liyuan zhao - Academia.edu (original) (raw)
Papers by liyuan zhao
Lecture Notes in Geoinformation and Cartography
This study describes an integrated platform model for assessing the interaction among land use, t... more This study describes an integrated platform model for assessing the interaction among land use, transportation, and mobile source emissions. In the proposed integrated framework, LandSys, a home grown land use model, produces land use change over the dimensions of space and time, allocates land use forecast results in terms of household and employment at the traffic analysis zone (TAZ) level, and feeds these socioeconomic data into a travel demand model, the Florida Standard Urban Transportation Model Structure (FSUTMS). Then, the produced travel time and accessibility index by FSUTMS are fed back into LandSys to quantify the emissions. Finally, the emissions from standalone FSUTMS and integrated framework are compared to quantify the air quality benefits of the land use development from the integrated land use and transportation model. In the case application of Orange County, Florida in the United States in 2000, 2012 and 2025, five major indicators of transportation networks were used: link saturation in the transportation network, overall vehicle miles traveled (VMT), vehicle hours traveled (VHT), mobile source greenhouse gas emissions and fuel consumption. The results show that the values of the five indicators were lower when utilizing the integrated platform than was predicted by the standalone FSUTMS models, which demonstrates that the integrated platform achieved greater effectiveness in environmental improvements by considering the interactions between land use and transportation.
Natural Hazards, 2016
Sea level rise (SLR), as a likely outcome of climate change, threatens coastal communities throug... more Sea level rise (SLR), as a likely outcome of climate change, threatens coastal communities through intensified storm surge, strong wind, flooding, and other extreme weather events. While social vulnerability to SLR is receiving overwhelming attention from research communities, studies on the business impacts of SLR are much less developed. In this study, an innovative framework of integrated business vulnerability is developed for environmental hazards (e.g., SLR) and is validated by a case study of Bay County, Florida. First, the model establishes a composite business vulnerability index (BVI) by incorporating business characteristics, infrastructure factors, and other indicators based on existing literature results. Second, it identifies impacted business indicators and how they will change with the projected SLR. To account for climate change uncertainty, floodplains are generated under three SLR levels (0, 0.2, and 0.9 m). Finally, this study uses a GIS-based methodology to combine physical and business vulnerabilities to investigate overall susceptibility and how this changes with SLR. Two important findings are identified. First, business vulnerability to flooding will be escalated substantially by SLR. Considerable amount of areas, businesses, and road networks would be exposed to highest flood risk zones due to SLR. Second, highest flood risk zones do not necessarily intersect with those areas of high BVI. The results can help local governments better allocate financial and manpower resources and assist hazard mitigation teams, urban planners, and city managers in steering business development away from high-risk regions due to SLR.
International Conference on Transportation Engineering 2009, 2009
This paper proposes a capacity origin destination (OD) assignment model, and the model's algo... more This paper proposes a capacity origin destination (OD) assignment model, and the model's algorithm is given. Then the optimal route choice optimal model is established according to the principle of minimize cost. The corresponding algorithm is given. The final part is the numerical experiment.
International journal of Environmental Science and Technology
Disruptions of vulnerable links in transportation networks have been widely recognized as a serio... more Disruptions of vulnerable links in transportation networks have been widely recognized as a serious safety issue, generating both traffic congestion and significant traffic emissions. This paper aims to consolidate a proposed land-use adaptation (LUA) strategy into transportation vulnerability assessment, quantitatively exploring the question about how to optimize spatial patterns in longterm land-use planning to improve network reliability, protect existing vulnerable links and critical locations, and reduce traffic emissions. To mitigate regional network vulnerability, the LUA model employs the bid-rent theory to describe the agents' behaviors in the land market. Using the genetic and frank-wolf algorithms, this paper analyzes the relationship between link vulnerability and geographical distribution of land-use patterns. The amount of trafficrelated CO emissions is used to evaluate the environmental impacts of the vulnerable link closure. The case study indicates that the long-term LUA strategy at land-cell level effectively reduces road network vulnerability, significantly improves the performance of existing urban road systems, and reduces traffic emissions. The model results also show that road networks tend to become more vulnerable with an increase in travel demand. Furthermore, without considering accessibility reduction caused by vulnerable transportation links, the land-use development is more likely to make the existing vulnerable links more susceptible. The proposed LUA methodology could allow urban system managers and planners to take proactive actions, thereby mitigating negative environmental impacts caused by network disruptions rather than being obliged to react to them.
Lecture Notes in Computer Science, 2008
The public transit route choosing problem is the key technology of public transit passenger infor... more The public transit route choosing problem is the key technology of public transit passenger information system. Considering travel time variety caused by uncertainty traffic congestion condition, firstly this paper designs the least transfer times algorithm and the K shortest transit paths algorithm in the stochastic transit network. On the basis of travel psychology analysis, transfer times, travel time and cost of each transit path plan are taken into account. By changing link travel time reliability, the algorithms generate different K shortest transit path plans under different traffic conditions. Computational experiments demonstrate the efficiency of the model and algorithm in stochastic transit network.
Transportation Research Record: Journal of the Transportation Research Board, 2010
The purpose of this paper is to develop a bilevel integrated dynamic model—a combination of an up... more The purpose of this paper is to develop a bilevel integrated dynamic model—a combination of an upper land use allocation model and a lower transportation model—to quantify the interaction between different land use allocation strategies and the transportation system. To manage the dynamic land use change in spatial and temporal dimensions, the upper-level model uses cellular automata to capture the spatial attributes of land use change, whereas the bid–rent agent model focuses on household location choice behavior. The cell-based land allocation strategy and residential location choice generated in the upper-level model are fed into the lower-level model to reflect new transportation demand, travel cost, and transportation accessibility. Then, the travel cost and transportation accessibility produced in the lower-level model are fed back into the upper-level model. To optimize land use allocation strategy, a combination of a genetic algorithm and a Frank–Wolfe algorithm is used to m...
Journal of Urban Planning and Development, 2014
AbstractThis paper extends the previous LandSys I to introduce artificial neural networks (ANNs) ... more AbstractThis paper extends the previous LandSys I to introduce artificial neural networks (ANNs) into the framework of cellular automata (CA), multiagents, and geographic information system (GIS) to forecast land-use change at the grid cell level (50×50 m). In the model, the temporal and spatial interactions of land-use change are described by CA where transition rules are defined by ANNs to reduce the tedious work of parameter calibration in LandSys I. Compared with LandSys I, an improved multiagent model in LandSys II captures both zoning policies and human decision-making behaviors. The effect of multiple human decision-making behaviors (e.g., governments, households, developers) on land-use change has been quantified. Based on the historical GIS data for Orange County, Florida, the model has a higher predictive ability (87.7%, compared to 85.7% in LandSys I) for land-use change from Year 1990 to 2000. It is also found that either increasing hidden layers in ANNs or the use of multiagent models improv...
Lecture Notes in Geoinformation and Cartography
This study describes an integrated platform model for assessing the interaction among land use, t... more This study describes an integrated platform model for assessing the interaction among land use, transportation, and mobile source emissions. In the proposed integrated framework, LandSys, a home grown land use model, produces land use change over the dimensions of space and time, allocates land use forecast results in terms of household and employment at the traffic analysis zone (TAZ) level, and feeds these socioeconomic data into a travel demand model, the Florida Standard Urban Transportation Model Structure (FSUTMS). Then, the produced travel time and accessibility index by FSUTMS are fed back into LandSys to quantify the emissions. Finally, the emissions from standalone FSUTMS and integrated framework are compared to quantify the air quality benefits of the land use development from the integrated land use and transportation model. In the case application of Orange County, Florida in the United States in 2000, 2012 and 2025, five major indicators of transportation networks were used: link saturation in the transportation network, overall vehicle miles traveled (VMT), vehicle hours traveled (VHT), mobile source greenhouse gas emissions and fuel consumption. The results show that the values of the five indicators were lower when utilizing the integrated platform than was predicted by the standalone FSUTMS models, which demonstrates that the integrated platform achieved greater effectiveness in environmental improvements by considering the interactions between land use and transportation.
Natural Hazards, 2016
Sea level rise (SLR), as a likely outcome of climate change, threatens coastal communities throug... more Sea level rise (SLR), as a likely outcome of climate change, threatens coastal communities through intensified storm surge, strong wind, flooding, and other extreme weather events. While social vulnerability to SLR is receiving overwhelming attention from research communities, studies on the business impacts of SLR are much less developed. In this study, an innovative framework of integrated business vulnerability is developed for environmental hazards (e.g., SLR) and is validated by a case study of Bay County, Florida. First, the model establishes a composite business vulnerability index (BVI) by incorporating business characteristics, infrastructure factors, and other indicators based on existing literature results. Second, it identifies impacted business indicators and how they will change with the projected SLR. To account for climate change uncertainty, floodplains are generated under three SLR levels (0, 0.2, and 0.9 m). Finally, this study uses a GIS-based methodology to combine physical and business vulnerabilities to investigate overall susceptibility and how this changes with SLR. Two important findings are identified. First, business vulnerability to flooding will be escalated substantially by SLR. Considerable amount of areas, businesses, and road networks would be exposed to highest flood risk zones due to SLR. Second, highest flood risk zones do not necessarily intersect with those areas of high BVI. The results can help local governments better allocate financial and manpower resources and assist hazard mitigation teams, urban planners, and city managers in steering business development away from high-risk regions due to SLR.
International Conference on Transportation Engineering 2009, 2009
This paper proposes a capacity origin destination (OD) assignment model, and the model's algo... more This paper proposes a capacity origin destination (OD) assignment model, and the model's algorithm is given. Then the optimal route choice optimal model is established according to the principle of minimize cost. The corresponding algorithm is given. The final part is the numerical experiment.
International journal of Environmental Science and Technology
Disruptions of vulnerable links in transportation networks have been widely recognized as a serio... more Disruptions of vulnerable links in transportation networks have been widely recognized as a serious safety issue, generating both traffic congestion and significant traffic emissions. This paper aims to consolidate a proposed land-use adaptation (LUA) strategy into transportation vulnerability assessment, quantitatively exploring the question about how to optimize spatial patterns in longterm land-use planning to improve network reliability, protect existing vulnerable links and critical locations, and reduce traffic emissions. To mitigate regional network vulnerability, the LUA model employs the bid-rent theory to describe the agents' behaviors in the land market. Using the genetic and frank-wolf algorithms, this paper analyzes the relationship between link vulnerability and geographical distribution of land-use patterns. The amount of trafficrelated CO emissions is used to evaluate the environmental impacts of the vulnerable link closure. The case study indicates that the long-term LUA strategy at land-cell level effectively reduces road network vulnerability, significantly improves the performance of existing urban road systems, and reduces traffic emissions. The model results also show that road networks tend to become more vulnerable with an increase in travel demand. Furthermore, without considering accessibility reduction caused by vulnerable transportation links, the land-use development is more likely to make the existing vulnerable links more susceptible. The proposed LUA methodology could allow urban system managers and planners to take proactive actions, thereby mitigating negative environmental impacts caused by network disruptions rather than being obliged to react to them.
Lecture Notes in Computer Science, 2008
The public transit route choosing problem is the key technology of public transit passenger infor... more The public transit route choosing problem is the key technology of public transit passenger information system. Considering travel time variety caused by uncertainty traffic congestion condition, firstly this paper designs the least transfer times algorithm and the K shortest transit paths algorithm in the stochastic transit network. On the basis of travel psychology analysis, transfer times, travel time and cost of each transit path plan are taken into account. By changing link travel time reliability, the algorithms generate different K shortest transit path plans under different traffic conditions. Computational experiments demonstrate the efficiency of the model and algorithm in stochastic transit network.
Transportation Research Record: Journal of the Transportation Research Board, 2010
The purpose of this paper is to develop a bilevel integrated dynamic model—a combination of an up... more The purpose of this paper is to develop a bilevel integrated dynamic model—a combination of an upper land use allocation model and a lower transportation model—to quantify the interaction between different land use allocation strategies and the transportation system. To manage the dynamic land use change in spatial and temporal dimensions, the upper-level model uses cellular automata to capture the spatial attributes of land use change, whereas the bid–rent agent model focuses on household location choice behavior. The cell-based land allocation strategy and residential location choice generated in the upper-level model are fed into the lower-level model to reflect new transportation demand, travel cost, and transportation accessibility. Then, the travel cost and transportation accessibility produced in the lower-level model are fed back into the upper-level model. To optimize land use allocation strategy, a combination of a genetic algorithm and a Frank–Wolfe algorithm is used to m...
Journal of Urban Planning and Development, 2014
AbstractThis paper extends the previous LandSys I to introduce artificial neural networks (ANNs) ... more AbstractThis paper extends the previous LandSys I to introduce artificial neural networks (ANNs) into the framework of cellular automata (CA), multiagents, and geographic information system (GIS) to forecast land-use change at the grid cell level (50×50 m). In the model, the temporal and spatial interactions of land-use change are described by CA where transition rules are defined by ANNs to reduce the tedious work of parameter calibration in LandSys I. Compared with LandSys I, an improved multiagent model in LandSys II captures both zoning policies and human decision-making behaviors. The effect of multiple human decision-making behaviors (e.g., governments, households, developers) on land-use change has been quantified. Based on the historical GIS data for Orange County, Florida, the model has a higher predictive ability (87.7%, compared to 85.7% in LandSys I) for land-use change from Year 1990 to 2000. It is also found that either increasing hidden layers in ANNs or the use of multiagent models improv...