Modeling transportation basically involves development of relationship between the demand for transportation and the land-use, socio-economic and transportation system characteristics. The Indian socio-economic and transportation system characteristics are highly complex and wide ranging and hence, formulation and quantification of appropriate causal variables for modeling is a challenging task. The first part of the talk will focus on this aspect. The traffic on Indian roads is highly heterogeneous and the vehicles move on the roads without any lane or queue discipline. Hence, the commonly adopted procedure to model lane based traffic flow is not applicable for modeling this type of traffic comprising vehicles of wide ranging static and dynamic characteristics. The approach to modeling of this type of traffic flow is distinctly different. An appropriate methodology for modeling heterogeneous traffic flow has recently been developed at Indian Institute of Technology Madras and the same be will discussed in the second part of the presentation.

Dr. V. Thamizh Arasan, Professor and Head, Transportation Engineering Division, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India, has been involved in teaching, research and consultancy, in the area of Transportation Engineering for the past two and a half decades. Traffic Simulation and Travel Demand Modeling are the areas of his research interest, and he has guided several Ph. D....

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New FHWA VMT Forecasts and Implications for Local Planning


Post-Apocalyptic Zombies Ate Oregon’s Post-Recession, ATR Regression

Where: Room 204 of the Distance Learning Center Wing of the Urban Center at PSU

A summary of FHWA’s new national traffic trends assessment will be presented, including discussion of varied factors influencing forward-thinking forecasts. Examples of Oregon statewide vehicle miles travelled (VMT) and historic traffic trends from ATR stations in the Portland urban region and greater Willamette Valley will be highlighted. VMT, population and income data will be noted with implications on local transportation planning.

Andrew is an associate with David Evans & Associates, Inc., with over 28 years of experience in multimodal transportation planning with emphasis on sustainable community and Complete Street policy and plan development. He focuses on developing multimodal transportation plans with context-sensitive street standards and policies that implement enhanced bicycle and pedestrian use and circulation. His area of expertise includes measured pedestrian-access-to-transit connectivity, the implementation of...

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Moore Presentation (PDF)

Ma Presentation (PDF)

Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: The purpose of this study is to explore the use of integrated probe vehicle, traffic and land use data to identify and characterize fine particulate matter (PM2.5) and volatile organic compound (VOC) hot spot locations on urban arterial corridors. An emission hot spot is defined as a fixed location along a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when considering all other locations along the corridor during the same time period. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM2.5 and VOC concentrations. Second-by-second measurements were performed for each pollutant from both the right and left sides of the vehicle. Detailed meteorological, traffic and land use data is also available for this research. The results of a statistical analysis are used to better understand which...

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Abstract: Integrated land use transportation models simulate the behavior of the spatial economic system and the interactions between the transportation system and the rest of the economic system. The essential elements of these models are explicit treatment of space in economic production and consumption behavior, both the space that is the physical areas that contain production processes and the space that separates different production locations and gives rise to the demand for travel and transport. They put travel within an economic context, and thus facilitate simulation of the impacts of transportation policy and planning actions and transportation conditions on the wider economic system. As such, integrated models can be used address complex policy questions that more limited transportation models cannot address, or cannot address well.

This seminar will set out the basic scope and form of integrated models and discusses several of the key advantages they provide for planning. Experiences gained in the practical applications of the Oregon SWIM and Sacramento MEPLAN and PECAS integrated models will be described. These experiences will be used to illustrate the added benefits arising with such models in terms of more efficient land use forecasting, more complete analysis of cumulative and indirect impacts and more holistic consideration of policy in general, more...

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The proliferation of information technology in the transportation field has opened up opportunities for communication and analysis of the performance of transportation facilities. The Highway Capacity Manual relies on rules of thumb and small data samples to generate levels of service to assess performance, but modern detection technology gives us the opportunity to better capture the dynamism of these systems and examine their performance from many perspectives. Travelers, operations staff, and researchers can benefit from measurements that provide information such as travel time, effectiveness of signal coordination, and traffic density. In particular, inductive loop detectors show promise as a tool to collect the data necessary to generate such information. But while their use for this purpose on restricted‐access facilities is well understood, a great many challenges remain in using loop detectors to measure the performance of surface streets.

This thesis proposes 6 methods for estimating arterial travel time. Estimates are compared to simulated data visually, with input/output diagrams; and statistically, with travel times. Methods for estimating travel time are applied to aggregated data and to varying detector densities and evaluated as above. Conclusions are drawn about which method provides the best estimates, what levels of data aggregation can still provide useful information, and what the effects of detector density are on the quality of estimates....

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