UCTC 2012 Faculty Grant Abstracts (Alphabetical by campus and PI)
Improve Transit Connectivity with Incentives
We propose to use incentives to address the transit connectivity problem. This problem, also known as the first and last mile problem, is the problem that people have difficulty accessing transit stations and therefore choose to drive instead of taking transit. Solutions to the problem exist, but adoption is limited because the access modes to transit stations are either inconvenient (e.g., too far for walking), or expensive (e.g., too few people to use shuttle), or infeasible (limited space for park and ride). We propose to use incentives to bootstrap the use of specific access modes, and retain some behavioral change in the long run in a sustainable manner. We will devise a comprehensive list of incentives for consideration. We will leverage an ongoing effort to study how people react to different types of incentives. We will choose a few candidate sites for case study and build a simulation tool to estimate the effects of incentives. The effects include both behavioral effects like how people choose access mode and travel mode, and traffic effects like the duration of congestion. We will also likely to find out which incentive is the most cost-efficient in achieving similar behavioral change.
Bus Stops near Signalized Intersections: Analytical Models, Management Strategies and Design Guidelines
UC BerkeleyCurbside bus stops are often located in close proximity to signalized intersections. A bus that dwells at a stop of this kind can impede queued cars upstream as they attempt to discharge into the intersection during green times. This state of affairs adds to the delay and queueing of cars, which in turn can negatively impact the bus. We seek to formulate analytical models that quantify these negative impacts of bus-stop operation. The models will be developed using kinematic wave theory, and we envision very general models that can be applied: to bus stops that are located either upstream or downstream of their neighboring intersections; and to wide ranges of car and bus demand and roadway geometry. We will use the models to theoretically explore innovative bus-stop management strategies. Our goal here is to devise strategies that improve travel for both buses and cars. Model predictions will be tested against simulation and real observation. Finished products will include a set of guidelines to assist practitioners in determining both, where to place bus stops relative to intersections, and how to manage the buses and cars at and around these stops in greener ways. Budget: $79,481
Air Emission Reduction Opportunities for California’s Trucking Sector by 2020 and 2050
California is the largest consumer of transportation fuels in the United States. An increasing fraction of these fuels (25% - 29%) are dedicated to powering heavy-duty trucks, which has significant effects to both air quality and the climate. Current technologies aiming at reducing emissions focus primarily on improved fuel efficiency. However, massive transformations to our current fuel technologies will be needed in order to meet California’s long-term air emissions goals. Alternately fueled vehicles (AFV) will have to play an important role in mitigating the environmental burdens associated with California’s heavy-duty freight trucking sector. We will conduct a study that will create a complete inventory of greenhouse gas and criteria air emissions attributed to heavy-duty trucks using life-cycle assessment models. The fuels analyzed will be natural gas, biodiesel, ethanol, and oil sands as a new source of fossil fuels. Current environmental inventories focus on tailpipe emissions, excluding key components of a truck’s life cycle: fuel production, manufacturing, and maintenance. We will provide life-cycle emission factors for California’s future AFVs. With these emission factors, we will create emission scenarios that compare business-as-usual performance with near-term efficiency-focused strategies and accelerated AFV deployment in the context of meeting California’s 2020 and 2050 climate and air quality goals.
Peer-to-Peer (P2P) Carsharing: Understanding Early Market Dynamics & Social and Environmental Impacts
As traditional carsharing has become an integral part of urban transportation systems across North America, new and advanced approaches to carsharing have begun to emerge. One such advance is peer-to-peer (P2P) carsharing, in which ITS technology opens personally-owned vehicles to carsharing. This project would study early P2P carsharing members through focus groups, stakeholder interviews, and an online survey. Focus groups would probe the experiences of members that contribute and rent vehicles to understand the obstacles faced in sharing P2P vehicles. The focus groups would also inform the design of an online survey of members across P2P organizations in North America. Questions would explore how P2P carsharing has altered member walking, bicycling, public transportation, personal driving, and ridesharing. Researchers would identify benefits/positive experiences and challenges/frustrations faced by P2P users/vehicle renters to inform the P2P industry of early adopter considerations. Finally, stakeholder interviews with operators and key supporters (e.g., legislators) would gain perspective on industry challenges and opportunities from a policy perspective. The results would be used to advance knowledge of P2P carsharing and aid organizations in expanding their vehicle networks through a better understanding of the fundamental needs and characteristics of their membership base as related to the broader population.
After SB375: Using Statewide Activity-Based Modeling to Assess the Impact of Sustainable Community Strategies on Regional and Interregional Travel Behavior
This research project proposes using the advanced statewide activity based travel demand model CSTDM, in combination with the more detailed interregional model SJVITM, for the evaluation of the impact of land use policies on travel behavior in California. Senate Bill 375 requires local metropolitan planning organizations (MPOs) in California to develop Sustainable Community Strategies (SCSs) to promote transportation investments and land use policies that reduce VMT and car use dependence. However, still little evidence is available on the expected results of these policies. In particular, the effects on the border regions between MPOs are not easy to estimate. In addition, contemporaneous changes in the transportation system (e.g. fuel prices, modifications in vehicle fleets and transit supply) might create synergies that are, to date, largely unexplored. The use of the proposed modeling framework, which simulates all components of long distance and short distance travel, for both passengers and goods, will provide a consistent interregional framework for this analysis. The project will provide useful insights on the overall impact of land use policies on regional and interregional travel behavior, and it will contribute to the transfer of knowledge to the community of policy-makers to support more informed decision-making.
Davis Shopping Study: Factors Influencing Impacts of Big-Box Retail on Shopping Travel
Shopping travel constitutes a significant share of all daily travel in the U.S. This travel has significant environmental impacts with respect to energy consumption, air quality, water quality, and climate change. Understanding the factors that influence choices about shopping provides a basis for the development of policies that help ensure that consumer needs are met while the environmental costs of shopping travel are minimized. The purpose of this study is to examine shopping behavior of residents of Davis, CA before and after the opening of a Target store in Davis in 2009. The opening of the store presented a unique opportunity to study the causal effects on shopping behavior of a significant change in the retail landscape. We completed a survey of Davis residents as to their shopping travel just before the opening of the store and one year after the store opening. Using data from this survey, we have estimated a significant reduction in vehicle miles of travel for shopping purposes for Davis residents. These results are relevant to current policy debates in California over the role of “smart growth” planning policies in reducing greenhouse gas emissions as a way to meet Senate Bill 375 requirements.
Jonathan London, Chris Benner, Deb Niemeir
From Development to Implementation of Social Equity Metrics and Scenarios for Sustainable Communities Strategies in the San Joaquin Valley
The proposed project seeks to: (1) refine for use in the San Joaquin Valley a set of existing social equity analysis tools applicable to sustainable regional development policy and planning that have been developed in the Bay Area and Sacramento regions; (2) apply these tools to inform social equity and health scenario development for use in regional planning related to SB 375 (Sustainable Communities Strategies/Metropolitan Transportation Plans) by Councils of Governments (COGs) and community advocates in the San Joaquin Valley; and (3) conduct a formative assessment of the scenario development and tool application process. These tools, including a Social Vulnerability Index, an Opportunity Index, a Jobs-Housing fit analysis, a Cumulative Environmental Hazard Index and a Transportation Equity Index, have been developed and applied in SB 375-related planning in the Sacramento and San Francisco Bay Area regions. Equity advocates in the San Joaquin Valley have requested assistance from UC Davis to work collaboratively with them and with the COGs in the region to apply these tools and develop equity scenarios for the region’s Sustainable Communities Strategies/Metropolitan Transportation Plans.
Social Networks and Travel Behavior: A Comparative Analysis
Using a comparative approach, this project explores how social networks influence travel behavior at three, large public universities that differ in environmental constraints such as climate, infrastructure and city/university-wide transportation culture. Focus groups and interviews of students and transportation policy decision-makers provide qualitative context for survey design and statistical analysis. Surveys of random samples of students provide measures of mode choice, as well as the “egonetworks” of contacts with whom each respondent communicates about transportation choices. Analysis includes measurement of network structures such as network density and centrality. Discrete choice models are estimated to predict travel mode as a function of individual characteristics as well as social networks attributes. Models from each university are compared to identify environmental factors which affect how social influences impact travel behavior. A key comparative hypothesis is that the influence of social networks is smaller in contexts with greater environmental constraints; high levels of environmental constraints make social networks less relevant. A greater understanding of the social processes that influence travel behavior can help improve policy and education programs designed to increase the use of alternative transportation modes and sustainable transportation behaviors.
Activities Conducted while Traveling: What Is Their Impact on Mode Choice and the Value of Travel Time?
From early studies of time allocation onward, it has been acknowledged that the “productive” nature of an activity such as travel could affect its utility. Yet until recently, there has been very little empirical assessment of such an effect, in particular the potential effect of activities conducted while traveling on the (dis)utility of the trip and thence the value of travel time for such a trip. In previous phases of this multi-year study, we developed a fundamental conceptualization of polychronicity (multitasking) attitudes and behavior, and created and administered a survey to measure multitasking attitudes and behavior specifically while commuting, together with general attitudes, mode-specific perceptions, and standard socioeconomic traits (N = approximately 3020 Northern California commuters). This proposed continuation of the research will fund the development of first-of-their-kind revealed preference mode choice models accounting for the impact of multitasking attitudes and behavior on the utility for various alternatives. The resulting insights will inform and improve policies and services promoting more sustainable forms of travel, and lead to more realistic models and forecasts.
Capacity Reallocation Projects and Their Perceived Effects on Local Economics, Sustainability, Livability
With increasing federal and state policies and funding support mechanisms for non-motorized transportation, an important opportunity exist to further our understanding around design and implementation issues associated with these projects. Many communities are exploring capacity reallocation projects, which generally take the form of reducing an existing multi-lane road (usually four-lanes) to two vehicle-lanes, and adding a center left hand turn lane and dedicated bike and pedestrian paths in both directions. Although capacity reallocation projects are becoming a more widely applied mode shift strategy, there is very little research on the impact of these types of projects on non-safety factors. This research will contribute by expanding our understanding of how residents and businesses judge the economic and livability impacts of road diets and how previously surveyed respondents and their initial project opinions may be modified by personal experience with a reallocation project. Our proposed project builds on a prior UCTC supported effort that focused on a pre-implementation data collection and analysis for a capacity reallocation project within the City of Davis. The project was referred to as the 5th Street Redesign. Our current UCTC support focused on capturing attitudes and perceptions as well as characterizing existing operating conditions as the 5th Street Redesign went from the public participation stage through final design. Here, we propose to focus on community perceptions, attitudes and personal usage after implementation, which is scheduled for Sept 2012. As far as we know, this project will serve, in total, as the first rigorous pre- and post-evaluation of capacity reallocation project.
Modeling Traffic Flow at Merge Bottlenecks Considering Merging Location Choice
Merge bottlenecks, such as lane drops, junctions with entry ramps, and freeway-to-freeway merges, are the most common places where traffic congestion initiates. These are the places where drivers compete for reduced road space and are forced to interact. Furthermore, merge junctions are also fundamental building blocks of networks, hence their models are essential components of network traffic models widely used in dynamic traffic assignment and other network applications. Despite recent renewed interest and progress made in modeling merge bottlenecks, our understanding of and ability to model them is far less mature than those related to traffic on homogeneous road sections, partly due to the complexity of merge dynamics and partly insufficient observations. In this research, we attempt to gain a better understanding of traffic system behavior at merge bottlenecks through careful studies of vehicle trajectories from on-ramp junctions, and use this understanding to develop more realistic merging traffic flow models that takes into account the choice of merging locations. It is expected that this research can help build a solid foundation of network traffic flow theory by addressing an essential component of this theory, namely merging traffic dynamics, which in turn can help the design of more effective traffic control strategies to reduce traffic congestion caused by merge bottlenecks.
Evaluating the Travel and Physical Activity Impacts of the Exposition (Expo) Light Rail Line; Leveraging Transit Investments for Community Livability and Regional Sustainability
This research will support analysis of data collected in California’s first experimental-control, before-and-after evaluation of a major light rail transit (LRT) investment, the Exposition (Expo) line from downtown to the westside of Los Angeles. The region’s ambitious LRT construction campaign will support Senate Bill SB375 goals for greater integration of transportation and land use planning, but we know little about whether and to what degree new LRT is associated with reduced private vehicle travel and increased transit usage. In Fall 2011, we collected geographically detailed 7-day travel data for 285 households along the corridor using daily trip and vehicle odometer logs and supplemental GPS-based location tracking. We will collect comparable “after” data for the same households in Fall 2012 after the Expo line service begins in Spring 2012. The current proposal will support data coding, processing, and analysis and will inform transit planning and community development by (1) assessing the impact of Expo service on nearby private vehicle travel, transit ridership, and physical activity, (2) identifying neighborhood factors which could enhance the potential positive effects of transit proximity on bus ridership and walking, and (3) demonstrating methods for evaluating the sustainability, travel, and community impacts of major transportation projects.
Bounded Acceleration and Capacity Drop at Merging Bottlenecks
The objective of this research is to prove the conjecture that bounded acceleration rates of vehicles can lead to capacity drop inside a merging area. Capacity drop is one of the most puzzling traffic phenomena occurring near such bottlenecks as lane-drop and merges. While it has been suspected that such a capacity drop is caused by drivers’ acceleration behaviors inside various bottleneck areas, there have been no systematic studies on the relationship between drivers’ acceleration process and the magnitude of capacity drop. In this research we aim to develop, calibrate, and validate a macroscopic model of acceleration behaviors inside a merging bottleneck and quantify their impacts on capacity drop. From observed vehicles’ trajectories, we will calibrate acceleration rates and distances inside such an acceleration zone and calculate the magnitude of capacity drop using the macroscopic acceleration behavior model. The result will be compared with the observed capacity drop from loop detector data. Such a research can improve our understanding of the mechanism and magnitude of capacity drops at freeway bottlenecks. The knowledge can then be employed towards improving ramp metering, variable speed limits, and other control strategies to reduce congestion and vehicle emissions in a road network.
Improving Transportation Performance: The Case of Left Turns
Over the past century, the automobile has evolved to dominate transportation not only from a behavioral perspective but from an infrastructure perspective. Thoroughfares that evolved over millennia to serve many users were transformed in decades to the near exclusive use by motor vehicles. The reasons for this evolution are well documented; alternatives to the behavioral dominance, while numerous in terms of proposals and promise, are nevertheless constrained by the infrastructural dominance. One option that has not been systematically studied but that has the cost advantage of maintaining current infrastructure while addressing associated performance impacts is a significant reduction in allowed arterial left turns. Such a policy will soon become feasible with the rapid adoption of GPS and traveler information systems that can inform drivers of optimal route choice in restricted networks. The proposed research will use a microsimulation approach to investigate a range of left turn restriction and removal options on sample arterial networks, under a range of driver behavior assumptions.
Moving from Interesting to Implementable Models for Efficient Transportation Systems Management – Breaking Through the Computing Barrier
In this research we propose to extend a decade or more of research in parallel and distributed computing architecture to work on transportation problems falling into the general category of network design, but with time scales that range from real-time to quasi-real time to quarterly or annual planning. We then propose to extend this work to many other operational problems.
Truck Tour-Based Model for Spatial Disaggregation of California Freight Demand
Freight transportation encompasses the movement of a wide variety of commodities as well as commercial vehicles on the freight infrastructure, linked to socioeconomic condition and polices. Throughout the history of transportation research, the concept that freight movement is responsible for a large share of the diverse problems in transportation has been accepted, but widespread concerns about environmental impacts such as air pollution, noise, and safety have led to a renaissance of new freight related research. In the same vein, the role of statewide freighting forecast models has been expanded into much finer levels of analysis than the county level. In partnership with state agencies and Metropolitan Planning Organizations (MPOs), the California Department of Transportation (Caltrans) is currently developing a California Statewide Freight Forecasting Model (CSFFM). A critical challenge is to provide a framework for organic integration between the CSFFM and a finer spatial level of models to meet MPO needs. However, factoring methods are currently largely used for disaggregating freight demand. Such methods cannot adequately capture the complex structure and behavior of freight movements, advances in logistics, information technology, and relocating infrastructure at the MPO level. One advantage of the CSFFM, modal path-based OD representation, cannot be fully utilized by MPOs because factoring methods tend to break the chains of modal path-based information in the conversion to trip-based information. This research will explore and develop truck tour-based models for disaggregating California Statewide Freight Demand from an aggregate Freight Analysis Zone (FAZ) level to the more disaggregateTraffic Analysis Zone (TAZ) level, by using truck GPS data. Expected results include new and improved insights into the spatial and temporal operations of trucks at the urban and MPO level, contribution to the statewide-related component of urban freight modeling, and an evaluation of traffic and environmental impacts of state-level policies and air pollution mitigation strategies.
Analysis and Synthesis of Electric Vehicle and Charging Data for Multi-Mode Mobility Systems
This project will explore PEV use and charging patterns in combination with unique vehicle attributes, to address the limitations of PEV adoption as a function of EVSE availability and explore mixed-mode mobility systems that leverage PEV performance characteristics while minimizing their limitations. Specifically, this project will utilize data available from the Zero Emission Vehicle•Network Enabled Transport program in conjunction with the established Spatially and Temporally Resolved Energy and Environment Tool (STREET) to analyze mixed-mode mobility system utilizing PEVs.
A Spatial Analysis of Housing and Transportation Affordability in Los Angeles County
Increases in fuel prices, combined with the deep downturn in the economy, have raised concerns about the burdens of transportation costs on low-income families. We propose to investigate this issue, focusing specifically on neighborhood variation in the percentage of household incomes spent on housing and transportation. We hypothesize that the phrase "drive 'til you qualify" (for a mortgage) has some truth; poor and moderate- income households living in suburban areas—particularly inner-ring suburbs—will pay less for housing, but more for transportation than households living in wealthy suburban neighborhoods or in central-city neighborhoods well served by public transit. We will test this hypothesis using individual data on vehicle miles traveled, vehicle type and fuel efficiency, and housing costs. Specifically, the proposed project will combine property-level housing data, vehicle-specific fuel use information, and block-group demographic data for households in Los Angeles County. We, first, will examine spatial variation in housing-transport costs relative to income. We then will analyze how neighborhood affordability has evolved since 2000, a period in which gas prices rose significantly. Finally, we will assess whether there is a relationship between neighborhood income levels and changes in vehicle miles traveled and the fuel economy of neighborhood vehicles.
Exploration and Implications of Multimodal Street Performance Metrics: What’s a Passing Grade?
This project aims to analyze new multimodal street performance metrics for transportation projects. Scholars and practitioners have developed these new performance metrics in recent years in an attempt to replace traditional automobile-based level of service (LOS) indicators. Many scholars and practitioners feel traditional LOS overemphasizes the free flow of automobile traffic while neglecting other users of the transportation system. While practitioners and advocates have shown enthusiasm for these new metrics, policy-makers have found it difficult to transition from well-understood and standardized automobile-based LOS metrics to any one of the new multimodal metrics. Similarly, scholars have paid a great deal of attention to the development of these new metrics, but have not documented how these metrics compare to one another. This comparison is necessary, as each of the metrics embodies a number of assumptions about the performance of the transportation network for non-auto users such as pedestrians and cyclists. This project will aid policy-makers by explicating these assumptions, providing a comparability analysis of the various metrics and relating the results to policy implications. Further, this project will enrich our understanding of the ways in which the needs of government regulation results in a reduction of complex transportation systems to simple descriptors.
Honey, Can you pick-up groceries on your way home? Analyzing activites and travel in non-traditional households
Except for walks in the park and cruising on a Saturday night, travel is a means to an end. Economists describe the demand for travel as “derived” because people travel in order to access other things—work, shops, restaurants, friends, and so on. Transportation is often a critical link to education, paid work, recreation, health care, culture, and many other aspects of quality living. While conventional measures like person-miles of travel (PMT) are excellent measures of mobility, they do not tell us much about access, or the utility of personal travel. To examine travel utility or access, we must turn our attention to activity participation—the taking of trips for various purposes. Trip-making is an excellent, albeit indirect and understudied window on activity participation. People’s work habits, shopping behavior, recreational preferences, and so on are revealed by the stated purpose of their travel in surveys like the National Household Travel Survey (NHTS), as well as in activity surveys such as the American Time Use Survey (ATUS). We propose to examine how activity participation differs by household type. This is increasingly relevant as the share of two-sex, married couple households with children continue to decline, while what has been (increasingly misleadingly termed) “non-traditional” households continues to grow. How members of this new majority of non-traditional households divide labor, organize activities, and travel about is of critical importance to transportation officials charged with planning for the next generation of travel.
In particular, we aim to add to the existing knowledge of the ways in which sex and gender roles influence activity patterns in households. Numerous scholars have investigated the important differences between men and women in travel and particular outcomes such as employment (e.g. Hanson and Pratt 1991; Hanson and Pratt 1995; McGuckin and Murakami 1999; Blumenberg 2004; Crane 2007), though none have taken a comprehensive look at gender and activity participation more broadly. Further, few researchers have considered the ways in which gender and sexuality may intersect to influence within-household activity allocation (cf. Rapino and Cooke 2011, who use same-sex partnered households as a counterfactual). A deeper understanding of how gender and household arrangements—including same-sex partnerships, opposite-sex partnerships, roommates, and other arrangements—influence activity and travel patterns may shed light on the mechanisms behind the gendered differences in travel. For instance, we expect that our study will suggest whether it is in fact sex in a broad societal context that drives the differences, or rather sex in a very specific context: that of the opposite-sex partnered household—the explicit or implicit subject of most prior studies. We thus propose to examine activity participation by sex and household type using two datasets. The first will be the confidential, geo-coded version 2009 NHTS, which will allow us to examine the connection between gender, household structure, and outside-the-home activity participation, as well as the availability and utilization of transportation resources of individuals in the household. The strength of this dataset is its ability to provide valuable information on specific transportation variables such as details on the vehicles owned by a household. However, a significant weakness of this dataset is the lack of within-household activity participation information, such as household chores and in-home childcare activities. In order to understand how gender, sexuality, and household structure influence both within-household and out-of-the-home activity patterns, we will also attempt to employ the American Time Use Survey, a detailed activity survey conducted in conjunction with the Bureau of Labor Statistics’ Current Population Survey. From this research, we expect to produce two academic papers—first, one that focuses on automobile usage and activity participation in various household types, with a particular emphasis on the differences between same-sex partnered and opposite-sex partnered women. In the second paper, we will examine the trade-offs between within-household and out-of-the-home activities, again with a special focus on the differences between women in same-sex and opposite-sex partnered households. Finally, we will produce a report for the University of California Transportation Center summarizing our findings from these two analyses.
The Role of Habitat Plans in Facilitating Transportation Infrastructure
Since the federal Endangered Species Act prohibits any action that causes harm to endangered species or destruction of their habitat, prior to the authorization of Habitat Conservation Plans (HCPs) in 1982, non-federal entities were limited in their ability to proceed with otherwise lawful activities, including transportation infrastructure projects, which might incidentally harm endangered species. HCPs provide a way to move forward on infrastructure projects without fear of criminal or civil endangered species violations by establishing agreed upon conservation or mitigation measures. The proposed research seeks to determine whether HCPs facilitate the delivery of large transportation infrastructure projects undertaken by non-federal entities. The research will involve case studies of six to twelve public HCPs with a specific focus on transportation infrastructure projects and off-site mitigation. The final report will include an assessment of the relationship between HCPs and environmental review processes for large infrastructure projects, and will develop a set of policy implications based on the research findings.
Calibration of Traffic Micro-simulation Models for Microscopic Vehicle Emission Modeling
When conducting vehicle emission analyses, ones generally rely on traffic models to generate traffic performance or vehicle activity data, which are then used as an input for emission models. For project-level conformity and hot spot analyses, the use of traffic microsimulation modeling tools is desirable as they are able to model detailed movements of individual vehicles in the traffic stream at high time resolution, allowing the impact of vehicle acceleration on emissions to be captured. To properly use traffic microsimulation models for such purposes, ones must ensure that the simulation network is well calibrated so that it replicates the real-world traffic condition. As the commonly used traffic microsimulation calibration criteria are based mostly on macroscopic traffic parameters, it is proposed herein to: 1) examine if these criteria are sufficient to make the simulated vehicle trajectories represent those observed in the real-world at the micro scale, and 2) develop supplemental calibration criteria and procedures specifically for the purpose of modeling emissions at the micro scale. The results of this research are expected to improve the current practice of microscopic vehicle emission modeling.
Kostas Goulias and Srinath Ravulaparthy
Business Establishment Spatial Evolution Microsimulation (BESEM)
UC Santa Barbara
In this research project Dr. Kostas Goulias and Srinath Ravulaparthy will develop a model system and define initial testing of a business establishment spatial evolution microsimulator (BESEM). The main objective of this method is to create a self- standing software that is able to replicate the change in location of each business establishment in California as a function of its relationship with other business establishments and the transportation infrastructure connecting all businesses. This is a much needed method to: a) show the spatial correlation between business location (and implicitly jobs) and infrastructure by each business type at a microlevel; and b) compute activity opportunity based accessibility indicators that capture observed changes due to businesses moving into the state, moving out of thestate, and relocating from one region to another. Schemata for each business type (medical, retail, legal) will be first developed and tested with real world data using point process statistical models. These models will then be used in a small scale simulation as proof of concept toshow their spatial and temporal relationship with transportation infrastructure. The tasks include data assembly and assessment of quality, testing of spatial statistics models, creation of the simulatorframework, and testing.