Planning for an uncertain future

Traffic forecasts and other projections are often presented as a single line on a graph or number in a chart. But we know—now more than ever—that these predictions are full of uncertainties. The Sacramento Council of Governments (SACOG), for a new study in JAPA, puts hard numbers to some of those uncertainties in order to plan better for them.

Can travel demand models predict cycling?

Try asking a conventional travel demand model about bicycle trips and you might get anything from an educated guess to an error message. A recent study from Sweden, however, shows what it takes to fix them. The short answer is to make the models much bigger. That leaves an important question: is it worth it?

Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements (Accident Analysis and Prevention, 2019)

With the advancements in artificial intelligence, and multiple studies being focused towards developing real-time crash prediction models, the concept of a proactive safety management system has become very close to reality. The linked study conducts an extensive review of the existing real-time crash prediction models, systematically illustrating the various methodologies being used world-wide. It evaluates the universality, design requirements, and associated challenges of various models. The study aims to be a “one stop knowledge source” for future researchers and practitioners for transitioning from the existing real-time crash prediction conceptual models to a real-world operational proactive traffic safety management system.

Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements (Accident Analysis and Prevention, 2019)

With the advancements in artificial intelligence, and multiple studies being focused towards developing real-time crash prediction models, the concept of a proactive safety management system has become very close to reality. The linked study conducts an extensive review of the existing real-time crash prediction models, systematically illustrating the various methodologies being used world-wide. It evaluates the universality, design requirements, and associated challenges of various models. The study aims to be a “one stop knowledge source” for future researchers and practitioners for transitioning from the existing real-time crash prediction conceptual models to a real-world operational proactive traffic safety management system.

Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements (Accident Analysis and Prevention, 2019)

With the advancements in artificial intelligence, and multiple studies being focused towards developing real-time crash prediction models, the concept of a proactive safety management system has become very close to reality. The linked study conducts an extensive review of the existing real-time crash prediction models, systematically illustrating the various methodologies being used world-wide. It evaluates the universality, design requirements, and associated challenges of various models. The study aims to be a “one stop knowledge source” for future researchers and practitioners for transitioning from the existing real-time crash prediction conceptual models to a real-world operational proactive traffic safety management system.

New study finds that road closures can alleviate congestion in dense urban areas

Historically, transportation policy addressing vehicle congestion has entailed increasing road capacity. However, research consistently reveals that these policies have the opposite effect. In fact, a new study reveals that cities may be able to improve vehicle travel times by closing certain road segments completely. Using the theoretical framework of the Braess Paradox, the study’s researchers model how blocking off selective streets in downtown Winnipeg can reduce overall vehicle travel times, a change which in turn enables new car-free spaces to be reclaimed as parks or pedestrian plazas.

The shortest path usually isn’t the best one, according to bikeshare users

Many transportation models assume that people choose the shortest (or least cost) path connecting them from point A to point B. But this isn’t how individuals actually behave—or so confirms one recent study based on bikeshare trip data. This affects how we model travel behavior, but also our understanding of people’s travel preferences and the ways in which we accommodate them.

The shortest path usually isn’t the best one, according to bikeshare users

Many transportation models assume that people choose the shortest (or least cost) path connecting them from point A to point B. But this isn’t how individuals actually behave—or so confirms one recent study based on bikeshare trip data. This affects how we model travel behavior, but also our understanding of people’s travel preferences and the ways in which we accommodate them.

Mainstreaming transportation and land use modeling within Oregon DOT

States interested in modeling transportation and land use can now learn from Oregon’s experience building its Statewide Integrated Model (SWIM), thanks to a new study published in the Journal of Transport and Land Use. The model, now used in ODOT’s regular operations, grew out of its decades-long Transportation and Land Use Model Integration Program (TLUMIP), launched in the late 1990s. Several keys to its success were committed staff, a sharp focus on meeting agency needs, and the ability to adapt as those needs changed.

Bridging the gap between research and practice: new study on the role of induced vehicle travel

A newly released study sponsored by CalTrans offers a thorough review and analysis of research and practice related to the limitations of existing travel forecasting models. The authors focus on limitations in forecasting induced vehicle travel generated by adding lane miles during a capacity expansion. Acknowledging that many practitioners may not have access to more advanced travel models capable of capturing induced demand, the authors recommend project staff in these cases rely on general elasticities while acknowledging the shortcomings in the analysis.