Portland State University

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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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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Summary: A growing concern related to large-truck crashes has increased in the State of Texas in recent years due to the potential economic impacts and level of injury severity that can be sustained. Yet, studies on large truck involved crashes highlighting the contributing factors leading to injury severity have not been conducted in detail in the State of Texas especially for its interstate system.  In this study, we analyze the contributing factors related to injury severity by utilizing Texas crash data based on a discrete outcome based model which accounts for possible unobserved heterogeneity related to human, vehicle and road-environment. We estimate a random parameter logit model (i.e., mixed logit) to predict the likelihood of five standard injury severity scales commonly used in Crash Records Information System (CRIS) in Texas – fatal, incapacitating, non-incapacitating, possible, and no injury (property damage only). Estimation findings indicate that the level of injury severity outcomes is highly influenced by a number of complex interactions between factors and the effects of the some factors can vary across observations. The contributing factors include drivers’ demographics, traffic flow condition, roadway geometrics, land use and temporal...

Transportation mode choice is often expressed in terms of models which assume rational choice; psychological case studies of mode adoption are comparatively rare. We present findings from a study of the psychology of adoption for sustainable transportation modes such as bicycles, car sharing, and mass transit. Case studies were conducted with current and former participants in PSU’s ‘Passport Plus’ transit pass program, as well as a longitudinal cohort study of first-time winter bicycle commuters. Composite sequence analysis was used to construct a theory of the adoption process for these modes. Our findings suggest that mode evaluation is cognitively distinct from mode selection and has different information requirements. We conclude that public and private organizations could improve the adoption rate for these modes by tailoring their communication strategies to match the commuter’s stage of adoption.

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The video begins at 9:01.