The Mineta Transportation Institute surveyed various levels of government—cities, states, and college campuses— as well as conducted personal interviews with stakeholders, to detail how jurisdictions are regulating electric and kick scooters, skateboards, e-skateboards, hoverboards, Segways, and rollerblades. They then recommended model state laws to bring some standardization to the use of these personal transportation devices.
Performance Measures
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.
Estimating policy effects on reduced vehicle travel in Hawaii (SSTI, 2019)
Transcending Oil, released in April 2018, describes Hawaii’s path toward meeting its ambitious clean energy goals by 2045. The report was commissioned by Elemental Excelerator and prepared independently by Rhodium Group and Smart Growth America. It focuses mainly on transitioning the electrical grid to renewable energy while moving large numbers of vehicles to electric power but also points to the importance of managing overall travel demand through transportation policies and investments. This technical guide describes the methods and findings behind Transcending Oil’s travel demand forecasts, developed by SSTI and Smart Growth America.
Modernizing Mitigation: A Demand-Centered Approach (SSTI, September 2018)
This report proposes a new approach to assessing and responding to land use-driven transportation impacts, called “modern mitigation.” Instead of relying on auto capacity improvements as a first resort, this approach builds on practice around transportation demand management (TDM) to make traffic reduction the priority. Based on programs dating to the 1990s in several cities, a modern mitigation program requires certain new land uses to achieve TDM credits.
Accessibility in practice (SSTI and Virginia Office of Intermodal Planning and Investment, 2017)
Planning agencies and transportation decision makers often talk about the importance of improving access to destinations, but they rarely have the tools or resources to measure accessibility and incorporate those metrics into decision making. This report guides agencies through that process.
Trip-making data, TDM, and connectivity in Northern Virginia (SSTI and Michael Baker International, 2016)
Commercially available GPS data offers valuable new insight about trip origins, destinations, and routes, including short trips that travel demand models often cannot capture. Using this data, SSTI worked with Michael Baker International, the Virginia DOT, and local stakeholders to identify opportunities for managing travel demand and improving connectivity throughout Northern Virginia. This final report describes the full data set and 17 selected case studies, along with recommended projects and policies, estimated costs, and benefits for each.
Trip-making and accessibility: New tools, better decisions (SSTI, 2016)
Transportation researchers and practitioners have long sought other tools to complement or perhaps replace conventional methods—tools that would better analyze trips rather than speed at points in the system, speak to non-auto modes of travel, address land use solutions as well as highway infrastructure, and so on. Fortunately, new sources of data and emerging methods, as well as new-found interest in performance and scenario planning, are yielding the types of tools that the field needs.
Quantifying Transit’s Impact on GHG Emissions and Energy Use—The Land Use Component (TRB, 2015)
Transit often fails to get the credit it deserves for reducing traffic and emissions. In most U.S. cities, transit’s mode share is in the single digits, so the direct effect of ridership seems small. And while it’s clear that even in places with low mode share transit plays a role in raising densities—and thereby reducing travel distances—this relationship has been hard to quantify; conventional demand models simply take land use as an input. Filling this gap is a report and tool from TRB’s Transit Cooperative Research Program.