Zhong-ren Peng - Academia.edu (original) (raw)

Papers by Zhong-ren Peng

Frontiers of Earth Science, 2017

The minute-scale variations of fine particulate matter (PM 2.5) and carbon monoxide (CO) concentr... more The minute-scale variations of fine particulate matter (PM 2.5) and carbon monoxide (CO) concentrations near a road intersection in Shanghai, China were investigated to identify the influencing factors at three traffic periods. Measurement results demonstrate a synchronous variation of pollutant concentrations at the roadside and setbacks, and the average concentration of PM 2.5 at the roadside is 7% (44% for CO) higher than that of setbacks within 500 m of the intersection. The pollution level at traffic peak periods is found to be higher than that of off-peak periods, and the morning peak period is found to be the most polluted due to a large amount of diesel vehicles and unfavorable dispersion conditions. Partial least square regressions were constructed for influencing factors and setback pollutant concentrations, and results indicate that meteorological factors are the most significant, followed by setback distance from the intersection and traffic factors. CO is found to be sensitive to distance from the traffic source and vehicle type, and highly dependent on local traffic conditions, whereas PM 2.5 originates more from other sources and background levels. These findings demonstrate the importance of localized factors in understanding spatiotemporal patterns of air pollution at intersections, and support decision makers in roadside pollution management and control.

At road intersections, pedestrians are frequently exposed to high level of air pollutants, and th... more At road intersections, pedestrians are frequently exposed to high level of air pollutants, and the effective estimation is thus critical for relieving the health risk in such a microenvironment. Although a series of deterministic models have been used to estimate the concentrations of air pollutants at intersections recently, they are limited to the original purpose of most simulation models to simulate the average behavior of the dispersion process of vehicular pollutants at longer time scale such as daily and hourly. While pollutant levels can vary with traffic signal lights and instantaneous peaks occur between minutes, these models are thus confronting the trial of forecasting minute-scale pollution levels. Hence, this study first evaluates the performances of two typical air quality models, i.e., California Line Source Model with Queuing and Hot Spot Calculations (CAL3QHC) and California Line Source Model version 4 (CALINE4), in predictions of fine particulate matter (PM2.5) and carbon monoxide (CO) at 5-min scale. Results show that CAL3QHC generally performs well for 5-min predictions of both PM2.5 and CO compared with CALINE4. Besides, both models perform better at off-peak than peak periods, which can be attributed to the fluctuation of high traffic volumes as well as the more complex mechanical turbulence induced by passing vehicles in peaks. Furthermore, performances of both models are more related to wind speed particularly when predicting CO concentrations. When wind speed is less than 1m/s, both models will have better performances. The outputs of these findings demonstrate the potential of both models to be applied to forecast the real-time trends of air pollution as well as to capture the extreme values due to varied scenarios at road intersections.

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics, 2012

ABSTRACT The introduction of UAV into transportation offers a great number of challenges such as ... more ABSTRACT The introduction of UAV into transportation offers a great number of challenges such as how to utilize the collected vehicle data of different levels to obtain traffic variables. Meanwhile, different detection approaches may acquire different types and precisions of vehicle data, and the methods that will be chosen for each detection approach also may vary. The main objective of this paper is to compare the difference of several methods of calculating space mean speed (SMS), so as to provide guidance for SMS calculation and application based on various detection data of UAV. Two basic methods and three expanded methods that are possible to be used for UAV detection to calculate SMS of a road are discussed based on a dataset from NGSIM. Without considering the errors that may be caused by instability of UAV flight and video processing, differences among the methods are analyzed in the MatLAB software. The results of the two basic methods are of large difference, and the expanded methods used to estimate the SMS in various time periods will also generate different results. So when the results obtained by these methods are used for data fusion and other transportation applications, they should be assigned different weights. Some other results are obtained too, which may provide references for the traffic parameter extraction based on UAV detection, and the data fusion between the space mean speed from UAV detection and that from other traffic detection methods.

URISA Editorial …, 2000

URISA Journal s Wiggins, Deuker, Ferreira, Merry, Peng, Spear 51 The Dimensions of the Applicatio... more URISA Journal s Wiggins, Deuker, Ferreira, Merry, Peng, Spear 51 The Dimensions of the Application Challenge: Transportation Planning and Management Choices about transportation alternatives permeate our daily lives. We are accustomed to making quite sophisticated decisions ...

2009 IEEE/INFORMS International Conference on Service Operations, Logistics and Informatics

... case of high-speed rail system in Taiwan which showed that an optimal set of ... They also fo... more ... case of high-speed rail system in Taiwan which showed that an optimal set of ... They also formulated a multi-class mixed-equilibrium mathematical program to capture the route choice behaviors ... and his co-authors (2007) presented an on-line timetable for rescheduling method in ...

Land

Public health emergencies are characterized by significant uncertainty and robust transmission, b... more Public health emergencies are characterized by significant uncertainty and robust transmission, both of which will be exacerbated by population mobility, threatening urban security. Enhancing regional resilience in view of these risks is critical to the preservation of human lives and the stability of socio-economic development. Network resilience (NR) is widely accepted as a strategy for reducing the risk of vulnerability and maintaining regional sustainability. However, past assessments of it have not sufficiently focused on its spatial effect and have overlooked both its internal evolution characteristics and external threats which may affect its function and effectiveness. Therefore, we used the Yangtze River Delta Region (YRDR) as a case study and conceptualized an integrated framework to evaluate the spatial pattern and mechanisms of NR under the superposition of the COVID-19 pandemiv and major holidays. The results indicated that the topology of a population mobility network ...

Climatic Change, 2020

Adaptation has become the major approach to reduce the adverse effects of storm surge and sea-lev... more Adaptation has become the major approach to reduce the adverse effects of storm surge and sea-level rise. However, maladaptation can happen when adaptation actions unintentionally increase community vulnerability. To evaluate the adequacy and efficacy of adaptation policies under uncertain sea-level rise, this study presents an agent-based model by integrating the random nature of storm surges, private adaptation decisions, and real estate market valuation. We evaluated the evolving flood damage of different adaptation strategies under two bounding cases of real estate market change. Our model results quantitatively illustrate the accelerating damages of storm surges under climateinduced sea-level rise. A reform in flood insurance to risk-based rates with a means-tested voucher program and a government-subsidized "twice and out" buyout program could both substantially improve coastal resilience. However, community adaptation with a public seawall may deliver false risk perception to high-risk property owners and result in maladaptation when sea-level rise rate is high. The modeling approach developed in this study can be used as a policy analysis tool to measure the impacts of sea-level rise and the effectiveness of adaptation strategies in coastal communities.

Urban Planning International, 2017

Facing the problem of fast ageing, "Ageing-in-place" model has become a worldwide consensus strat... more Facing the problem of fast ageing, "Ageing-in-place" model has become a worldwide consensus strategy because it not only embodies the "Active Ageing" concept, but also reduces the burden of public finance. Retirement community is an important space to realize the "Active Ageing" and "Ageing-in-place" strategies. This article takes "The Villages" in Florida as a case to introduce the experience of "Active Adult Retirement Community" (AARC) in the United States. Compared to AARC, the domestic academic community and real estate industry are more concerned about "Continuous Care Retirement Community"(CCRC). This paper compares AARC and CCRC to explore the future model of China's retirement community construction. This study finds out that the elderly should be regarded as the mainstream population with active participation in social, economic, cultural, spiritual, civic and other affairs. Retirement communities should help them to build social networks through rich cultural and social activities to achieve physical and mental pleasure. The successful experience of AARC provides a positive and effective response to the upcoming wave of ageing in China.

Mitigation and Adaptation Strategies for Global Change, 2017

Coastal regions worldwide are during the process of rapid urban expansion. However, expanded urba... more Coastal regions worldwide are during the process of rapid urban expansion. However, expanded urban settlements in land-sea interfaces have been faced with unprecedented threats from climate change related hazards. Adaptation to coastal hazards has received increasing attention from city managers and planners. Adaptation and land management practices are largely informed by remote sensing and land change modeling. This paper establishes a framework that integrates land change analysis, coastal flooding, and sea level rise adaptation. Multilayer perceptron neural network, similarity learning, and binary logistic regression were applied to analyze spatiotemporal changes of residential, commercial, and other built-up areas in Bay County, Florida, USA. The prediction maps of 2030 were produced by three models under four policy scenarios that included the population relocation strategy. Validation results reveal that three models return overall acceptable accuracies but generate distinct landscape patterns. Predictions indicate that planned retreat of residents can greatly reduce urban vulnerability to sea level rise induced flooding. While managed realignment of the coast brings large benefits, the paper recommends different mixes of adaptation strategies for different parts of the globe, and advocates the application of reflective land use planning to foster a more disaster resilient coastal community.

Traffic monitoring with infrastructure-based sensors is effective and reliable for improving traf... more Traffic monitoring with infrastructure-based sensors is effective and reliable for improving traffic safety and traffic monitoring on high-volume roads, but not on low-volume roads. Low-volume roads in remote areas lack traffic monitoring sensors and thus traffic incidents are difficult to detect in a timely manner. Hence, this paper focused on low-volume road, and introduced Unmanned Aerial Vehicle (UAV) to detect traffic incident and analyzed its feasibility. Firstly, the research aim and definition of traffic incident were presented. Then, a numerical simulation method of using UAV to detect traffic incident was proposed, and a simulation case study with sensitivity analysis was implemented. Next, a UAV flight experiment was conducted. Finally, the cost-benefit analysis of using UAV to detect incident was given. The simulation results showed: (1) the theoretical UAV incident detection rate of the given scenario was 8.80%; (2) extending incident detection time, conducting UAV shuttling flight can increase incident detection rate significantly; and (3) some factors, such as UAV detection range, UAV flight speed and road incident occurrence rate, had little impact on incident detection result. The experiment and cost-benefit analysis showed that it’s cost efficient to use UAV to detect incident for low-volume road.

Road edges recognition is important for various applications in Intelligent Transport System . Th... more Road edges recognition is important for various applications in Intelligent Transport System . This paper focuses on extracting road edges from an image captured by a Unmanned Aerial Vehicle. Linear feature extraction is an important part of this job which is done by a proposed chain-code based algorithm. This paper brings forward a novel direction encoding scheme (DES) which improves encoding efficiency of digital straight lines and overcome drawbacks of Freeman encoding scheme (FES) successfully. DES also simplifies chain-code based line detecting methods from four stages to three. The new DES chain-code based criteria proposed can extract line segments in O(n) time, and curb errors due to digitalization effectively. A rotation of line (ROL) approach is employed for grouping line segments into much longer ones. Experimental results show that algorithm proposed in this paper works pretty well for road edges extraction

Journal of Central South University, 2014

Video processing is one challenge in collecting vehicle trajectories from unmanned aerial vehicle... more Video processing is one challenge in collecting vehicle trajectories from unmanned aerial vehicle (UAV) and road boundary estimation is one way to improve the video processing algorithms. However, current methods do not work well for low volume road, which is not well-marked and with noises such as vehicle tracks. A fusion-based method termed Dempster-Shafer-based road detection (DSRD) is proposed to address this issue. This method detects road boundary by combining multiple information sources using Dempster-Shafer theory (DST). In order to test the performance of the proposed method, two field experiments were conducted, one of which was on a highway partially covered by snow and another was on a dense traffic highway. The results show that DSRD is robust and accurate, whose detection rates are 100% and 99.8% compared with manual detection results. Then, DSRD is adopted to improve UAV video processing algorithm, and the vehicle detection and tracking rate are improved by 2.7% and 5.5%, respectively. Also, the computation time has decreased by 5% and 8.3% for two experiments, respectively.

Lecture Notes in Computer Science

Geospatial data sharing is an increasingly important subject as large amount of data is produced ... more Geospatial data sharing is an increasingly important subject as large amount of data is produced by variety of sources, stored in incompatible formats, and accessible through different GIS applications. Past efforts to enable sharing have produced standardized data format such as GML and data access protocols such as Web Feature Service (WFS). While these standards help enabling client applications to gain access to heterogeneous data stored in different formats from diverse sources, the usability of the access is limited due to the lack of data semantics encoded in the WFS feature types. Past research has used ontology languages to describe the semantics of geospatial data but ontology-based queries cannot be applied directly to legacy data stored in databases or shapefiles, or to feature data in WFS services. This paper presents a method to enable ontology query on spatial data available from WFS services and on data stored in databases. We do not create ontology instances explicitly and thus avoid the problems of data replication. Instead, user queries are rewritten to WFS getFeature requests and SQL queries to database. The method also has the benefits of being able to utilize existing tools of databases, WFS, and GML while enabling query based on ontology semantics.

International Conference on Transportation Engineering 2009, 2009

Giving priority to transit vehicles at urban intersections could improve transit operation and sc... more Giving priority to transit vehicles at urban intersections could improve transit operation and schedule reliability and attract ridership, it may also be an effective way to alleviate traffic congestion. This paper reports a new method to compute the cycle length at signalized intersections based on the principle of people oriented transportation systems. This is a departure from the current signal timing mechanism based on the average delay per vehicle, which is naturally in favor of private vehicles. Taking the minimum delay per person as the objective and based on the linear programming planning, the author developed a model calculating the optimal cycle length. Furthermore, the model was calibrated and validated in a case study. The result shows that, comparing with traditional control program, the model not only reduced delay per person but also diminished the delay per car dramatically at the same time. It demonstrated that giving priority to bus not only improve bus services but also improve all traffic at urban intersections.

Transportation Research Record: Journal of the Transportation Research Board, 2001

The use of breakeven analysis as a tool to assess the benefits of intelligent transportation syst... more The use of breakeven analysis as a tool to assess the benefits of intelligent transportation systems (ITS) at the system level in systemwide sketch planning is discussed. The breakeven analysis was developed on the basis of the SCRITS (SCReening for ITS) spreadsheet template and used data from Madison, Wisconsin, as a case study and provided considerable in sight into the magnitude of the potential benefits of different ITS programs. The analysis can help identify critical performance variables in the assessment of ITS benefits. Breakeven analysis coupled with sensitivity analysis can be used to identify and assess ITS projects for deployment in the ITS planning and programming process with limited data. It can be used to screen, prioritize, and select ITS projects among different ITS options. It can also be used to compare ITS projects in different geographic locations on the basis of different traffic data and breakeven points. The method is also useful in the identification of da...

2009 American Control Conference, 2009

Plug-in hybrid electric vehicles (PHEV) are widely received as a promising means of green mobilit... more Plug-in hybrid electric vehicles (PHEV) are widely received as a promising means of green mobility by utilizing more battery power. Recently, we have proposed a scheme of two-scale spatial-domain dynamic programming (DP) as a nearly global optimization approach to trip based optimal power management for PHEV through the combination with traffic data and trip modeling. Previously, the segment-wise power demand and SOC change was calculated through numerical integration based on the average speed and acceleration of the segment, and lookup tables were obtained. When more parameters are involved into power management, such as road grade and load change, such process becomes very tedious. In this paper, the spatial-domain DP is improved by calculating the power demand and SOC change in an analytical manner. The power demand is first calculated based on length, initial speed, acceleration, road grade, payload and wind of a road segment. The SOC change is then calculated for different PSR. An adjustable segment scheme used of analytical function is developed in order to improve the computation efficiency of the optimal power management without losing much of fuel economy. Simulation study shows that incorporating additional trip information such as road grade and predictable payload change into the optimization can significantly improve the fuel economy. The computational efficiency is also evaluated. The proposed method can greatly facilitate the development of optimal power management strategy for PHEV with multiple information inputs.

2013 21st International Conference on Geoinformatics, 2013

ABSTRACT This paper analyzes characteristics of population distribution and movements of the city... more ABSTRACT This paper analyzes characteristics of population distribution and movements of the city of Shenzhen in southern China by using mobile phone position data, and visualizes the distribution and movements of population in Shenzhen. Nowadays, positioning information of calling activity records of cell phones is more and more feasible with popularity of cell phones and development of the cell network. The tremendous advantages of positioning data in massive data samples, real-time and coverage guarantee it can be a significant supplement tool to monitor population dynamics. The experimental results display a vivid visual representation of population distribution and their movements through space and time. This paper's analytical method and results can potentially contribute to a better understanding of the surrounding city and further benefits to urban planning and management.

IFAC Proceedings Volumes, 2008

The plug-in hybrid electric vehicle (PHEV), utilizing more battery power, has become the next-gen... more The plug-in hybrid electric vehicle (PHEV), utilizing more battery power, has become the next-generation HEV with great promise of higher fuel economy. Global optimization charge-depletion power management would be desirable. However, this has so far been hampered due the a priori nature of the trip information and the almost prohibitive computational cost of global optimization techniques such as dynamic programming (DP). This situation can be changed by the current advancement of Intelligent Transportation Systems (ITS) based on the use of on-board GPS, GIS, real-time and historical traffic flow data and advanced traffic flow modeling techniques. In this paper, gas-kinetic base trip modeling approach was used for the highway portion trip and for the local road portion the traffic light sequences throughout the trip will be synchronized with the vehicle operation. Several trip models approaches were studied for a specific case. For DP based charge-depletion control of PHEV, the SOC is forced to drop to a specific terminal value at the final time of the trip. Simulation study has been performed on a hybrid SUV model from ADVISOR, for the different trip modeling approaches. The simulation results demonstrated significant improvement in fuel economy using DP based charge-depletion control compared to rule based control. The gas-kinetic based trip model for the highway portion can describe the dynamics of the traffic flow on highway with on/off ramps which may be missed by the model which used only the main road detectors data. The modeling approach shows a step to the more accurate trip model prediction which can be used for the power management of PHEV.

Frontiers of Earth Science, 2012

ABSTRACT In recent years, the increasing development of traffic information collection technology... more ABSTRACT In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemination system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g., identifying the real travel path), as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type (i.e., elevated or ground road) of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.