental outcome. Findings from this study can provide meaningful insights for researchers into understanding the pedestrian behavior in bidirectional flow and help develop more reliable simulation software.
Shuqi Xue; Feliciani Claudio; Xiaomeng Shi; Tongfei Li. Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model. Simulation Modelling Practice and Theory 2019, 100, 102044 .
AMA StyleShuqi Xue, Feliciani Claudio, Xiaomeng Shi, Tongfei Li. Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model. Simulation Modelling Practice and Theory. 2019; 100 ():102044.
Chicago/Turabian StyleShuqi Xue; Feliciani Claudio; Xiaomeng Shi; Tongfei Li. 2019. "Revealing the hidden rules of bidirectional pedestrian flow based on an improved floor field cellular automata model." Simulation Modelling Practice and Theory 100, no. : 102044.
Haozhe Cong; Xiaomeng Shi; Jill Cooper; Zhi Ye; Zijian Suo; Xinwei Zhao; Zhirui Ye; Cong Chen. Road rage in China: An exploratory study. Journal of Transportation Safety & Security 2019, 13, 503 -524.
AMA StyleHaozhe Cong, Xiaomeng Shi, Jill Cooper, Zhi Ye, Zijian Suo, Xinwei Zhao, Zhirui Ye, Cong Chen. Road rage in China: An exploratory study. Journal of Transportation Safety & Security. 2019; 13 (5):503-524.
Chicago/Turabian StyleHaozhe Cong; Xiaomeng Shi; Jill Cooper; Zhi Ye; Zijian Suo; Xinwei Zhao; Zhirui Ye; Cong Chen. 2019. "Road rage in China: An exploratory study." Journal of Transportation Safety & Security 13, no. 5: 503-524.
A safer and securer public transport provides a wide range of sustainability benefits to a community. This paper explores passengers’ perception of security checks (SCs) in metro stations, with a focus on the safety and mobility of passenger flows. We used 27 scaling items categorized into five variables: efficiency, comfort, safety, privacy and willingness-to-pay. A questionnaire survey of 880 metro passengers in China showed that respondents are generally homogenous in their perceptions of metro SCs in terms of their agreement on mandatory SC policy and the priority of safety. Most passengers are willing to trade-off their trip efficiency and privacy in exchange for safety improvement, while a small proportion of people are inclined to trade-off their trip efficiency for a more comfortable waiting and riding experiences. Demographic differences such as gender and age group effects are observed. For example, females tend to be more concerned with trip comfort while older passengers are more likely to compromise their privacy with enhancement in safety features. Findings from this study can be a valuable resource to railway authorities in designing and developing a SC system at major railway hubs.
Xiaomeng Shi; Zhirui Ye; Nirajan Shiwakoti; Huaxin Li. Passengers’ Perceptions of Security Check in Metro Stations. Sustainability 2019, 11, 2930 .
AMA StyleXiaomeng Shi, Zhirui Ye, Nirajan Shiwakoti, Huaxin Li. Passengers’ Perceptions of Security Check in Metro Stations. Sustainability. 2019; 11 (10):2930.
Chicago/Turabian StyleXiaomeng Shi; Zhirui Ye; Nirajan Shiwakoti; Huaxin Li. 2019. "Passengers’ Perceptions of Security Check in Metro Stations." Sustainability 11, no. 10: 2930.
Jie Bao; Xiaomeng Shi; Hao Zhang. Spatial Analysis of Bikeshare Ridership With Smart Card and POI Data Using Geographically Weighted Regression Method. IEEE Access 2018, 6, 76049 -76059.
AMA StyleJie Bao, Xiaomeng Shi, Hao Zhang. Spatial Analysis of Bikeshare Ridership With Smart Card and POI Data Using Geographically Weighted Regression Method. IEEE Access. 2018; 6 ():76049-76059.
Chicago/Turabian StyleJie Bao; Xiaomeng Shi; Hao Zhang. 2018. "Spatial Analysis of Bikeshare Ridership With Smart Card and POI Data Using Geographically Weighted Regression Method." IEEE Access 6, no. : 76049-76059.
In a pioneering work in Nature journal, a counter-intuitive prediction that escape rates of people under panic conditions will be enhanced if an obstacle such as a column or a barrier is placed on the “upstream” side of an exit was demonstrated through a simulation model. However, the prediction lacked empirical verification. Despite the substantial works in this topic in the past decade, there is currently a lack of knowledge on how and to what extent the obstacle near an exit can enhance the pedestrian outflow at the bottlenecks during emergency escape. Therefore, the aim of this paper is to present a critical review on the performance of an obstacle near an exit and identify future research directions. It is found that although there is a general consensus on the beneficial effect of an obstacle, there is a large uncertainty on the situations on which the positive effect of obstacle could be observed. In addition, verification of the model’s prediction with empirical data with humans is still largely unexplored. There is no clear established relationship between the exit width, obstacle distance and obstacle size/shape. Also, quantitative understanding of the nature of the clogging transition due to obstacle is a challenging task. Further, researchers have questioned the implementation of such obstacles at bottlenecks in real life scenario. A systematic approach of optimising architectural adjustments that enhances escape dynamics of pedestrians’ crowd in indoor and outdoor public spaces needs to be conducted in future.
Nirajan Shiwakoti; Xiaomeng Shi; Zhirui Ye. A review on the performance of an obstacle near an exit on pedestrian crowd evacuation. Safety Science 2018, 113, 54 -67.
AMA StyleNirajan Shiwakoti, Xiaomeng Shi, Zhirui Ye. A review on the performance of an obstacle near an exit on pedestrian crowd evacuation. Safety Science. 2018; 113 ():54-67.
Chicago/Turabian StyleNirajan Shiwakoti; Xiaomeng Shi; Zhirui Ye. 2018. "A review on the performance of an obstacle near an exit on pedestrian crowd evacuation." Safety Science 113, no. : 54-67.
The purpose of this study is to develop a radiomics model for predicting the histopathological grades of soft tissue sarcomas preoperatively through magnetic resonance imaging (MRI). Thirty-five patients who were pathologically diagnosed with soft tissue sarcomas and their histological grades were recruited. All patients had undergone MRI before surgery on a 3.0T MRI scanner. Radiomics features were extracted from fat-suppressed T2-weighted imaging. We used the least absolute shrinkage and selection operator (LASSO) regression method to select features. Then three machine learning classification methods, including random forests, k-nearest neighbor, and support vector machine algorithm were trained using the 5-fold cross validation strategy to separate the soft tissue sarcomas with low- and high-histopathological grades. The radiomics features were significantly associated with the histopathological grades. Quantitative imaging features (n = 1049) were extracted from fat-suppressed T2-weighted imaging, and five features were selected to construct the radiomics model. The model that used support vector machine classification method achieved the best performance among the three methods, with areas under the receiver operating characteristic curves Area Under Curve (AUC) values of 0.92 ± 0.07, accuracy of 0.88. Good accuracy and AUC could be obtained using only five radiomic features. Therefore, we proposed that three-dimensional imaging features from fat-suppressed T2-weighted imaging could be used as candidate biomarkers for preoperative prediction of histopathological grades of soft tissue sarcomas noninvasively.
Yu Zhang; Yifeng Zhu; Xiaomeng Shi; Juan Tao; Jingjing Cui; Yue Dai; Minting Zheng; Shaowu Wang. Soft Tissue Sarcomas: Preoperative Predictive Histopathological Grading Based on Radiomics of MRI. Academic Radiology 2018, 26, 1262 -1268.
AMA StyleYu Zhang, Yifeng Zhu, Xiaomeng Shi, Juan Tao, Jingjing Cui, Yue Dai, Minting Zheng, Shaowu Wang. Soft Tissue Sarcomas: Preoperative Predictive Histopathological Grading Based on Radiomics of MRI. Academic Radiology. 2018; 26 (9):1262-1268.
Chicago/Turabian StyleYu Zhang; Yifeng Zhu; Xiaomeng Shi; Juan Tao; Jingjing Cui; Yue Dai; Minting Zheng; Shaowu Wang. 2018. "Soft Tissue Sarcomas: Preoperative Predictive Histopathological Grading Based on Radiomics of MRI." Academic Radiology 26, no. 9: 1262-1268.
Complex movement patterns of pedestrian traffic, ranging from unidirectional to multidirectional flows, are frequently observed in major public infrastructure such as transport hubs. These multidirectional movements can result in increased number of conflicts, thereby influencing the mobility and safety of pedestrian facilities. Therefore, empirical data collection on pedestrians’ complex movement has been on the rise in the past two decades. Although there are several reviews of mathematical simulation models for pedestrian traffic in the existing literature, a detailed review examining the challenges and opportunities on empirical studies on the pedestrians complex movements is limited in the literature. The overall aim of this study is to present a systematic review on the empirical data collection for uni- and multidirectional crowd complex movements. We first categorized the complex movements of pedestrian crowd into two general categories, namely, external governed movements and internal driven movements based on the interactions with the infrastructure and among pedestrians, respectively. Further, considering the hierarchy of movement complexity, we decomposed the externally governed movements of pedestrian traffic into several unique movement patterns including straight line, turning, egress and ingress, opposing, weaving, merging, diverging, and random flows. Analysis of the literature showed that empirical data were highly rich in straight line and egress flow while medium rich in turning, merging, weaving, and opposing flows, but poor in ingress, diverging, and random flows. We put emphasis on the need for the future global collaborative efforts on data sharing for the complex crowd movements.
Xiaomeng Shi; Zhirui Ye; Nirajan Shiwakoti; Offer Grembek. A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement. Journal of Advanced Transportation 2018, 2018, 1 -42.
AMA StyleXiaomeng Shi, Zhirui Ye, Nirajan Shiwakoti, Offer Grembek. A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement. Journal of Advanced Transportation. 2018; 2018 ():1-42.
Chicago/Turabian StyleXiaomeng Shi; Zhirui Ye; Nirajan Shiwakoti; Offer Grembek. 2018. "A State-of-the-Art Review on Empirical Data Collection for External Governed Pedestrians Complex Movement." Journal of Advanced Transportation 2018, no. : 1-42.
Xiaomeng Shi; Zhirui Ye; Nirajan Shiwakoti; Dounan Tang; Junkai Lin. Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck. 2018, 1 .
AMA StyleXiaomeng Shi, Zhirui Ye, Nirajan Shiwakoti, Dounan Tang, Junkai Lin. Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck. . 2018; ():1.
Chicago/Turabian StyleXiaomeng Shi; Zhirui Ye; Nirajan Shiwakoti; Dounan Tang; Junkai Lin. 2018. "Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck." , no. : 1.
Folksonomy Tag Application (FTA) has emerged as an important approach of Internet content organization. However, with the massive increase in the scale of data, the information overloading problem has been more severe. On the other hand, traditional personalized recommendation algorithms based on the interaction between “user-item” are not easy to extend to the three dimensional interface of “user-item-tag”. This paper proposes a clustering analysis method for the initial dataset of the Tag Recommendation System (TRS) based on the improvement of Artificial Fish Swarm Algorithm (AFSA). The method is used for dimension reduction of TRS datasets. To this end, considering the weight of the elements in TRS and the score that can reveal user preference, a novel weighted tensor model is established. And in order to complete the personalized recommendation, the model is solved by the tensor decomposition algorithm with dynamic incremental updating. Finally, a comparative analysis between the proposed FTA algorithm and the two classical tag recommendation algorithms is conducted based on two sets of empirical data. The experimental results show that the FTA algorithm has better performance in terms of the recall rate and precision rate.
Hao Zhang; Qiong Hong; Xiaomeng Shi; Jie He. A Social Tagging Recommendation Model Based on Improved Artificial Fish Swarm Algorithm and Tensor Decomposition. Advances in Intelligent Systems and Computing 2018, 3 -13.
AMA StyleHao Zhang, Qiong Hong, Xiaomeng Shi, Jie He. A Social Tagging Recommendation Model Based on Improved Artificial Fish Swarm Algorithm and Tensor Decomposition. Advances in Intelligent Systems and Computing. 2018; ():3-13.
Chicago/Turabian StyleHao Zhang; Qiong Hong; Xiaomeng Shi; Jie He. 2018. "A Social Tagging Recommendation Model Based on Improved Artificial Fish Swarm Algorithm and Tensor Decomposition." Advances in Intelligent Systems and Computing , no. : 3-13.
Urban public transport and public life are closely related. Since routine bus system has the advantage over capacity and flexibility, its role is irreplaceable in urban public transportation system. Thus, the approaches that can take full advantage of routine bus system’s service ability is a key point to improve the level-of-service (LOS) of urban public transportation system. Based on previous research on flexible-route bus systems, this paper proposes a set of design principles, method, and processes which can be adapted to the majority of Chinese cities, especially medium and small-sized cities. This essay will focus on a flexible-route bus mode which can be adopted within Chinese cities and then propose a set of principles, method, and steps to transform existing bus routes in low traffic density areas into flexible bus routes.
Ruoxiao Feng; Zhirui Ye; Xiaomeng Shi. A Feasibility Study on the Application of Flexible-Route Bus System in Chinese Medium and Small-Sized Cities. CICTP 2017 2018, 1 .
AMA StyleRuoxiao Feng, Zhirui Ye, Xiaomeng Shi. A Feasibility Study on the Application of Flexible-Route Bus System in Chinese Medium and Small-Sized Cities. CICTP 2017. 2018; ():1.
Chicago/Turabian StyleRuoxiao Feng; Zhirui Ye; Xiaomeng Shi. 2018. "A Feasibility Study on the Application of Flexible-Route Bus System in Chinese Medium and Small-Sized Cities." CICTP 2017 , no. : 1.
Traffic design and management in historical districts is complicated on account of its outdated infrastructures and the limitation of protecting the inner establishment. This paper investigates the transportation characteristics and transportation structure in historical districts so as to offer proposals to optimize the transportation system. The interactions between pedestrians and vehicles are also studied by adapting their behaviors to qualitative definitions of conflicts and preferences of road users. A case study has been developed in the historical district in Suzhou. The main existing problems in the study area are identified and classified into two classes, perceived problems and quantified problems, and the conceptions like shared space and exclusive travel channel are proposed in order to coordinate different traffic modes in the area and provide more comfortable travel circumstances for tourists. The strategies proposed in the research are finally evaluated by numerical analysis results of a bi-level optimization model.
Zhao Fang; Zhirui Ye; Xiaomeng Shi; Gang Sun. Research on Urban Street Design and Traffic Management in Historical District. CICTP 2017 2018, 1 .
AMA StyleZhao Fang, Zhirui Ye, Xiaomeng Shi, Gang Sun. Research on Urban Street Design and Traffic Management in Historical District. CICTP 2017. 2018; ():1.
Chicago/Turabian StyleZhao Fang; Zhirui Ye; Xiaomeng Shi; Gang Sun. 2018. "Research on Urban Street Design and Traffic Management in Historical District." CICTP 2017 , no. : 1.
We conducted a preliminary evaluation on the performance of Bluetooth/Wi-Fi-based smartphone sensing approach for estimating pedestrian walking characteristics. A fuzzy RSSI-geometric localization method was developed based on the wireless information derived from smartphone sensing. To test the effectiveness of the method, a series of controlled laboratory walking experiments with 50 participants carrying a smartphone accessible to Bluetooth/Wi-Fi were conducted. The experiments included uni-directional and bi-directional movements of participants in a narrow corridor and each experimental setup was repeated for three times. Three smartphone sensing routers equipped with Bluetooth and Wi-Fi scanners were deployed in the experimental sites. Meanwhile, video recordings of participants’ movement from two stereo-cameras and a UAV were used for the verification of ground truth data. Before the walking experiments, essential scanning performance indices of the routers and smartphones under different environmental complexities were tested. Pedestrian walking trajectories and the corresponding motion properties were calculated through using the proposed algorithm and validated by comparison with the ground truth data obtained from the video recordings. Results suggested that Bluetooth/Wi-Fi sensing approach has low detection rate. However, it is noteworthy that the velocity estimation has a relatively higher accuracy than density and flow estimation. Furthermore, flow, density, and speed estimation under normal walking conditions have a relatively higher accuracy than that under slow running conditions, suggesting that the walking speed affects the detection rate. Moreover, contrary to intuition, the estimation of macroscopic parameters revealed higher accuracy in bi-directional movement as compared to uni-directional movement. Findings of this study might be helpful for identifying the limitations and opportunities of Bluetooth/Wi-Fi sensing devices in terms of the automatic collection of pedestrian empirical data.
Xiaomeng Shi; Xinwei Zhao; Zhirui Ye; Nirajan Shiwakoti; Jiajian Lu. Estimating Pedestrian Walking Characteristics by Use of Smartphone Sensing: An Experimental Study. CICTP 2017 2018, 1 .
AMA StyleXiaomeng Shi, Xinwei Zhao, Zhirui Ye, Nirajan Shiwakoti, Jiajian Lu. Estimating Pedestrian Walking Characteristics by Use of Smartphone Sensing: An Experimental Study. CICTP 2017. 2018; ():1.
Chicago/Turabian StyleXiaomeng Shi; Xinwei Zhao; Zhirui Ye; Nirajan Shiwakoti; Jiajian Lu. 2018. "Estimating Pedestrian Walking Characteristics by Use of Smartphone Sensing: An Experimental Study." CICTP 2017 , no. : 1.