"Everything should be made as simple as possible, but not simpler."-Albert Einstein

Relative space-based GIS data model to analyze the group dynamics of moving objects

The relative motion of moving objects is an essential research topic in geographical information science (GIScience), which supports the innovation of geodatabases, spatial indexing, and geospatial services. This analysis is very popular in the domains of urban governance, transportation engineering, logistics and geospatial information services for individuals or industrials. Importantly, data models of moving objects are one of the most crucial approaches to support the analysis for dynamic relative motion between moving objects, even in the age of big data and cloud computing. Traditional geographic information systems (GIS) usually organize moving objects as point objects in absolute coordinated space. The derivation of relative motions among moving objects is not efficient because of the additional geo-computation of transformation between absolute space and relative space. Therefore, current GISs require an innovative approach to directly store, analyze and interpret the relative relationships of moving objects to support their efficient analysis. This paper proposes a relative space-based GIS data model of moving objects (RSMO) to construct, operate and analyze moving objects’ relationships and introduces two algorithms (relationship querying and relative relationship dynamic pattern matching) to derive and analyze the dynamic relationships of moving objects. Three scenarios (epidemic spreading, tracker finding, and motion-trend derivation of nearby crowds) are implemented to demonstrate the feasibility of the proposed model. The experimental results indicates the execution times of the proposed model are approximately 5–50% those of the absolute GIS method for the same function of these three scenarios. It’s better computational performance of the proposed model when analyzing the relative relationships of moving objects than the absolute methods in a famous commercial GIS software based on this experimental results. The proposed approach fills the gap of traditional GIS and shows promise for relative space-based geo-computation, analysis and service..

Automatic Identification System-Based Approach for Assessing the Near-Miss Collision Risk Dynamics of Ships in Ports

Vessel risk analysis is critical for safe ship navigation and maritime safety management. Near-miss collisions by ships comprise an significant risk, which may be complicated by factors, such as the ship conditions, waterway environment, and driving behavior of any ships encountered. Previous studies have rarely considered how to automatically and adaptively estimate the risk of near-miss collisions for different situations, particularly in port areas. In this paper, we propose an automatic identification system-based approach for adaptively calibrating near-miss collision risk model and assessing a ship’s near-miss collision risk by using the vessel’s speed and course patterns to obtain a robust estimate of the collision risk. Six measures are employed to determine the hierarchical geographical distribution of the near-miss collision risk for ships in port areas and to identify the high-risk areas. Some predicted high-risk areas were validated as official precautionary areas in the Xiamen Port area. All predicted areas may help the port administration to plan monitoring areas to ensure safe traffic flow in the port.

Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes

Understanding maritime network structure and traffic flow changes is a challenging task that must incorporate economic, energy, geopolitics, maritime transportation, and network sciences. The reported research examines whether there are linkages between oil price fluctuations, maritime network structure and traffic flow changes, and investigates whether tanker maritime network structure and traffic flow changes are driven by oil price fluctuations. This is essential knowledge for developing strategies energy policies. To address this, a systemsbased approach is introduced to construct a maritime transportation network based on trajectory data. The maritime network structure and traffic flow changes are derived from monthly transport. Supporting methods were then used to reveal two-way linkages, long-term balance relationships and shock responses attributable to oil price fluctuations, the maritime network structure and traffic flow changes. Evidence suggests that there are different two-way linkages between oil price fluctuations, maritime network structure and traffic flow changes in oil import- dependent and export-dependent countries. International crude oil price fluctuations contribute to maritime network structure changes for many of the countries examined, and showed rapid growth peaks in the second or third month. Our results have important policy implications for national tanker transportation strategies within the context of oil price fluctuations, suggesting diversification of import origins and export destinations as well as adjustment of shipping mode to cope with the supply shocks caused by oil price fluctuations.

Spatial heterogeneity in spatial interaction of human movements—Insights from large-scale mobile positioning data

Distance decay is a primary characteristic of spatial interaction in human movements, and it has been incorporated into many spatial interaction models. Existing approaches mainly rely on travel survey datasets to fit the frictional coefficient of distance decay. However, limited sample size and spatiotemporal resolution make the determination of the spatial interaction characteristic from a comprehensive view difficult. Recently, this situation has been reversed due to emerging large human trajectory datasets, which have stimulated a body of literatures to re-examine the traditional issue of distance decay. However, these studies only focused on distance decay from a global perspective and neglected the spatial non-stationarity of spatial interaction. This study aims to reveal the spatial heterogeneity of distance decay of human movements extracted from massive mobile phone location data from Shenzhen, China. The power law function is utilized to fit the distance decay coefficients for inflow and outflow of each spatial analysis unit. Then, geographically weighted regression is employed to quantify the relationship between distance decay coefficients and land use distribution and between distance decay coefficients and traffic facilities. Results show that considerable spatial non-stationarity appears in the distance decay of spatial interaction, and the regression coefficients indicate the spatial variations of the influence of land use and traffic facilities on distance decay across urban space. These findings provide an in-depth insight into the distance decay characteristics of human movements in a more microcosmic space..

Revealing the relationship of human convergence–divergence patterns and land use: A case study on Shenzhen City, China

Understanding the relationship between human mobility and land use has been a longstanding topic in multiple disciplines, including transport geography and urban planning. Recently, urban collective mobility patterns have become a hot research direction and has been explored at an unprecedented space–time scale due to the emerging big human tracking datasets (e.g., mobile phone data). However, only a few studies have comprehensively quantified the effects of land use on human mobility patterns while considering the influence of the scale of spatial analysis units. This study attempts to reinforce this knowledge by investigating urban human convergence–divergence patterns and their relationship with land use distribution characteristics at three popular types of spatial analysis units of human mobility studies (voronoi polygons, grid cells, and traffic analysis zones) using mobile phone data. A case study on Shenzhen, China is implemented, and results indicate that eight distinct convergence–divergence patterns could be extracted to describe urban collective mobility patterns despite the use of different types of spatial analysis unit. Moreover, the scale of spatial analysis units exerts a few effects on the quantification of the influence of land use distribution on human convergence–divergence patterns, but some common characteristics could be summarized from these discrepant results. The findings can help policy makers understand urban human mobility and can serve as a guide for urban management and planning.

Modeling of Structure Landmark for Indoor Pedestrian Localization

The decreasing of accumulative error is a key issue for various multi-sensor fusion-based indoor localization systems that employ pedestrian dead reckoning (PDR) to improve their localization performance. Current studies mainly use activity-based map matching (AMM) to prevent the accumulative error. However, it is vulnerable to mismatch problems, which are usually caused by the randomness of human activities. This paper proposes a structure landmark map matching-based indoor localization approach. Structure landmarks refer to special spatial structures (e.g., intersections, corridors, or corners), which are visually salient in a local environment. These landmarks are visually recognizable in indoor spaces because of their distinct shapes. This paper integrates visual and inertial information to recognize the structure landmarks by using a Bayesian classier. An algorithm is also proposed to realize indoor localization without prior knowledge of the initial location or the turning angles of people. This approach decreases the accumulative localization error of PDR by matching the detected structure landmarks to the ground-truth values. The experimental results showed that the identication accuracy of the structure landmark was about 90% and the matching accuracy was 92%. The mean off-line localization error was about 1.2 m. Compared with the AMM-based method, this approach is robust to the random turning activities of people and can realize indoor localization with a faster convergence speed.

Identifying stops from mobile phone location data by introducing uncertain segments

Identifying stops is a primary step in acquiring activity-related information from mobile phone location data to understand the activity patterns of individuals. However, signal jumps in mobile phone location data may create “fake moves,” which will generate fake activity patterns of “stops-and-moves.” These “fake moves” share similar spatiotemporal features with real short-distance moves, and the stops and moves of trajectories (SMoT), which is the most extensively used stop identification model, often fails to distinguish them when the dataset has coarse temporal resolution. This study proposes the stops, moves, and uncertainties of trajectories (SMUoT) model to address this issue by introducing uncertain segment analysis to distinguish “fake moves” and real short-distance moves. A real mobile phone location dataset collected in Shenzhen, China is used to evaluate the performance of SMUoT. We find that SMUoT improves the performance (i.e., 15 and 19% increase in accuracy and recall rate for a onehour temporal resolution dataset, respectively) of stop identification and exhibits high robustness to parameter settings. With a better reliability of “stops-and-moves” pattern identification, the proposed SMUoT can benefit various individual activity-related research based on mobile phone location data for many fields, such as urban planning, traffic analysis, and emergency management.

An Invisible Salient Landmark Approach to Locating Pedestrians for Predesigned Business Card Route of Pedestrian Navigation

Visual landmarks are important navigational aids for research into and design of applications for last mile pedestrian navigation, e.g., business card route of pedestrian navigation. The business card route is a route between a fixed origin (e.g., campus entrance) to a fixed destination (e.g., office). The changing characteristics and combinations of various sensors’ data in smartphones or navigation devices can be viewed as invisible salient landmarks for business card route of pedestrian navigation. However, the advantages of these invisible landmarks have not been fully utilized, despite the prevalence of GPS and digital maps. This paper presents an improvement to the Dempster–Shafer theory of evidence to find invisible landmarks along predesigned pedestrian routes, which can guide pedestrians by locating them without using digital maps. This approach is suitable for use as a “business card” route for newcomers to find their last mile destinations smoothly by following precollected sensor data along a target route. Experiments in real pedestrian navigation environments show that our proposed approach can sense the location of pedestrians automatically, both indoors and outdoors, and has smaller positioning errors than purely GPS and Wi-Fi positioning approaches in the study area. Consequently, the proposed methodology is appropriate to guide pedestrians to unfamiliar destinations, such as a room in a building or an exit from a park, with little dependency on geographical information.

A Visual-Based Approach for Indoor Radio Map Construction Using Smartphones

Localization of users in indoor spaces is a common issue in many applications. Among various technologies, a Wi-Fi fingerprinting based localization solution has attracted much attention, since it can be easily deployed using the existing off-the-shelf mobile devices and wireless networks. However, the collection of the Wi-Fi radio map is quite labor-intensive, which limits its potential for large-scale application. In this paper, a visual-based approach is proposed for the construction of a radio map in anonymous indoor environments. This approach collects multi-sensor data, e.g.,Wi-Fi signals, video frames, inertial readings, when people are walking in indoor environments with smartphones in their hands. Then, it spatially recovers the trajectories of people by using both visual and inertial information. Finally, it estimates the location of fingerprints from the trajectories and constructs a Wi-Fi radio map. Experiment results show that the average location error of the fingerprints is about 0.53 m. A weighted k-nearest neighbor method is also used to evaluate the constructed radio map. The average localization error is about 3.2 m, indicating that the quality of the constructed radio map is at the same level as those constructed by site surveying. However, this approach can greatly reduce the human labor cost, which increases the potential for applying it to large indoor environments..

Spatiotemporal model for assessing the stability of urban human convergence and divergence pattern

Understanding the stability of urban flows is critical for urban transportation, urban planning and public health. However, few studies have measured the stability of aggregate human convergence or divergence patterns. We propose a spatiotemporal model for assessing the stability of human convergence and divergence patterns. A mobile phone location data set obtained from Shenzhen, China, was used to assess the stability of daily human convergence and divergence patterns at three different spatial scales, i.e. points (cell phone towers), lines (bus lines) and areas (traffic analysis zones [TAZs]). Our analysis results demonstrated that the proposed model can identify points and bus lines with timedependent variations in stability, which is useful for delineating TAZs for transportation planning, or adjusting bus timetables and routes to meet the needs of bus riders. Comparisons of the results obtained from the proposed model and the widely used entropy measure indicated that the proposed model is suitable for assessing the differences in stability for various types of spatial analysis units, e.g. cell phone towers. Therefore, the proposed model is a useful alternative approach of measuring spatiotemporal stability of aggregate human convergence and divergence patterns, which can be derived from the space–time trajectories of moving objects.

An artificial bee colony-based multi-objective route planning algorithm for use in pedestrian navigation at night

Pedestrian navigation at night should differ from daytime navigation due to the psychological safety needs of pedestrians. For example, pedestrians may prefer better-illuminated walking environments, shorter travel distances, and greater numbers of pedestrian companions. Route selection at night is therefore a multiobjective optimization problem. However, multi-objective optimization problems are commonly solved by combining multiple objectives into a single weighted-sum objective function. This study extends the artificial bee colony (ABC) algorithm by modifying several strategies, including the representation of the solutions, the limited neighborhood search, and the Pareto front approximation method. The extended algorithm can be used to generate an optimal route set for pedestrians at night that considers travel distance, the illumination of the walking environment, and the number of pedestrian companions. We compare the proposed algorithm with the well-known Dijkstra shortest-path algorithm and discuss the stability, diversity, and dynamics of the generated solutions. Experiments within a study area confirm the effectiveness of the improved algorithm. This algorithm can also be applied to solving other multi-objective optimization problems.

Functionally critical locations in an urban transportation network:Identification and space–time analysis using taxi trajectories

This paper studies the space–time properties of locations that are critical to travel activities in an urban environment. Specifically, we analyze locations on the urban street network from the perspective of the distribution of people’s travel trajectories. We identify the intersections of an urban transportation network which are characterized by good connectivity, serving a high density of trip trajectories, and exhibiting multiple traversing patterns of trip trajectories as potential functionally critical network locations (FCNLs). A geospatial method is proposed to extract FCNLs from people’s moving trajectories based on the street network. Two groups of quantitative indices are introduced to measure the evolution of the spatial extent and temporal variation patterns of different criticality levels of FCNLs. A case study using taxi trajectory data from Wuhan, China has been implemented. The results show that the FCNLs are very powerful in uncovering the space–time traveling patterns of a particular population and studying the relationship between urban functional structures and people’s activities

A cube-based saliency detection method using integrated visual and spatial features

Purpose – The spatial feature is important for scene saliency detection. Scene-based visual saliency detection methods fail to incorporate 3D scene spatial aspects. This paper aims to propose a cube-based method to improve saliency detection through integrating visual and spatial features in 3D scenes.Design/methodology/approach – In the presented approach, a multiscale cube pyramid is used to organize the 3D image scene and mesh model. Each 3D cube in this pyramid represents a space unit similar to a pixel in the image saliency model multiscale image pyramid. In each 3D cube color, intensity and orientation features are extracted from the image and a quantitative concave– convex descriptor is extracted from the 3D space. A Gaussian filter is then used on this pyramid of cubes with an extended center-surround difference introduced to compute the cube-based 3D scene saliency.Findings – The precision-recall rate and receiver operating characteristic curve is used to evaluate the method and other state-of-art methods. The results show that the method used is better than traditional image-based methods, especially for 3D scenes.Originality/value – This paper presents a method that improves the image-based visual saliency model.

Spatiotemporal Critical Opportunity and Link Identification for Joint Participation Scheduling

Purpose – the choice sets for activities limited by a space-time prism should be investigated based on knowledge of the transportation network as well as of time-space constraints. To accumulate transportation knowledge for urban management, many cities have equipped their transportation networks with various sensors to collect plentiful video data and loop signals for future data mining. Beside this traditional knowledge, trajectory data collected by Global Positioning System (GPS)-equipped vehicles also provide much useful information for mining transportation network knowledge, such as traffic speeds in occupied links and the spatiotemporal frequency of often-used links. This kind of information can facilitate activity scheduling by identifying critical links. Therefore, this chapter proposes an approach which identifies critical links and opportunities for joint participation based on analysis of GPS-recorded taxi trajectories within the framework of time geography theory..

Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach

Advancements of information, communication and location-aware technologies have made collections of various passively generated datasets possible. These datasets provide new opportunities to understand human mobility patterns at a low cost and large scale. This study presents a home-based approach to understanding human mobility patterns based on a large mobile phone location dataset from Shenzhen, China. First, we estimate each individual’s ‘‘home’’ anchor point, and a modified standard distance (S0 D) is proposed to measure the spread of each individual’s activity space centered at this ‘‘home’’ anchor point. We then derive aggregate mobility patterns at mobile phone tower level to describe the distance distribution of S0 D for people who share the same ‘‘home’’ anchor point. A hierarchical clustering algorithm is performed and the spatial distributions of the...

Parametric Modeling of Visual Search Efficiency in Real Scenes

How should the efficiency of searching for real objects in real scenes be measured? Traditionally, when searching for artificial targets, e.g., letters or rectangles, among distractors, efficiency is measured by a reaction time (RT) × Set Size function. However, it is not clear whether the set size of real scenes is as effective a parameter for measuring search efficiency as the set size of artificial scenes. The present study investigated search efficiency in real scenes based on a combination of low-level features, e.g., visible size and target-flanker separation factors, and high-level features, e.g., category effect and target template. Visible size refers to the pixel number of visible parts of an object in a scene, whereas separation is defined as the sum of the flank distances from a target to the nearest distractors. During the experiment, observers searched for targets in various urban scenes, using pictures as the target templates. The results indicated that the effect of the set size in real scenes decreased according to the variances of other factors, e.g., visible size and separation. Increasing visible size and separation factors increased search efficiency. Based on these results, an RT × Visible Size × Separation function was proposed. These results suggest that the proposed function is a practicable predictor of search efficiency in real scenes.

What about people in pedestrian navigation?

Pedestrian navigation has become an important theoretical and practical research topic in many disciplines such as cartography, geographical information science, global and indoor positioning, spatial behavior, psychology, sociology, and neuroscience. Many research studies view pedestrian navigation using process-oriented and goal-directed approaches. However, this paper revisits people’s needs in pedestrian navigation and classifies their needs as three layers: physical sense layer, physiological safety layer, and mental satisfaction layer according to Maslow’s theory. This paper introduces a people-centric framework for pedestrian navigation theory based on these three layers and discusses theoretical challenges for meeting each layer of people’s needs. These challenging theories may represent promising and valuable research and promote usage of pedestrian navigation systems or devices in the future.

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

Vehicle routing optimization (VRO) designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard) complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW). Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of....

Impacts of high speed rail on railroad network accessibility in China

High speed rail (HSR) is changing the overall travel accessibility of cities in China. There have been a number of studies of high speed rail in China. However, detailed spatiotemporal accessibility pattern of cities affected by the operation of high speed rail in China has not been reported. This study takes a timetablebased accessibility evaluation approach to analyze the changes in travel time, travel cost, and distance accessibility for each of the four main stages of HSR development in China: no HSR service in Stage 1 before August 2008, several HSR lines in Stage 2 between August 2008 and July 2011, reduced operating speed of HSR trains in Stage 3 between August 2011 and November 2012, and addition of new HSR lines and reduction of ticket fares in Stage 4 between December 2012 and January 2013. In addition to the‘‘corridor effect’’ and the ‘‘center-diffusion’’ pattern, this paper investigates the impacts of HSR on changes in in-vehicle travel time and out-of-vehicle travel time with respect to the policy changes that reduced the operating speed of HSR trains, rearranged the train timetable, and lowered the ticket fare on HSR trains. ...

A multi-objective approach to scheduling joint participation with variable space and time preferences and opportunities

Activity scheduling supports activity-based analysis in travel demand management and promotes a potentially popular traveler assistance service. A multi-objective approach is proposed to schedule joint participation of multiple individuals, in which the candidate space–time opportunities for joint participation are identified by a concept of time-varying network-based prisms, and optimal opportunities for joint participation are determined by the non-dominated sorting genetic algorithm-II (NSGA-II) with four objectives (i) minimizing cost for congestion charges, (ii) maximizing participation desirability of time of day, (iii) minimizing total travel distance and (iv) time in the trips of multiple individuals…

Spatiotemporal analysis of critical transportation links based on time geographic concepts: a case study of critical bridges in Wuhan, China

Critical transportation infrastructure has been studied extensively in recent years. This paper presents a spatiotemporal analysis of critical transportation links based on time geographic concepts. With widespread adoption of information and communication technologies (ICT) and location-aware mobile devices, large tracking datasets have become readily available. This study uses a tracking dataset of approximately 12,000 taxis in Wuhan, China over 1 week to analyze spatiotemporal origin–destination (O–D) patterns of trips that use three critical bridges connecting the three districts of Wuchang, Hankou, and Hanyang separated by the Yangtze River and the Han River.We use the space–time prism concept to identify alternative space–time paths passing through different bridges that observe the spatial and temporal constraints between each O–D pair derived from the taxi trajectory data. This case study illustrates the feasibility and benefits of using the proposed time geographic approach to analyze spatiotemporal patterns of travel demands on the critical links and their alternative paths in a transportation system…

A Space-Time Efficiency Model for Optimizing Intra-Intersection Vehicle-Pedestrian Evacuation Movements

The effectiveness of an evacuation plan is a central concern of emergency management agencies. Methodologies for assessing and optimizing the space–time use efficiency of an evacuation plan have yet to be studied satisfactorily. To this end, this paper proposes an assessment metric and uses it for the optimization of evacuation plans. First, we define a space–time use efficiency metric on the basis of trajectories on road segments and intersections. The metric measures the usage of an evacuation network by supporting a trajectory-based analysis of the competing behaviors of vehicles and pedestrians in a hybrid pedestrian-vehicle simulation. Secondly, we present a two-tier hybrid multi-objective optimization algorithm to plan vehicle and pedestrian turning movement directions in an integrated road and building-interior network for the purpose of making decisions about evacuation plans.....

A proposed pedestrian waiting-time model for improving spaceetime use efficiency in stadium evacuation scenarios

Efficiency is a fundamental requirement in evacuation planning and operations. The “faster-is-slower” phenomenon in pedestrian evacuation has been observed and deemed a significant obstacle to evacuation efficiency. This paper thus focuses on two aspects of evacuation planning in the case of stadium evacuation. The first is to define a spaceetime use efficiency measure for evaluating the utility of both space and time resources. The second is to propose a pedestrian waiting-time model for directing evacuees to alleviate evacuation bottlenecks. An agent-based simulation approach was employed to test the proposed model in stadium evacuation scenarios…

A conflict-congestion model for pedestrian-vehicle mixed evacuation based on discrete particle swarm optimization algorithm

A simulation model based on temporal‐spatial conflict and congestion for pedestrian‐vehicle mixed evacuation has been investigated. Assuming certain spatial behaviors of individuals during emergency evacuation, a discrete particle swarm optimization with neighborhood learning factor algorithm has been proposed to solve this problem. The proposed algorithm introduces a neighborhood learning factor to simulate the sub‐group phenomenon among evacuees and to accelerate the evacuation process. The approach proposed here is compared with methods from the literatures, and simulation results indicate that the proposed algorithm achieves better evacuation efficiency while maintaining lower pedestrian‐vehicle conflict levels.

Hierarchical multi-objective evacuation routing in stadium using ant colony optimization approach

Evacuation planning is a fundamental requirement to ensure that most people can be evacuated to a safe area when a natural accident or an intentional act happens in a stadium environment. The central challenge in evacuation planning is to determine the optimum evacuation routing to safe areas. We describe the evacuation network within a stadium as a hierarchical directed network. We propose a multi-objective optimization approach to solve the evacuation routing problem on the basis of this hierarchical directed network. This problem involves three objectives that need to be achieved simultaneously, such as minimization of total evacuation time, minimization of total evacuation distance and minimal cumulative congestion degrees in an evacuation process. To solve this problem, we designed a modified ant colony optimization (ACO) algorithm, implemented it in the MATLAB software environment, and tested it using a stadium at the Wuhan Sports Center in China…

A multiobjective model for generating optimal landmark sequences in pedestrian navigation applications

Landmarks provide the most predominant navigational cue for pedestrian navigation.The choice and representation of landmarks require an optimal approach to meet the needs of pedestrians, for example, shorter distances, fewer turns, and easy confirmation. This article proposes a multiobjective model to generate optimal landmark sequences for pedestrian route instructions. This model offers a general approach to meet the diverse needs of pedestrians. A modified ant colony optimization (ACO) algorithm is used to implement the proposed model. This research determined the parameters of the modified ACO algorithm by testing the whole study area using various weight combinations…

A GIS data model for landmark-based pedestrian navigation

Landmarks provide the most predominant navigation cue for pedestrian navigation. Very few navigation data models in the geographical information science and transportation communities support modeling of landmarks and use of landmark-based route instructions for pedestrian navigation services. This article proposes a landmark based pedestrian navigation data model to fill this gap. This data model can model landmarks in several pedestrian navigation scenarios (buildings, open spaces, multimodal transportation systems, and urban streets). This article implements the proposed model in the ArcGIS software environment and demonstrates two typical pedestrian navigation scenarios: (1) a multimodal pedestrian navigation environment involving bus lines, parks, and indoor spaces and (2) a subway system in a metropolitan environment…

A Bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem

In this paper, a bi-level Voronoi diagram-based metaheuristic is introduced to solve the large-scale multi-depot vehicle routing problem (MDVRP). The upper level of the Voronoi diagram, derived from the depots, is used to allocate customers to depots. The lower level of the Voronoi diagram, derived from the customers, limits the search space of reallocating customers among the depots and rearranging the customers among the routes from each depot to its Voronoi neighbors. The results of numerical experiments clearly indicate the benefits of this proposed bi-level Voronoi diagram approach for solving very large-scale MDVRPs while balancing the solution quality and the computational demand.

A Voronoi neighborhood-based search heuristic for distance/capacity constrained very large vehicle routing problems

Local search heuristics for very large-scale vehicle routing problems (VRPs) have made remarkable advances in recent years. However, few local search heuristics have focused on the use of the spatial neighborhood in Voronoi diagrams to improve local searches. Based on the concept of a k-ring shaped Voronoi neighbor, we propose a Voronoi spatial neighborhood-based search heuristic and algorithm to solve very large-scale VRPs. In this algorithm, k-ring Voronoi neighbors of a customer are limited to building and updating local routings, and rearranging local routings with improper links. This algorithm was evaluated using four sets of benchmark tests for 200–8683 customers. Solutions were compared with specific examples in the literature, such as the one-depot VRP. This algorithm produced better solutions than some of the best known benchmark VRP solutions and requires less computational time. The algorithm outperformed previous methods used to solve very large-scale real-world distance constrained capacitated VRP.

Finding Reliable Shortest Paths in Road Networks Under Uncertainty

The aim of this study is to investigate the solution algorithm for solving the problem of determining reliable shortest paths in road networks with stochastic travel times. The availability of reliable shortest paths enables travelers, in the face of travel time uncertainty, to plan their trips with a pre-specified on-time arrival probability. In this study, the reliable shortest path between origin and destination nodes is determined using a multiple-criteria shortest path approach when link travel times follow normal distributions. The dominance conditions involved in such problems are established, thereby reducing the number of generated non-dominated paths during the search processes. Two solution algorithms, multi-criteria label-setting and A* algorithms, are proposed and their complexities analyzed. Computational results using large scale networks are presented. Numerical examples using data from a real-world advanced traveller information system is also given to illustrate the applicability of the solution algorithms in practice…

Reliable Space-Time Prisms Under Travel Time Uncertainty

Time geography is a powerful framework for analyzing human activities under various space–time constraints.At the core of time geography is the concept of the space–time prism, which delimits an individual’s potential activity locations in space and time. The classical space–time prism, however, admits only deterministic travel speeds and ignores the stochastic nature of travel environments. In this article, the classical space–time prism model is extended to congested road networks with travel time uncertainty. A reliable space–time prism is proposed to consider explicitly an individual’s on-time arrival probability concerns in the face of travel time uncertainty. The reliable space–time prism is defined as the set of space–time locations where an individual can participate in an activity and return to his or her destination with a given on-time arrival probability. To construct such a reliable space–time prism in a road network, a solution algorithm is developed. A case study using real-world traffic information is carried out to demonstrate the applicability of the proposed prism model. The results of the case study indicate that the proposed prism model can represent well individuals’ space–time taking into account various on-time arrival probability concerns.

FL-GrCCA: A granular computing classification algorithm based on fuzzy lattices

Defining a relation between granules and computing ever-changing granules are two important issues in granular computing. In view of this, this work proposes a partial order relation and lattice computing, respectively, for dealing with the aforementioned issues. A fuzzy lattice granular computing classification algorithm, or FL-GrCCA for short,is proposed here in the framework of fuzzy lattices. Algorithm FL-GrCCA computes a fuzzy inclusion relation between granules by using an inclusion measure function based on both a nonlinear positive valuation function, namely arctan, and an isomorphic mapping between lattices. Changeable classification granules are computed with a dilation operator using, conditionally, both the fuzzy inclusion relation between two granules and the size of a dilated granule. We compare the performance of FL-GrCCA with the performance of popular classification algorithms, including support vector machines (SVMs) and the fuzzy lattice reasoning (FLR) classifier, for a number of two-class problems and multiclass problems. Our computational experiments showed that FL-GrCCA can both speed up training and achieve comparable generalization performance.

Paper lists

2024. Antonio Moreno‑Munoz, Zhixiang Fang,· Francesco Ricciardelli, · Rachel Hu. naugural editorial of Discover Cities. Discover Cities, https://doi.org/10.1007/s44327-024-00001-x.

2024. Jiawen Long, Zhixiang Fang*, Lubin Wang. SK-MMFMNet: A Multi-dimensional Fusion Network of Remote Sensing Images and EEG signals for Multi-scale Marine Target Recognition. Information Fusion 108 (2024)，102402, doi: https://doi.org/10.1016/j.inffus.2024.102402

2024. Zhixiang Fang*, Rui Feng, Zhongyuan Wang. Spatiotemporal flow force model of source/sink human mobilities within city. Cities, 145 (2024) 104691.

2024. Xiping Yang, Junyi Li, Zhixiang Fang*, Hongfei Chen, Jiyuan LI, Zhiyuan Zhao. Influence of residential built environment on human mobility in Xining: A mobile phone data perspective. Travel Behaviour and Society, 34:100665.

2023. Fangli Guan, Zhixiang Fang*, Xucai Zhang, Haoyu Zhong, Haosheng Huang*. Using street-view panoramas to model the decision-making complexity of road intersections based on the passing branches during navigation. Computers, Environment and Urban Systems 2023, 103:101975

2023. Yuxuan Liu，Xiaoguang Lyu，Bo Yang，Zhixiang Fang*，Dejun Hu，Lei Shi，Bisheng Wu，Yong Tian，Enli Zhang，YuanChao Yang. Early triage of critically ill mushroom poisoning adult patients: a machine learning approach. JMIR Formative Research.

2023. Zhongyuan Wang, Zhixiang Fang*, Jianfeng Liang, Xiao Song. Estimating Ulva prolifera green tides of the Yellow Sea through ConvLSTM data fusion. Environmental Pollution. 2023，324：121350.

2023. Hongchu Yu，Qiang Meng，Zhixiang Fang，Jingxian Liu，Lei Xu. A review of ship collision risk assessment, hotspot detection and path planning for maritime traffic control in restricted waters. The Journal of Navigation (2023), 1–27. doi:10.1017/S03734633220006.

2023. Yue Hu, Zhixiang Fang*, Xinyan Zou, Haoyu Zhong, Lubin Wang. Two-stage tour route recommendation approach by integrating crowd dynamics derived from mobile tracking data. Applied Sciences 2023, 13, 596.

2023. Yu Zhang, Sheng Wu, Zhiyuan Zhao*, Xiping Yang, Zhixiang Fang. An urban crowd flow model integrating geographic characteristics. Scientific Reports 2023，volume 13, Article number: 1695.

2023. Zhiyuan Zhao, Wei Yao, Sheng Wu, Xiping Yang, Qunyong Wu, Zhixiang Fang*. Identifying the collaborative scheduling areas between ride-hailing and traditional taxi services based on vehicle trajectory data. Journal of Transport Geography 2023, 107, 103544

2022.Zhongyuan Wang, Zhixiang Fang*，Jianfeng Liang, Xiao Song. Assessment of global habitat suitability and risk of ocean green tides. Harmful Algae，2022，119，102324

2022.Zhixiang Fang*, Xiaofan Wang, Ying Zhuang, Xianglong Liu. Estimating the substitution of gasoline taxis by electric taxis in the era of green energy: A case study of Zhengzhou City. Geo-Spatial Information Science

2022.Zhixiang Fang*, Lupan Zhang, Meng Zheng. Transferability analysis of built environment variables for public transit ridership estimation in Wuhan, China. Transactions in Urban Data, Science and Technology. 2022，1-2，56-85

2022.Fangli Guan, Zhixiang Fang*，Lubin Wang, Xucai Zhang, Haoyu Zhong, Haosheng Huang*. Modelling people's perceived scene complexity of real-world environments using street-view panoramas and open geodata. ISPRS Journal of Photogrammetry and Remote Sensing. 186:315-331.

2022.Hongchu Yu, Alan Murray, Zhixiang Fang*, Guojun Peng, Solgi Mohammad, Weilong Zhang. Ship path optimization that accounts for geographical traffic characteristics to increase maritime port safety. IEEE Transactions on Intelligent Transportation Systems. 2022, 23(6): 5765-5776.

2022.Tianhong Zhao, Wei Tu*, Zhixiang Fang, Xiaofan Wang, Zhengdong Huang*, Shengwu Xiong, Meng Zheng. Optimizing living material delivery during the COVID-19 outbreak. IEEE Transactions on Intelligent Transportation Systems 2022，23(7)：6709-6719

2022.Zhixiang Fang*, Lubin Wang, Fan Yang, Fangli Guan. Landmark selection preferences of young students under orientation task within street environment. Journal of Location based services. 2021, 10.1080/17489725.2021.2006347.

2021.Hongchu Yu, Zhixiang Fang, Xiuju Fu, Jingxian Liu, Jinhai Chen. Literature Review on Emission Control based Voyage Optimization. Transportation Research Part D, 93, 102768

2021.Yang Zhou, Jean-Claude Thill, Yang Xu, Zhixiang Fang. Variability in individual home-work activity patterns. Journal of Transport Geography. 2021, 90,102901

2021.Xinyan Zou, Zhixiang Fang*, Shengwu Xiong*. A Discrete Particle Swarm Optimization Method for Allocating Supermarket Resources to Urban Residential Communities under the Epidemic Control. Applied Soft Computing. 2021, 98，106832.

2021.Hongchu Yu, Zhixiang Fang*, Alan T Murray, Guojun PENG. A direction-constrained space-time prism-based approach for quantifying possible multi-ships collision avoidance risk. IEEE Intelligent Transportation Systems Transactions.2021，22(1)：131-141

2021.Zhixiang Fang*, Yichen Wu*, Haoyu Zhong, Jianfeng Liang, Xiao Song. Revealing the impact of storm surge on taxis’ activity space: evidence from taxi and typhoon trajectory data. Environment and Planning B: Urban Analytics and City Science, Accepted

2021.Xiping Yang, Zhixiang Fang*, Yang Xu, Ling Yin, Junyi Li, Zhiyuan Zhao. Revealing temporal stay patterns in human mobility using large-scale mobile phone location data. Transactions in GIS. Accepted

2021.Meng Huang, Zhixiang Fang*, Haosheng Huang*, Tao Zhang, Robert Weibel. Dynamic optimization models for displaying outdoor advertisement at the right time and place. International Journal of Geographical Information Science. 10.1080/13658816.2020.1823396.

2021.Tianhong Zhao, Wei Tu*, Zhixiang Fang, Xiaofan Wang, Zhengdong Huang*, Shengwu Xiong, Meng Zheng. Optimizing living material delivery during the COVID-19 outbreak. IEEE Intelligent Transportation Systems Transactions. 2021，10.1109/TITS.2021.3061076

2020.Zhixiang Fang*, Fan Yang*, Fanli Guan, Mingxiang Feng, Yuxin Jiang. A data model organizing images semantically to support navigation computing for pedestrians in a relative space. Transactions in GIS, 2020，24(6), 1655-1680.

2020.Fangli Guan, Zhixiang Fang*, Tao Yu, Mingxiang Feng, Fan Yang. Deriving Relative Spatial Relations of Visual Salient Scene Areas from Continuous Street-View Panoramas. International Journal of Digital Earth, 2020, 13(12):1504-1531

2020.Qiuping Li*, Shaobo Zhong, Zhixiang Fang*, Lin Liu, Wei Tu, BiYu Chen. Optimizing Mixed Pedestrian-Vehicle Evacuation by Adaptive Network Reconfiguration. IEEE Intelligent Transportation Systems Transactions.2020, 21(3):1023-1033

2020. Shih-Lung Shaw, Mingxiang Feng, Guojun Peng, Zhixiang Fang. Time Efficiency Assessment of Ship Movements in Maritime Ports: A Case Study of Two Ports based on AIS Data. Journal of Transport Geography. 2020，86: 102751

2020. Ling Yin, Nan Lin, Xiaoqing Song, Shujiang Mei, Shih-Lung Shaw, Zhixiang Fang, Qinglan Li, Ye Li, Liang Mao. Space-Time Personalized Short Message Service (SMS) for Infectious Disease Control-Policies for Precise Public Health. Applied Geography, 114, 102103

2019. Mingxiang Feng, Shih-Lung Shaw*, Zhixiang Fang*, Hao Cheng. Relative space-based GIS data model to analyze the group dynamics of moving objects. ISPRS Journal of Photogrammetry and Remote Sensing. 2019, 153, 74-95.

2019. Xiping Yang, Zhixiang Fang*, Yang Xu, Ling Yin, junyi Li, Shiwei Lu. Spatial heterogeneity in spatial interaction of human movements—Insights from large-scale mobile positioning data. Journal of Transport Geography, 2019, 78: 29–40.

2019. Xiping Yang, Zhixiang Fang*, Ling Yin, junyi Li, Shiwei Lu, Zhiyuan Zhao. Revealing the relationship of human convergence–divergence dynamics and land use: A case study on Shenzhen City, China. Cities, 95, 102384

2019. Hongchu Yu, Zhixiang Fang*, Feng Lu, Alan T Murray, Hengcai Zhang, Peng Peng, Qiang Mei, Jinhai Chen. Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes. Applied Energy, 2019, 237: 390-403.

2019. Zhixiang Fang*, Hongchu Yu*, Ranxuan Ke, Shih-Lung Shaw and Guojun Peng. Automatic Identification System-based Approach to Assess Near Miss Collision Risk of Ship in Ports. IEEE Transactions on Intelligent Transportation Systems. 2019，20(2), 534-543.

2019. Meng Huang, Zhixiang Fang*, Shili Xiong, Tao Zhang. Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data. IEEE Access, 2019, 7(1), 30878-30889. DOI:10.1109/ACCESS.2019.2903277

2019. Zhongyuan Wang, Zhixiang Fang*, Yichen Wu, Jianfeng Liang, Xiao Song. Multi-source evidence data fusion approach to detect daily detecting the distribution and coverage of Ulva prolifera in the Yellow Sea, China. IEEE Access, DOI: 10.1109/ACCESS.2019.2936247.

2019. Qiuping Li*, Shaobo Zhong, Zhixiang Fang*, Lee D. Han, Lin Liu. Optimizing Mixed Pedestrian-Vehicle Evacuation by Adaptive Network Reconfiguration. IEEE Intelligent Transportation Systems Transactions. . DOI:10.1109/TITS.2019.2900754.

2019. Tao Liu, Xing Zhang*, Qingquan Li, Zhixiang Fang. Structure Landmark-based Indoor Pedestrian Localization. IEEE Access, 2019, 7(1):15654-15668

2019. Tao Liu, Xing Zhang*, Qingquan Li, Zhixiang Fang, Nadeem Tahir. An Accurate Visual-Inertial Integrated Geo-Tagging Method for Crowdsourcing-Based Indoor Localization. Remote Sensing, 11, 1912; doi:10.3390/rs11161912

2019. Yingzhi Cao, Yichen Wu*, Zhixiang Fang, Xiaojian Cui, Jianfeng Liang, Xiao Song. Spatiotemporal Patterns and Morphological Characteristics of Ulva prolifera Distribution in the Yellow Sea, China in 2016–2018. Remote Sensing, 2019, 11, 445; doi:10.3390/rs11040445.

2019. Zhiyuan Zhao, Shih-Lung Shaw, Ling Yin, Zhixiang Fang, Xiping Yang. Impacts of temporal sampling intervals on human mobility indicators using mobile phone location data. International Journal of Geographical Information Science. DOI: 10.1080/13658816.2019.1584805

2019. Rongxiang Su, Zhixiang Fang*. Review of studies on taxi mobility and e-hailing taxi service. Journal of Smart Cities. http://doi.org/10.18063/JSC.2019.01.002

2018. Zhixiang Fang, Hongchu Yu*, Feng Lu, Mingxiang Feng, Meng Huang. Maritime network dynamics before and after international events. Journal of Geographical Sciences, 2018, 28(7):937-956.

2018. Zhixiang Fang, Yuxin Jiang, Hong Xu*, Shih-Lung Shaw, Ling Li and Xuexian Geng. An invisible salient landmark approach to locating pedestrians for predesigned business card route of pedestrian navigation. Sensors, 2018, 18, 3164; doi:10.3390/s18093164.

2018. Zhixiang FANG*, Rongxiang Su and Huang Lian. Understanding the effect of an e-hailing app subsidy war on taxicab operation zones. Journal of Advanced Transportation, Article ID 7687852, https://doi.org/10.1155/2018/7687852

2018. Rongxiang Su, Zhixiang Fang*, Ningxin Luo, Jingwei Zhu. Understanding the dynamics of the pick-up and drop-off locations of taxicabs in the context of a subsidy war among e-hailing apps. Sustainability, 2018, 10, 1256; doi:10.3390/su10041256.

2018. Rongxiang Su, Zhixiang Fang*, Hong Xu*, Lian Huang .Uncovering Spatial Inequality in Taxi Services in the Context of a Subsidy War among E-hailing Apps. ISPRS International Journal of Geo-Information, 7(6), Article ID: 230, 10.3390/ijgi7060230.

2018. Xiping Yang, Zhixiang Fang*, Ling Yin, Junyi Li, Yang Zhou, Shiwei Lu. Understanding the spatial structure of urban human commuting using mobile phone location data: A case study of Shenzhen, China. Sustainability, 2018, 10, 1435; doi:10.3390/su10051435.

2018. Jingwei Zhu, Yang Xu*, Zhixiang Fang, Shih-Lung Shaw, Xingjian Liu. Geographic Prevalence and Mix of Regional Cuisines in Chinese Cities. ISPRS International Journal of Geo-Information, 2018, 7, 183; doi:10.3390/ijgi7050183.

2018. Zhiyuan Zhao, Ling Yin, Shih-Lung Shaw, Zhixiang Fang, Xiping Yang, Fan Zhang. Identifying stops from mobile phone location data by introducing uncertain segments. Transactions in GIS, 2018, 22(4): 958-974

2017. Zhixiang Fang*, Ling Li, Bijun Li*, Jingwei Zhu, Qingquan Li, Shengwu Xiong. An artificial bee colony-based multi-objective route planning algorithm for use in pedestrian navigation at night. International Journal of Geographical Information Science. 2017, 31(10): 2020-2044. 10.1080/13658816.2017.1346795.

2017. Zhixiang Fang*, Xiping Yang*, Yang Xu, Shih-Lung Shaw, Ling Yin. Spatiotemporal model for assessing the stability of urban human convergence and divergence patterns. International Journal of Geographical Information Science. 2017, 31(11):2119-2141. 10.1080/13658816.2017.1346256.

2017. Hongchu Yu, Zhixiang Fang*, Guojun Peng, Mingxiang Feng. Revealing the linkage network dynamic structures of Chinese maritime ports through Automatic Information System data. Sustainability. 9, 1913; doi:10.3390/su9101913

2017. Tao Liu, Xing Zhang *, Qingquan Li, Zhixiang Fang. A Visual-based Approach for Indoor Radio Map Construction Using Smartphone. Sensors, 2017, 17(8), 1790; doi:10.3390/s17081790.

2017. Shaobo Zhong, Zhixiang Fang, Min Zhu, Quanyi Huang. A geo-ontology based approach to decision-making in emergency management of meteorological disaster. Natural Hazards, DOI 10.1007/s11069-017-2979-z.

2017. Shiwei Lu*, Shih-Lung Shaw, Zhixiang Fang, Xirui Zhang, Ling Yin. Exploring the Effects of Sampling Locations for Calibrating the Huff Model Using Mobile Phone Location Data. Sustainability, 2017, 9, 159; doi:10.3390/su9010159.

2017. Shiwei Lu *, Zhixiang Fang, Xirui Zhang, Shih-Lung Shaw, Ling Yin, Zhiyuan Zhao, Xiping Yang. Understanding the Representativeness of Mobile Phone Location Data in Characterizing Human Mobility Indicators. ISPRS International Journal of Geo-Information, (ISPRS Int. J. Geo-Inf.) 2017, 6(1), 7; doi:10.3390/ijgi6010007.

2016. Xiping Yang, Zhixiang Fang*, Yang Xu*, Shi-Lung Shaw, Zhiyuan Zhao, Ling Yin, Tao Zhang and Yunong Lin. Understanding spatiotemporal patterns of human convergence and divergence using mobile phone location data. ISPRS International Journal of Geo-Information, 5, 177; doi:10.3390/ijgi5100177.

2016. Yang Xu, Shih-Lung Shaw *, Zhixiang Fang, Ling Yin. Estimating Potential Demand of Bicycle Trips From Mobile Phone Data–An Anchor-point Based Approach. ISPRS International Journal of Geo-Information, 5, 131; doi:10.3390/ijgi5080131.

2016. Tao LIU, Zhixiang FANG*,Qingzhou MAO*, Qingquan LI, Xing Zhang. A cube-based saliency detection method using integrated visual and spatial features. Sensor Review, 36(2):148-157.

2015. Zhixiang Fang, Shi-Lung Shaw, Wei TU, Qingquan LI. Spatiotemporal critical links and opportunities identification for joint participation scheduling. In: Mei-Po Kwan, Douglas Richardson, Donggen Wang and Chenghu Zhou (eds).Space-Time Integration in Geography and GIScience: Research Frontiers in the U.S. and China. Dordrecht: Springer. 109-126.

2015. Zhixiang FANG*, Qingquan Li & Shih-Lung Shaw. What about people in pedestrian navigation? Geo-spatial Information Science, 18(4):135-150.

2015. Yang Xu, Shih-Lung Shaw, Ziliang Zhao, Ling Yin, Feng Lu, Jie Chen, Zhixiang Fang, Qingquan Li. Another Tale of Two Cities — Understanding Human Activity Space using Actively Tracked Cellphone Location Data, Annals of the Association of American Geographers, 106(2):489-502.

2015. Ling Yin*, Qian Wang, Shih-Lung Shaw, Zhixiang FANG, Jinxing HU, Ye Tao, Wei Wang. Re-identification risk versus data utility for aggregated mobility research using mobile phone location data. PLOS ONE, 10(10): e0140589. doi:10.1371/journal.pone.0140589

2015. Rolla Jamil, S. Xiong, X. Kong, S. Zheng and Zhixiang FANG*. Pedestrian crossing patterns preference at a non-signalized crosswalk. Procedia Manufacturing. 3, 3353-3359, 10.1016/j.promfg.2015.07.496.

2015. Wei TU*, Qingquan LI*, Zhixiang FANG, Shih-lung Shaw, Baoding ZHOU, Xiaomeng CHANG. Optimizing the Locations of Electric Taxi Charging Stations: a Spatial-temporal Demand Coverage Approach. Transportation Research Part C: Emerging Technologies.65: 172–189

2015. Wei TU*, Qingquan LI, Zhixiang FANG, Baoding ZHOU. A novel spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing optimization with time constraints. ISPRS International Journal of Geo-Information. 2015, 4, 2019-2044; doi:10.3390/ijgi4042019

2015. Zhong Chen, Shengwu Xiong, Zhixiang Fang*, Ruiling Zhang, Xiangzhen Kong, Yi Rong. Topologically ordered feature extraction based on sparse group restricted boltzmann machines. Mathematical problems in engineering, Volume 2015, Article ID 267478. http://dx.doi.org/10.1155/2015/267478

2015. Xing ZHANG, Qingquan LI, Qin ZOU, Zhixiang FANG, Baoding ZHOU. Parametric Modeling of Visual Search Efficiency in Real Scenes, PLOS ONE, 10.1371/journal.pone.0128545

2015. Rolla Jamil Almodfer, Shengwu Xiong, Zhixiang Fang*, Xiangzhen Kong, Senwen Zheng. Quantitative Analysis of Lane-Based Pedestrian-Vehicle Conflict at a Non-Signalized Marked Crosswalk. Transportation Research Part F: Traffic Psychology and Behaviour, 10.1016/j.trf.2015.07.004.

2015. Yang XU, Shih-Lung Shaw*, Ziliang Zhao, Ling Yin, Zhixiang Fang, Qingquan LI. Understanding aggregate human mobility patterns using passive mobile phone location data- a home-based approach. Transportation, 42(2):625-646.

2015. Yang ZHOU, Zhixiang Fang*, Jean-Claude Thill, Qingquan Li, Yuguang Li. Functionally critical locations in an urban transportation network: Identification and space-time analysis using taxi trajectories. Computers, Environment and Urban Systems,52, 34–47.

2015. Zhong Chen, Shengwu Xiong, Qingzhou Mao, Zhixiang Fang and Xiaohan Yu. An improved saliency detection approach for Flying Apsaras in the Dunhuang Grotto Murals, China. Advances in Multimedia, Volume 2015 (2015), Article ID 625915, 11 pages, http://dx.doi.org/10.1155/2015/625915

2014. Xing Zhang, Qingquan LI*, Zhixiang FANG*, Shiwei LU, Shih-Lung Shaw. An assessment method for landmark recognition time in real scenes. Journal of environmental psychology. 2014, 40: 206-217.

2014. Zhong Chen, Shengwu Xiong, Zhixiang FANG*, Qingquan LI, Baolin Wang, Qin Zou. A kernel support vector machine-based feature selection approach for recognizing Flying Apsaras' streamers in the Dunhuang Grotto Murals, China. Pattern Recognition Letters, 2014,49, 107-113.

2014. Shih-Lung SHAW, Zhixiang FANG*, Shiwei LU, RanTAO. Impacts of the High Speed Rail on Railroad Network Accessibility in China. Journal of Transport Geography. 2014, 40, 112-123.

2014. Wei TU, Zhixiang Fang*, Qingquan LI, Shih-Lung SHAW, BiYu CHEN. A Bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review.2014, 61, 84-97

2014. Xinlu Zong*, Shengwu Xiong, Zhixiang Fang*. A conflict-congestion model for pedestrian-vehicle mixed evacuation based on discrete particle swarm optimization algorithm. Computers & Operations Research, 2014, 44, 1-12.

2014. ZhongBo Hu, ShengWu Xiong, QingHua Su, ZhiXiang Fang. Finite Markov Chain Analysis of Differential Evolution. Journal of Computational and Applied Mathematics. 2014,121-134.

2014. Zhongbo Hu, Shengwu Xiong, Zhixiang Fang and Qinghua Su. A Convergent Differential Evolution Algorithm with Hidden Adaptation Selection for Engineering Optimization. Mathematical Problems in Engineering. volume 2014, Article ID 135653, http://dx.doi.org/10.1155/2014/135652

2013. Zhixiang FANG, Qiuping Li, Qingquan Li, Lee D. Han, Shih-Lung Shaw. A space–time efficiency model for optimizing intra-intersection vehicle–pedestrian evacuation movements. Transportation Research Part C: Emerging Technologies,31, 112-130.

2013. Zhixiang FANG, Wei TU,Qingquan LI, Shih-Lung SHAW, Shunqing CHEN, BiYu CHEN. A Voronoi Neighborhood-based Search Heuristic for Distance/Capacity Constrained Very-Large Vehicle Routing Problems. International Journal of Geographical Information Science. 27(4), 741-764

2013. Bi Yu CHEN*, Qingquan LI, Donggen WANG, Shih-Lung SHAW, William H.K. LAM, Hui YUAN and Zhixiang FANG*, 2013, Reliable Space-time Prisms under Travel Time Uncertainty. Annals of the Association of American Geographers, 103(6):1502-1521.

2013. Chen, B., Lam, W., Sumalee, A., Li, Q., Shao, H. and Fang, Z.. Finding reliable shortest paths in road networks under uncertainty. Networks & Spatial Economics. 13(2): 123-148

Jialiang Kou, Shengwu Xiong *, Zhixiang Fang, Xinlu Zong, Zhong Chen. Multiobjective Optimization of Evacuation Routes in Stadium Using Superposed Potential Field Network Based ACO. Computational Intelligence and Neuroscience，Volume 2013 (2013), Article ID 369016, 11 pages, http://dx.doi.org/10.1155/2013/369016.

2012. Zhixiang FANG, Shih-Lung SHAW, Wei TU, Qingquan LI, Yuguang LI. Spatiotemporal analysis of critical transportation links based on time geographic concepts: a case study of critical bridges in Wuhan, China. Journal of Transport Geography. 2012, 23:44-59.

2012. Zhixiang FANG, Qingquan Li, Xing Zhang and Shih-Lung Shaw. A GIS data model for landmark-based pedestrian navigation. International Journal of Geographical Information Science. 2012, 26:5, 817-838

2011. Zhixiang FANG, Qingquan LI, Qiuping LI, Lee D. Han, Dan Wang. A Proposed Pedestrian Waiting-Time Model for Improving Space-Time Use Efficiency in Stadium Evacuation Scenarios. Building and Environment, 2011, 46(9): 1774-1784.

2011. Zhixiang Fang, Qingquan Li and Xing Zhang. A multiobjective model for generating optimal landmark sequences in pedestrian navigation applications. International Journal of Geographical Information Science. 2011, 25(5):785-805.

2011. Zhixiang Fang, Wei Tu, Qingquan Li, Qiuping Li. A multi-objective approach to scheduling joint participation with variable space and time preferences and opportunities. Journal of Transport Geography, 19(4):623-634.

2011. Zhixiang Fang,Xinlu Zong,Qingquan LI, Qiuping Li , Shengwu Xiong. Hierarchical multi-objective evacuation routing in stadium using ant colony optimization approach. Journal of Transport Geography. 2011, 19(3): 443–451.

2011. Hongbing Liu, Shengwu Xiong, Zhixiang Fang. FL-GrCCA: A granular computing classification algorithm based on fuzzy lattices. Computers and Mathematics with Applications, 61(1), 138-147.

2010. Zhixiang Fang, Shih-Lung Shaw and Qingquan Li. 2010. A sensitive indicator of regional space–time accessibility. Annals of GIS, 16: 3, 155- 164.

2021. 方志祥*.人群动态的观测理论及其未来发展思考.地球信息科学学报, 2021,23(9): 1527-1536.

2021. 张宇,吴升,赵志远,杨喜平,方志祥.顾及相似用户特征的个人位置预测算法. 武汉大学学报·信息科学版.已录用

2021. 张星,林静,李清泉,刘涛,方志祥. 结合感知哈希与空间约束的室内连续视觉定位方法.测绘学报. 2021, 50(12): 1639-1649

2021. 方志祥, 裴韬, 尹凌. “全球新型冠状病毒肺炎(COVID-19)疫情动态的时空建模与可视化决策分析”专辑导言[J]. 地球信息科学学报, 2021, 23(2): 187-187.

2021. 王晓凡,方志祥,仲浩宇,邹欣妍. 传染病防控下的市民慢性病药品购买周期优化方法. 地球信息科学学报. 2021,23(2):307-317.

2021. 方志祥, 姜宇昕, 管昉立. 融合可视与不可视地标的行人相对定位方法. 武汉大学学报·信息科学版, 46(5)

2021. 徐虹,王禄斌*,方志祥,何明辉,侯学成,左亮,熊策,龚毅宇,庞晴霖,张涵,孙树藤,娜迪热.艾麦尔. 街景影像区域匹配下的城市建筑风格地图生成方法. 武汉大学学报·信息科学版. 46(5)

2021.张星,刘涛,李清泉,孙龙培,方志祥. 一种视觉与惯性协同的室内多行人目标定位方法. 武汉大学学报·信息科学版. 46(5)

2020. 方志祥. 公共卫生与安全应急视角下人群动态的观测思考与挑战. 武汉大学学报·信息科学版. 2020,45（12）：1847-1856.

2020. 方志祥,仲浩宇,邹欣妍. 轨迹延续性与影像特征相似性结合的城市道路提取.测绘学报. 2020, 49(12): 1554-1563

2020. 周亚娟,赵志远,吴升,方志祥,陈佐旗. 基于大规模手机位置数据的城市潜在自行车出行需求评估——以上海市为例. 地球信息科学学报. 2020, 22(6):1282-1293

2020. 方志祥, 倪雅倩, 黄守倩.顾及上网行为特征的手机用户停留行为预测方法[J].地球信息科学学报,2020,22(1):136-144.

2020. 方志祥, 黄守倩, 苏荣祥, 肖和平. 高速公路多源数据融合下的层次拥堵区间探测方法. 武汉大学学报·信息科学版 2020,45(5): 682-690.

2020. 冯明翔,方志祥*, 路雄博, 谢泽丰, 熊盛武, 郑猛. 交通分析区尺度上的新型冠状肺炎时空扩散推估方法：以武汉市为例. 武汉大学学报·信息科学版, 2020, 45(5):651-657

2020. 刘涛,李清泉,方志祥,张星. 一种室内位置指纹数据库构建方法, 测绘科学, 2020,45(4):149-155

2020. 涂伟, 曹劲舟, 高琦丽, 曹瑞, 方志祥, 乐阳, 李清泉. 融合多源时空大数据感知城市动态[J]. 武汉大学学报·信息科学版, 2020, 45(12): 1875-1883.

2020. 刘涛,李清泉,方志祥,张星. 一种室内位置指纹数据库构建方法, 测绘科学, 2020,45(4):149-155

2019.倪文强, 方志祥*, 李灵. 图像显著度和信息量均衡的地标链生成方法.测绘地理信息，2019,44(6), 6-10

2019.袁淑君. 乘车软件应用前后出租车寻客路径偏好分析. 测绘地理信息, 2019, 44(3):94-98

2019.孙龙培, 张星, 李清泉, 刘涛,方志祥.单目视觉的室内多行人目标连续定位方法，测绘科学，2019,44(12):95-101,133

2018. 方志祥, 徐虹*, 萧世伦, 李清泉, 袁淑君, 李灵. 绝对空间定位到相对空间感知的行人导航研究趋势.武汉大学学报.信息科学版，2018，43(12), 2173-2182.

2018. 方志祥,余红楚,黄守倩.海洋运输网络研究进展与趋势探讨[J].地球信息科学学报,2018,20(5):554-563.

2018. 余红楚,方志祥*,陆锋,等.重要经济发展区域间海运网络时空演变特性分析[J].地球信息科学学报, 2018,20(5): 582- 592

2018. 杨喜平, 方志祥*. 2018. 移动定位大数据视角下的人群移动模式及城市空间结构研究进展[J]. 地理科学进展, 37 (7): 880- 889.

2018. 朱菁玮,方志祥,杨喜平,等.城市邻近基站间人群流动时空变化同步性分析[J].地球信息科学学报,2018,20(6): 844-853

2018. 杨喜平,方志祥*,尹凌.城市空间结构要素与人群聚散稳定性的关联性探索[J].地球信息科学学报,2018,20(6):791-798.

2018. 赵志远, 尹凌, 方志祥*, 萧世伦, 杨喜平. 轨迹数据的时间采样间隔对停留识别和出行网络构建的影响, 武汉大学学报•信息科学版.2018, 43(8):1152-1158.

2018. 董智青，方志祥，杨喜平，李清泉. 深圳市出租车服务能力时空分析.测绘地理信息，43(2): 105-109

2017.刘涛, 张星, 李清泉, 方志祥, 李秋萍. 一种运动恢复结构和航位推算结合的室内行人视觉定位方法, 地球信息科学学报 , 2017, 19 (6): 744- 753

2017.方志祥,于冲,张韬,等.手机用户上网时段的混合Markov预测方法.地球信息科学学报, 2017,19(8):1019-1025

2017.方志祥, 倪雅倩, 张韬, 冯明翔, 于冲. 利用终端位置时空转移概率预测通讯基站服务用户规模. 地球信息科学学报，2017, 19(6):772-781

2017.方志祥, 罗浩, 李灵. 基于有限状态自动机的行人导航状态匹配算法. 测绘学报，2017, 46(3):371-380.

2017. 杨喜平, 方志祥*, 萧世伦, 尹凌. 顾及手机基站分布的核密度估计城市人群时空停留分布. 武汉大学学报•信息科学版. 2017, 42(1)：49-55

2017. 刘涛，张星*.李清泉，方志祥， 顾及地标可视性的室内导航路径优化算法, 武汉大学学报•信息科学版. 2017, 42(1):43-48.

2016. 宋晓晴, 方志祥*,尹凌, 刘立寒, 杨喜平, 萧世伦. 一种基于IC卡综合换乘信息的公交乘客上车站点推算方法. 地球信息科学学报, 18(8): 1060-1068.

2016. 罗浩，方志祥，萧世伦. 基于谷歌眼镜传感器的曲线拟合计步算法. 计算机工程与应用, 已接受待刊.

2016. 刘涛，李清泉，方志祥，张星*. 顾及地标可视性的室内导航路径优化算法, 武汉大学学报•信息科学版. 已接受待刊.

2016.鲁仕维, 方志祥，萧世伦，张希瑞，尹淩.城市群体移动模式研究中空间尺度影响的定量分析.武汉大学学报•信息科学版. 41(9):1199-1204.

2016. 周洋，方志祥，李清泉，郭善昕. 基于经验约束规则和证据理论的出租车异常轨迹检测，武汉大学学报•信息科学版. 41(6):797-802.

2016. 杨喜平, 方志祥, 赵志远, 萧世伦, 尹凌. 城市人群聚集消散时空模式探索分析——以深圳为例. 地球信息科学学报, 18(4):486-492.

2015. 刘立寒, 方志祥*, 萧世伦, 尹凌. 带源节点的快速社区发现算法. 计算机工程与应用. 已在线出版.

2015. 张希瑞，方志祥*，李清泉，鲁仕维. 基于浮动车数据的城市道路通行能力时空分异特征研究.地球信息科学学报, 17(3):336-343.

2015. 徐金垒，方志祥*，萧世伦，尹淩；城市海量手机用户停留时空分异分析——以深圳市为例，地球信息科学学报, 17(1):1-9.

2015. 张华兵，方志祥，郭翌寒，武捷，刘春平. 基于实景显著性的行人导航数据模型, 测绘地理信息，40(3): 57-59.

2014. 萧世伦，方志祥*. 从时空GIS视野来定量分析人类行为的思考[J]. 武汉大学学报.信息科学版. 2014, 39(6): 667-670.

2014. 涂伟，李清泉，方志祥. 基于网络Voronoi图的大规模多仓库物流配送路径优化[J]. 测绘学报.43(10):1075-1082.

2013. 涂伟，李清泉，方志祥. 一种大规模车辆路径问题的启发式算法[J]. 武汉大学学报•信息科学版. V38(3): 307-310.

2013. 张星, 李清泉, 方志祥,黄玲.顾及地标与道路分支的行人导航路径选择算法，武汉大学学报信息科学版，38(10):1239-1242.

2012. 李清泉, 萧世伦, 方志祥, 杨必胜 等著. 交通地理信息系统技术与前沿发展.科学出版社.

2012. 涂伟，方志祥*，李清泉，鲁仕维. 基于Voronoi 邻近的大规模物流车辆路径优化算法 [J]. 地球信息科学学报. V14(6): 781-787

2012.宗欣露，熊盛武，方志祥.基于蚁群算法的人车混合疏散优化及混合比例分析，系统工程理论与实践.32(7): 1610-1617

2011.李清泉,李秋萍,方志祥.一种基于时空拥挤度的应急疏散路径优化方法.测绘学报, 40(4): 517-523.

2010. 方志祥，李清泉，萧世伦. 利用时间地理的的位置相关时空可达性表达方法.武汉大学学报信息科学版,35(9),1091-1095.

2010. 张星，李清泉，方志祥.面向行人导航的地标链生成方法.武汉大学学报信息科学版,35(10),1240-1244.

2008. 方志祥，宋莺. 嵌入式环境基于实时交通信息的多层次路径规划算法.武汉大学学报信息科学版，33(4):397-401

2005. 方志祥,李清泉,熊盛武. GIS矩形网格中任意多边形裁剪算法.武汉理工大学学报(交通科学与工程版) 29(5):685-688

2004. 方志祥,李清泉.基于Mobile Agent技术的空间信息移动服务,测绘学报33(4):328-334.

2003.李必军, 方志祥, 任娟.从激光扫描数据中进行建筑物特征提取研究.武汉大学学报信息科学版,28(1):65-70.