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Ming Zhong
Engineering Research Center for Transportation Safety of Ministry of Education, National Engineering Research Center for Water Transport Safety, Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan 430063, China

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Journal article
Published: 29 January 2021 in Sustainability
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Understanding how drivers behave at stop-controlled intersection is of critical importance for the control and management of an urban traffic system. It is also a critical element of consideration in the burgeoning field of smart infrastructure and connected and autonomous vehicles (CAV). A number of past efforts have been devoted to investigating the driver behavioral patterns when they pass through stop-controlled intersections. However, the majority of these studies have been limited to qualitative descriptions and analyses of driver behavior due to the unavailability of high-resolution vehicle data and sound methodology for classifying various driver behaviors. In this paper, we introduce a methodology that uses computer-vision vehicle trajectory data and unsupervised clustering techniques to classify different types of driver behaviors, infer the underlying mechanism and compare their impacts on safety. Two major types of behaviors are investigated, including vehicle stopping behavior and vehicle approaching patterns, using two clustering algorithms: a bisecting K-means algorithm for classifying stopping behavior, and the improved density-based spatial clustering of applications with noise (DBSCAN) algorithm for classifying vehicle approaching patterns. The methodology is demonstrated using a case study involving five stop-controlled intersections in Montreal, Canada. The results from the analysis show that there exist five distinctive classes of driver behaviors representing different levels of risk in both vehicle stopping and approaching processes. This finding suggests that the proposed methodology could be applied to develop new safety surrogate measures and risk analysis methods for network screening and countermeasure analyses of stop-controlled intersections.

ACS Style

Xiamei Wen; Liping Fu; Ting Fu; Jessica Keung; Ming Zhong. Driver Behavior Classification at Stop-Controlled Intersections Using Video-Based Trajectory Data. Sustainability 2021, 13, 1404 .

AMA Style

Xiamei Wen, Liping Fu, Ting Fu, Jessica Keung, Ming Zhong. Driver Behavior Classification at Stop-Controlled Intersections Using Video-Based Trajectory Data. Sustainability. 2021; 13 (3):1404.

Chicago/Turabian Style

Xiamei Wen; Liping Fu; Ting Fu; Jessica Keung; Ming Zhong. 2021. "Driver Behavior Classification at Stop-Controlled Intersections Using Video-Based Trajectory Data." Sustainability 13, no. 3: 1404.

Journal article
Published: 09 March 2020 in ISPRS International Journal of Geo-Information
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The flow in meandering rivers is characterized by rapid changes in flow velocity and water level, especially in flooded environments. Accurate cross-sectional observation data enable continuous monitoring of flow conditions, which is important for river navigation. In this paper, cross-sectional data based flow modeling and rendering methods are studied to build an interactive hybrid flow environment for three-dimensional river shipping. First, the sparse cross-sectional data are extrapolated and interpolated to provide dense sampling points. Then, the data are visualized separately by dynamic texture mapping, particle tracking, streamline rendering, and contour surface rendering. Finally, the rendering models are integrated with ship animation to build a comprehensive hybrid river navigation scenario. The proposed methods are tested by visualizing measured cross-sectional data in the Yangtze River using an open-source software, called World Wind. The experimental results demonstrate that the hybrid flow rendering achieves comprehensive visual effect and the rendering frame rate is greater than 30. The interactive hybrid flow visualization is beneficial to support river shipping analysis.

ACS Style

Xuequan Zhang; Jin Liu; Zihe Hu; Ming Zhong. Flow Modeling and Rendering to Support 3D River Shipping Based on Cross-Sectional Observation Data. ISPRS International Journal of Geo-Information 2020, 9, 156 .

AMA Style

Xuequan Zhang, Jin Liu, Zihe Hu, Ming Zhong. Flow Modeling and Rendering to Support 3D River Shipping Based on Cross-Sectional Observation Data. ISPRS International Journal of Geo-Information. 2020; 9 (3):156.

Chicago/Turabian Style

Xuequan Zhang; Jin Liu; Zihe Hu; Ming Zhong. 2020. "Flow Modeling and Rendering to Support 3D River Shipping Based on Cross-Sectional Observation Data." ISPRS International Journal of Geo-Information 9, no. 3: 156.

Journal article
Published: 21 February 2020 in Journal of Advanced Transportation
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This paper proposes an improved impedance function for roads with mixed traffic. It is known that only limited studies consider the impact of nonmotorized traffic on travel impedance of a road segment, and a comparison of the impedance considering nonmotorized traffic with the classic BPR function, which does not consider the former, is scarce. Most of the previous studies targeted road conditions in developed countries, where the presence of nonmotorized traffic is negligible, and therefore limited efforts have been invested to develop improved impedance function considering mixed traffic. To overcome this limitation, this paper develops an improved impedance function and carries out a case study for a road in the city of Wuhan, China. The improved impedance function explicitly considers the interaction between motorized and nonmotorized traffic. Taxi GPS data from the case study road is used to extract and analyze the travel time of the “probe vehicles” running through the sampled segment at any time during a sampling day. The capacity of the road segment is measured, and the traffic flow of motorized vehicles and nonmotorized vehicles on the segment is counted. Based on the above data, the classic BPR function and the improved one proposed in this paper are calibrated. After comparing and analyzing the observed road impedance based on both analytical and simulation results, the classic BPR function and the proposed impedance function, the proposed impedance function is found to be more accurate to simulate the observed road impedance, with the error reducing from 14.83 s with the classic BPR impedance function to 6.50 s with the improved function. The proposed impedance function possesses a simple structure and high flexibility, and the parameters calibrated in this paper can be applied to similar roads to provide more realistic impedance than the previous ones based on the classic BPR function. The calibrated improved impedance function’s transferability to other similar roads is validated by applying it to another road and the results show that the percentage error between the predicted travel times and the observed ones is only 3.8%.

ACS Style

Fei Zhao; Liping Fu; Ming Zhong; Shaobo Liu; Xudong Wang; Junda Huang; Xiaofeng Ma. Development and Validation of Improved Impedance Functions for Roads with Mixed Traffic Using Taxi GPS Trajectory Data and Simulation. Journal of Advanced Transportation 2020, 2020, 1 -12.

AMA Style

Fei Zhao, Liping Fu, Ming Zhong, Shaobo Liu, Xudong Wang, Junda Huang, Xiaofeng Ma. Development and Validation of Improved Impedance Functions for Roads with Mixed Traffic Using Taxi GPS Trajectory Data and Simulation. Journal of Advanced Transportation. 2020; 2020 ():1-12.

Chicago/Turabian Style

Fei Zhao; Liping Fu; Ming Zhong; Shaobo Liu; Xudong Wang; Junda Huang; Xiaofeng Ma. 2020. "Development and Validation of Improved Impedance Functions for Roads with Mixed Traffic Using Taxi GPS Trajectory Data and Simulation." Journal of Advanced Transportation 2020, no. : 1-12.

Journal article
Published: 08 October 2019 in Sustainability
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It is believed that the “scissors difference” of socioeconomics between rural and urban households in typical municipalities of China is significant. This may result in differences in their behavior and has important implications for urban land use and transportation planning policies, as well as related modeling accuracy and data requirements. However, detailed analyses regarding such “scissors differences” between rural and urban groups in China have not been done before. In this study, travel survey data collected from the City of Wuhan in 2008 is used to study if rural and urban households are statistically different in terms of household income, household size, space consumption, highest household mobility and travel distance. A set of statistical tests, such as the Kolmogorov–Smirnov test, Mann–Whitney U test and Kruskal–Wallis H test, are applied to the study data. The study results show that the “scissors difference” is found to be statistically significant in terms of household size (HS), household income (HI), building area (BA) consumed and household mobility (except for travel distance) between rural and urban households. Conversely, analyses applied to travel distance of urban and rural household subgroups (categorized by HS and HI) reveal that the urban and rural counterparts show almost exactly opposite behavior. The study results also suggest that such differences should be explicitly considered in relevant modeling exercises by separately setting up urban and rural household groups, but the number of household groups used should be determined based on a balance between modeling accuracy and data required/modeling workload.

ACS Style

Ming Zhong; Qi Tang; Xiaofeng Ma; John Douglas Hunt. Scissors Difference of Socioeconomics, Travel and Space Consumption Behavior of Rural and Urban Households and Its Impact on Modeling Accuracy and Data Requirements. Sustainability 2019, 11, 5534 .

AMA Style

Ming Zhong, Qi Tang, Xiaofeng Ma, John Douglas Hunt. Scissors Difference of Socioeconomics, Travel and Space Consumption Behavior of Rural and Urban Households and Its Impact on Modeling Accuracy and Data Requirements. Sustainability. 2019; 11 (19):5534.

Chicago/Turabian Style

Ming Zhong; Qi Tang; Xiaofeng Ma; John Douglas Hunt. 2019. "Scissors Difference of Socioeconomics, Travel and Space Consumption Behavior of Rural and Urban Households and Its Impact on Modeling Accuracy and Data Requirements." Sustainability 11, no. 19: 5534.

Journal article
Published: 22 August 2019 in ISPRS International Journal of Geo-Information
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The 3D road network scene helps to simulate the distribution of road infrastructure and the corresponding traffic conditions. However, the existing road modeling methods have limitations such as inflexibility in different types of road construction, inferior quality in visual effects and poor efficiency for large-scale model rendering. To tackle these challenges, a template-based 3D road modeling method is proposed in this paper. In this method, the road GIS data is first pre-processed before modeling. The road centerlines are analyzed to extract topology information and resampled to improve path accuracy and match the terrain. Meanwhile, the road network is segmented and organized using a hierarchical block data structure. Road elements, including roadbeds, road facilities and moving vehicles are then designed based on templates. These templates define the geometric and semantic information of elements along both the cross-section and road centerline. Finally, the road network scene is built by the construction algorithms, where roads, at-grade intersections, grade separated areas and moving vehicles are modeled and simulated separately. The proposed method is tested by generating large-scale virtual road network scenes in the World Wind, an open source software package. The experimental results demonstrate that the method is flexible and can be used to develop different types of road models and efficiently simulate large-scale road network environments.

ACS Style

Xuequan Zhang; Ming Zhong; Shaobo Liu; Luoheng Zheng; Yumin Chen. Template-Based 3D Road Modeling for Generating Large-Scale Virtual Road Network Environment. ISPRS International Journal of Geo-Information 2019, 8, 364 .

AMA Style

Xuequan Zhang, Ming Zhong, Shaobo Liu, Luoheng Zheng, Yumin Chen. Template-Based 3D Road Modeling for Generating Large-Scale Virtual Road Network Environment. ISPRS International Journal of Geo-Information. 2019; 8 (9):364.

Chicago/Turabian Style

Xuequan Zhang; Ming Zhong; Shaobo Liu; Luoheng Zheng; Yumin Chen. 2019. "Template-Based 3D Road Modeling for Generating Large-Scale Virtual Road Network Environment." ISPRS International Journal of Geo-Information 8, no. 9: 364.

Journal article
Published: 17 July 2019 in ISPRS International Journal of Geo-Information
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Anomalous urban mobility pattern refers to abnormal human mobility flow in a city. Anomalous urban mobility pattern detection is important in the study of urban mobility. In this paper, a framework is proposed to identify anomalous urban mobility patterns based on taxi GPS trajectories and Point of Interest (POI) data. In the framework, functional regions are first generated based on the distribution of POIs by the DBSCAN clustering algorithm. A Weighted Term Frequency-Inverse Document Frequency (WTF-IDF) method is proposed to identify function values in each region. Then, the Origin-Destination (OD) of trips between functional regions is extracted from GPS trajectories to detect anomalous urban mobility patterns. Mobility vectors are established for each time interval based on the OD of trips and are classified into clusters by the mean shift algorithm. Abnormal urban mobility patterns are identified by processing the mobility vectors. A case study in the city of Wuhan, China, is conducted; the experimental results show that the proposed method can effectively identify daily and hourly anomalous urban mobility patterns.

ACS Style

Zhenzhou Xu; Ge Cui; Ming Zhong; Xin Wang. Anomalous Urban Mobility Pattern Detection Based on GPS Trajectories and POI Data. ISPRS International Journal of Geo-Information 2019, 8, 308 .

AMA Style

Zhenzhou Xu, Ge Cui, Ming Zhong, Xin Wang. Anomalous Urban Mobility Pattern Detection Based on GPS Trajectories and POI Data. ISPRS International Journal of Geo-Information. 2019; 8 (7):308.

Chicago/Turabian Style

Zhenzhou Xu; Ge Cui; Ming Zhong; Xin Wang. 2019. "Anomalous Urban Mobility Pattern Detection Based on GPS Trajectories and POI Data." ISPRS International Journal of Geo-Information 8, no. 7: 308.

Journal article
Published: 12 January 2019 in Sustainability
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Major cities in developing countries are undergoing massive transportation infrastructure construction, which has significant impacts on the land use and economic activities in these cities. Standard Cost–Benefit Analysis (CBA) is applied to quantify the user benefits of transport projects, but does not provide an answer as to who will obtain the benefits and who will lose out and excludes the calculation of Wider Economic Impacts (WEIs) which can sometimes be large and hardly negligible. This paper introduces thoughts and experiences obtained through the design and development of an integrated land use transport model for the assessment of the WEI of a transport infrastructure project. The development and application of such an integrated model for WEI analysis should help decision-makers understand not only the “direct or immediate” impact of transport infrastructure on mobility, but also those “indirect or long-term” impacts on the distribution patterns of economic activities, corresponding land use, and resulting urban structure.

ACS Style

Wanle Wang; Ming Zhong; John Douglas Hunt. Analysis of the Wider Economic Impact of a Transport Infrastructure Project Using an Integrated Land Use Transport Model. Sustainability 2019, 11, 364 .

AMA Style

Wanle Wang, Ming Zhong, John Douglas Hunt. Analysis of the Wider Economic Impact of a Transport Infrastructure Project Using an Integrated Land Use Transport Model. Sustainability. 2019; 11 (2):364.

Chicago/Turabian Style

Wanle Wang; Ming Zhong; John Douglas Hunt. 2019. "Analysis of the Wider Economic Impact of a Transport Infrastructure Project Using an Integrated Land Use Transport Model." Sustainability 11, no. 2: 364.

Articles
Published: 27 September 2018 in Transportation Planning and Technology
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In recent years, there has been considerable research interest in short-term traffic flow forecasting. However, forecasting models offering a high accuracy at a fine temporal resolution (e.g. 1 or 5 min) and lane level are still rare. In this study, a combination of genetic algorithm, neural network and locally weighted regression is used to achieve optimal prediction under various input and traffic settings. The genetically optimized artificial neural network (GA-ANN) and locally weighted regression (GA-LWR) models are developed and tested, with the former forecasting traffic flow every 5-min within a 30-min period and the latter for forecasting traffic flow of a particular 5-min period of each for four lanes of an urban arterial road in Beijing, China. In particular, for morning peak and off-peak traffic flow prediction, the GA-ANN 5-min traffic flow model results in average errors of 3–5% and most 95th percentile errors of 7–14% for each of the four lanes; for the peak and off-peak time traffic flow predictions, the GA-LWR 5-min traffic flow model results in average errors of 2–4% and most 95th percentile errors are lower than 10% for each of the four lanes. When compared to previous models that usually offer average errors greater than 6–15%, such empirical findings should be of interest to and instrumental for transportation authorities to incorporate in their city- or state-wide Advanced Traveller Information Systems (ATIS).

ACS Style

Asif Raza; Ming Zhong. Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting. Transportation Planning and Technology 2018, 41, 901 -917.

AMA Style

Asif Raza, Ming Zhong. Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting. Transportation Planning and Technology. 2018; 41 (8):901-917.

Chicago/Turabian Style

Asif Raza; Ming Zhong. 2018. "Hybrid artificial neural network and locally weighted regression models for lane-based short-term urban traffic flow forecasting." Transportation Planning and Technology 41, no. 8: 901-917.

Conference paper
Published: 02 July 2018 in CICTP 2018
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Growing urban traffic congestion is one of the major problems of today’s transportation system. Properly understanding the nature of transit travel demand is at the heart of transportation policy and the success of transit systems. Unfortunately, in analyzing transit travel demand and level of transit use, most existing studies have focused on only a few aspects of transit systems and overlooked basic accessibility and transportation equity. This study investigates the determining factors for transit travel demand by bus and subway in Wuhan. This research is primarily concerned with two concepts: accessibility and equity. Although the demand for transit travel in Wuhan is rapidly increasing, the current transportation infrastructure is lacking in the provision of basic accessibility to low-income and suburban households. To meet passenger demand, high public transit accessibility is vital to provide basic accessibility to key locations such as job centers.

ACS Style

Asif Raza; Ming Zhong. Evaluating Public Transit Equity Using the Concept of Accessibility. CICTP 2018 2018, 1 .

AMA Style

Asif Raza, Ming Zhong. Evaluating Public Transit Equity Using the Concept of Accessibility. CICTP 2018. 2018; ():1.

Chicago/Turabian Style

Asif Raza; Ming Zhong. 2018. "Evaluating Public Transit Equity Using the Concept of Accessibility." CICTP 2018 , no. : 1.

Article
Published: 06 February 2018 in Journal of Systems Science and Systems Engineering
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Literature review indicates that sample size, attribute variance and within-sample choice distribution of alternatives are important considerations in the estimation of multinomial logit (MNL) models, but their impacts on the estimation accuracy have not been systematically studied. Therefore, the objective of this paper is to provide an empirical examination to the above issues through a set of simulated discrete choice preference and rank ordered preference datasets. In this paper, the utility coefficients, alternative specific constants (ASCs), and the mean and standard deviation of the four attributes for a set of seven hypothetical alternatives are specified as a priori. Then, synthetic datasets, with varying sample size, attribute variance and within-sample choice distribution are simulated. Based on these datasets, the utility coefficients and ASCs of the specified MNLs are re-estimated and compared with the original values specified as the priori. It is found that (1) the estimation accuracy of utility parameters increases as the sample size increases; (2) the utility coefficients can be re-estimated with reasonable accuracy, but the estimates of the ASCs are confronted with much larger errors; (3) as the variances of the alternative attributes increase, the estimation accuracy improves significantly; and (4) as the distribution of chosen choices becomes more balanced across alternatives within sample datasets, the hit-ratio decreases. The results indicate that (a) under a similar setting presented in this paper, a large sample consisting of a few thousand observations (3000–4000) may be needed in order to provide reasonable estimates for utility coefficients, particularly for ASCs; (b) a larger, but realistic attribute space is preferred in the stated preference survey design; and (c) choice datasets with unbalanced “chosen” choice frequency distribution is preferred, in order to better capture the elasticity between the “perceived utility” associated with alternative’s attributes.

ACS Style

Minhui Zeng; Ming Zhong; John Douglas Hunt. Analysis of the Impact of Sample Size, Attribute Variance and Within-Sample Choice Distribution on the Estimation Accuracy of Multinomial Logit Models Using Simulated Data. Journal of Systems Science and Systems Engineering 2018, 27, 771 -789.

AMA Style

Minhui Zeng, Ming Zhong, John Douglas Hunt. Analysis of the Impact of Sample Size, Attribute Variance and Within-Sample Choice Distribution on the Estimation Accuracy of Multinomial Logit Models Using Simulated Data. Journal of Systems Science and Systems Engineering. 2018; 27 (6):771-789.

Chicago/Turabian Style

Minhui Zeng; Ming Zhong; John Douglas Hunt. 2018. "Analysis of the Impact of Sample Size, Attribute Variance and Within-Sample Choice Distribution on the Estimation Accuracy of Multinomial Logit Models Using Simulated Data." Journal of Systems Science and Systems Engineering 27, no. 6: 771-789.

Conference paper
Published: 18 January 2018 in CICTP 2017
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Short-term traffic speed prediction plays a key importance in urban traffic management and operation. Literature review indicates that lane-based short-term urban traffic forecasting is still rare. In this study, genetic algorithms (GAs) are used to optimize the input data sets for artificial neural network (ANN) models and locally weighted regression (LWR) models to achieve optimal prediction under various input and traffic settings. The GA designed ANN (GA-ANN) and GA designed LWR (GA-LWR) models are used to predict 5 minute short-term traffic speed prediction for four lanes of an urban road. For the peak and off-peak time traffic speed prediction, both GA-ANN and GA-LWR aggregate and disaggregate models are developed and tested, with the former forecasting traffic speed of every 5 min with a 30 min period (e.g., 7:25–7:55 am morning peak) and the latter for forecasting traffic speed of a particular 5-min of each weekday (e.g., 7:25–7:30 am of Monday to Friday). In addition, for peak and off-peak traffic speed prediction, the GA-ANN disaggregate model results in most cases average errors of 3-4% and the 95th percentile errors of lower than 8% for each of the four lanes. Meanwhile, for the peak and off-peak time traffic speed prediction, the GA-LWR disaggregate model results in most cases average errors of 1-2% and the 95th percentile errors of lower than 4% for each of the four lanes. When compared to previous models that usually offer average errors more than 6-15%, such empirical findings is promising and instrumental for transportation authorities to put through their city- or state-wide ATIS.

ACS Style

Asif Raza; Ming Zhong. An Optimized Hybrid Lane-Based Short-Term Urban Traffic Forecasting Using Artificial Neural Network and Locally Weighted Regression Models. CICTP 2017 2018, 1 .

AMA Style

Asif Raza, Ming Zhong. An Optimized Hybrid Lane-Based Short-Term Urban Traffic Forecasting Using Artificial Neural Network and Locally Weighted Regression Models. CICTP 2017. 2018; ():1.

Chicago/Turabian Style

Asif Raza; Ming Zhong. 2018. "An Optimized Hybrid Lane-Based Short-Term Urban Traffic Forecasting Using Artificial Neural Network and Locally Weighted Regression Models." CICTP 2017 , no. : 1.

Journal article
Published: 05 January 2018 in Journal of Transport and Land Use
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Massive construction of transportation infrastructure and fast growth of private car ownership have brought unprecedented changes in land use and transportation systems to cities and regions in many developing countries. Traditional “four-step” travel demand models, which are not designed to assess transport policies under the case of rapid land-use change, cannot be used to achieve coordinated planning of transport and land use. Therefore, there is a pressing need to develop and use integrated land-use transport models (ILUTMs), which consider interactions among socioeconomic activities, urban land use, and transportation development, for policy analysis and for guiding the progressive urbanization process taking place in many parts of these countries. In light of this, efforts have been invested in developing production, exchange, and consumption allocation system (PECAS) models for the cities of Shanghai, Wuhan, and Guangzhou in mainland China. This paper presents the cultural, organizational, and technical challenges encountered in the development of PECAS models for the cities of Shanghai, Wuhan, and Guangzhou and the mitigating solutions from the development teams for taking up or working around them. The solutions and discussions presented in this paper should be interesting to researchers and practitioners for developing ILUTMs in the context of a developing country like China.

ACS Style

Ming Zhong; Wanle Wang; John Douglas Hunt; Haixiao Pan; Tao Chen; Jianzhong Li; Wei Yang; Ke Zhang. Solutions to cultural, organizational, and technical challenges in developing PECAS models for the cities of Shanghai, Wuhan, and Guangzhou. Journal of Transport and Land Use 2018, 11, 1 .

AMA Style

Ming Zhong, Wanle Wang, John Douglas Hunt, Haixiao Pan, Tao Chen, Jianzhong Li, Wei Yang, Ke Zhang. Solutions to cultural, organizational, and technical challenges in developing PECAS models for the cities of Shanghai, Wuhan, and Guangzhou. Journal of Transport and Land Use. 2018; 11 (1):1.

Chicago/Turabian Style

Ming Zhong; Wanle Wang; John Douglas Hunt; Haixiao Pan; Tao Chen; Jianzhong Li; Wei Yang; Ke Zhang. 2018. "Solutions to cultural, organizational, and technical challenges in developing PECAS models for the cities of Shanghai, Wuhan, and Guangzhou." Journal of Transport and Land Use 11, no. 1: 1.

Research article
Published: 31 May 2015 in Mathematical Problems in Engineering
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The rollover accidents induced by severe maneuvers are very dangerous and mostly happen to vehicles with elevated center of gravity, such as heavy-duty trucks and pickup trucks. Unfortunately, it is hard for drivers of those vehicles to predict and prevent the trend of the maneuver-induced (untripped) rollover ahead of time. In this study, a lateral load transfer ratio which reflects the load distribution of left and right tires is used to indicate the rollover criticality. An antiroll controller is designed with smooth sliding mode control technique for vehicles, in which an active antiroll suspension is installed. A simplified second order roll dynamic model with additive sector bounded uncertainties is used for control design, followed by robust stability analysis. Combined with the vehicle dynamics simulation package TruckSim, MATLAB/Simulink is used for simulating experiment. The results show that the applied controller can improve the roll stability under some typical steering maneuvers, such as Fishhook and J-turn. This direct antiroll control method could be more effective for untripped rollover prevention when driver deceleration or steering is too late. It could also be extended to handle tripped rollovers.

ACS Style

Duanfeng Chu; Xiao-Yun Lu; Chaozhong Wu; Zhaozheng Hu; Ming Zhong. Smooth Sliding Mode Control for Vehicle Rollover Prevention Using Active Antiroll Suspension. Mathematical Problems in Engineering 2015, 2015, 1 -8.

AMA Style

Duanfeng Chu, Xiao-Yun Lu, Chaozhong Wu, Zhaozheng Hu, Ming Zhong. Smooth Sliding Mode Control for Vehicle Rollover Prevention Using Active Antiroll Suspension. Mathematical Problems in Engineering. 2015; 2015 ():1-8.

Chicago/Turabian Style

Duanfeng Chu; Xiao-Yun Lu; Chaozhong Wu; Zhaozheng Hu; Ming Zhong. 2015. "Smooth Sliding Mode Control for Vehicle Rollover Prevention Using Active Antiroll Suspension." Mathematical Problems in Engineering 2015, no. : 1-8.

Articles
Published: 28 May 2015 in Transportation Planning and Technology
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Activity-based travel demand modeling (ABTDM) has often been viewed as an advanced approach, due to its higher fidelity and better policy sensitivity. However, a review of the literature indicates that no study has been undertaken to investigate quantitatively the differences and accuracy between an ABTDM approach and a traditional four-step travel demand model. In this paper we provide a comparative analysis against each step – trip generation, trip distribution, mode split, and network assignment – between an ABTDM developed using travel diary data from the Tampa Bay Region in Florida and the Tampa Bay Regional Planning Model (TBRPM), an existing traditional four-step model for the same area. Results show salient differences between the TBRPM and the ABTDM, in terms of modeling performance and accuracy, in each of the four steps. For example, trip production rates calculated from the travel diary data are found to be either double or a quarter less than those used in the TBRPM. On the other hand, trip attraction rates computed from activity-based travel simulations are found to be either more than double or one tenth less than those used in the TBRPM. The trip distribution curves from the two models are similar, but both average and peak trip lengths of the two are significantly different. Mode split analyses show that the TBRPM may underestimate driving trips and fail to capture any usage of alternative modes, such as taxi and nonmotorized (e.g., walking and bicycling) modes. In addition, the ABTDMs are found to be less capable of reproducing observed traffic counts when compared to the TBRPM, most likely due to not considering external and through trips. The comparative results presented can help transportation engineers and planners better understand the strengths and weaknesses of the two types of model and this should assist decision-makers in choosing a better modeling tool for their planning initiatives.

ACS Style

Ming Zhong; Rong Shan; Donglei Du; Chunyu Lu. A comparative analysis of traditional four-step and activity-based travel demand modeling: a case study of Tampa, Florida. Transportation Planning and Technology 2015, 38, 517 -533.

AMA Style

Ming Zhong, Rong Shan, Donglei Du, Chunyu Lu. A comparative analysis of traditional four-step and activity-based travel demand modeling: a case study of Tampa, Florida. Transportation Planning and Technology. 2015; 38 (5):517-533.

Chicago/Turabian Style

Ming Zhong; Rong Shan; Donglei Du; Chunyu Lu. 2015. "A comparative analysis of traditional four-step and activity-based travel demand modeling: a case study of Tampa, Florida." Transportation Planning and Technology 38, no. 5: 517-533.

Research article
Published: 01 January 2015 in Environment and Planning B: Planning and Design
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A literature review indicates that most integrated land-use transport models (ILUTMs) estimate base-year floorspace data according to limited population and employment data provided by the census and, in general, the accuracy is unknown. This paper assesses the utility of airborne Light Detection And Ranging (LiDAR) technology as a valuable tool for extracting base-year floorspace using the following three datasets: a geographic vector building footprint layer, a LiDAR dataset, and field survey data for the south side of the City of Fredericton, Canada. It is found through a statistical comparison with the results from the field survey that LiDAR data can be used to extract buildings and estimate floorspace with a good degree of accuracy. Further, two base-year floorspace estimation methods, one based on the LiDAR data and the other on census data, are compared. In general, our results show that the traditional census-based approach may not be reliable for estimating base-year floorspace. Using the extracted floorspace from the LiDAR data as the basis, for residential floorspace estimation the average absolute percentage errors (APE) of the census-based approach is 16% and the 95th percentile APE is 34%. On the other hand, for employment floorspace estimation, the accuracy of the census-based approach is even lower, with average errors of 50% or higher and the 95th percentile APEs as high as 163% up to 400% for several land-use categories. All the above statistics indicate that the traditional census-based approach is unreliable and inaccurate for modelers and planners to prepare their base-year floorspace, and therefore suggest a better way be explored. Study results clearly show the utility of LiDAR data and imply that it can be used as a powerful add-on for ILUTMs in general.

ACS Style

Sajad Shiravi; Ming Zhong; Seyed Ahad Beykaei; John Douglas Hunt; John E Abraham. An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach. Environment and Planning B: Planning and Design 2015, 42, 708 -729.

AMA Style

Sajad Shiravi, Ming Zhong, Seyed Ahad Beykaei, John Douglas Hunt, John E Abraham. An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach. Environment and Planning B: Planning and Design. 2015; 42 (4):708-729.

Chicago/Turabian Style

Sajad Shiravi; Ming Zhong; Seyed Ahad Beykaei; John Douglas Hunt; John E Abraham. 2015. "An assessment of the utility of LiDAR data in extracting base-year floorspace and a comparison with the census-based approach." Environment and Planning B: Planning and Design 42, no. 4: 708-729.

Journal article
Published: 01 October 2014 in Transportation Research Part C: Emerging Technologies
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ACS Style

Seyed Ahad Beykaei; Ming Zhong; Sajad Shiravi; Yun Zhang. A hierarchical rule-based land use extraction system using geographic and remotely sensed data: A case study for residential uses. Transportation Research Part C: Emerging Technologies 2014, 47, 155 -167.

AMA Style

Seyed Ahad Beykaei, Ming Zhong, Sajad Shiravi, Yun Zhang. A hierarchical rule-based land use extraction system using geographic and remotely sensed data: A case study for residential uses. Transportation Research Part C: Emerging Technologies. 2014; 47 ():155-167.

Chicago/Turabian Style

Seyed Ahad Beykaei; Ming Zhong; Sajad Shiravi; Yun Zhang. 2014. "A hierarchical rule-based land use extraction system using geographic and remotely sensed data: A case study for residential uses." Transportation Research Part C: Emerging Technologies 47, no. : 155-167.

Journal article
Published: 19 July 2014 in Procedia - Social and Behavioral Sciences
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A public transit system consists of various components in which all must be considered together in order to develop an efficient and sustainable transit network. Providing convenient access to public transit enhances the service performance, reliability and will also result in higher public usage. Conventionally transit stop locations and spacing are determined based on aggregate measures of population density on a zonal basis using simple buffer analysis. This method has been criticized as inaccurate, as the population is rarely uniformly distributed over zones. In this research, transit stop access coverage is estimated using building geometric information accurately extracted from the LiDAR data collected in the City of Fredericton, Canada. LiDAR data is mostly used for flood hazard studies but can also be used for other purposes such as 3D building modeling. Through this approach building floorspace information and therefore a much more accurate measurement of transit stop coverage based on the building floorspace is obtained at disaggregate spatial level and compared with the conventional buffer-density approach through a real example in the City of Fredericton. Overall, it is found that this approach can provide transit planners with much more improved building and population distribution information at a very precise spatial level, in order to set the transit stops at their optimal locations.

ACS Style

Sajad Shiravi; Ming Zhong; Faranak Hosseini. Using LiDAR Data for Measuring Transit Stop Coverage. Procedia - Social and Behavioral Sciences 2014, 138, 715 -721.

AMA Style

Sajad Shiravi, Ming Zhong, Faranak Hosseini. Using LiDAR Data for Measuring Transit Stop Coverage. Procedia - Social and Behavioral Sciences. 2014; 138 ():715-721.

Chicago/Turabian Style

Sajad Shiravi; Ming Zhong; Faranak Hosseini. 2014. "Using LiDAR Data for Measuring Transit Stop Coverage." Procedia - Social and Behavioral Sciences 138, no. : 715-721.

Conference paper
Published: 24 June 2014 in CICTP 2014
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It is widely recognized that driving anger plays a major role in road safety. Many studies have been carried out in this field, and the significance of incentive factors of driving anger - in terms of driver's personal characteristics (e.g., sex or education) and external environment (e.g., interaction among drivers and obstruction) - has been proven. Questionnaire surveys and simulation experiments are used as the basis for those studies, but such methods make the studies very unrealistic. In this study, 22 licensed drivers were hired to drive along a specified route in Wuhan, China. Physiological data and drivers' reported driving anger and observed driving behavior are used to study the ranking of the contribution of various incentive factors to and their causal relationship with driving anger. Study results show that the following top three factors result in about three quarters of driving anger: (1) red traffic lights, (2) congestion, and (3) offensive hogging behavior of surrounding vehicles. Further, statistical analyses show that the p-values from the Somers-d test applied to red light waiting times and congestion duration, and from the F-test to hogging behavior are very small (< 0.02) and, thus, indicate that they have a significant impact on the level of driving anger. In general, this study contributes to this field by using both self-reported data and in-cabin observations to study the ranking of incentive factors and their causal relationship with driving anger in a typical driving environment in China. Study results can be useful for traffic operation and management agencies in China to improve their level of service in order to effectively reduce road rage.

ACS Style

Lixin Yan; Dunyao Zhu; Chaozhong Wu; Ming Zhong; Ke Zheng. Ranking and Causal Relationship Analysis of Incentive Factors of Driving Anger: A Case Study from an On-Road Experiment in China. CICTP 2014 2014, 1 .

AMA Style

Lixin Yan, Dunyao Zhu, Chaozhong Wu, Ming Zhong, Ke Zheng. Ranking and Causal Relationship Analysis of Incentive Factors of Driving Anger: A Case Study from an On-Road Experiment in China. CICTP 2014. 2014; ():1.

Chicago/Turabian Style

Lixin Yan; Dunyao Zhu; Chaozhong Wu; Ming Zhong; Ke Zheng. 2014. "Ranking and Causal Relationship Analysis of Incentive Factors of Driving Anger: A Case Study from an On-Road Experiment in China." CICTP 2014 , no. : 1.