Erick Guerra

Planning for Cars That Drive Themselves Metropolitan Planning Organizations, Regional Transportation Plans, and Autonomous Vehicles

Through a review of long-range transportation plans and interviews with planners, this article examines how large metropolitan planning organizations are preparing for autonomous vehicles. In just a few years, the prospect of commercially available self-driving cars and trucks has gone from a futurist fantasy to a likely near-term reality. However, uncertainties about the new technology and its relationship to daily investment decisions have kept mention of self-driving cars out of nearly all long-range transportation plans. Nevertheless, interviewees are keeping a close watch on the new technology and actively looking to understand and plan for future impacts.

The Built Environment and Car Use in Mexico City Is the Relationship Changing over Time

This article explores differences in the relationship between the built environment and households’ car use in Mexico City in 1994 and 2007. After controlling for income and other household attributes, population and job density, transit and highway proximity, destination diversity, intersection density, and accessibility are statistically correlated with households’ weekday car travel in Mexico City. These correlations are generally stronger than those found in studies from U.S. cities and fairly stable over time. Where correlations have changed, they have strengthened. Findings suggest that land use planning can play a modest and growing role in reducing car travel in Mexico City.

To T or Not to T: A Ballpark Assessment of the Costs and Benefits of Urban Rail Transportation

The debate over the costs and benefits of rail passenger transit is lively, deep, and often ideological. As with most polemical debates, the truth probably lies somewhere in the middle of extreme views. Some rail systems have benefits that outweigh their costs, while others do not. Applying a commonly used transit-fare price elasticity to 24 of the largest light and heavy rail systems in the United States and Puerto Rico, assuming a linear demand curve, and accounting for a counterfactual scenario, we find that just over half of the systems have net social benefits. Although Los Angeles’ rail system does not “pass” our back-of-the-envelope cost—benefit analysis, as the network expands, it will begin to mimic the regional spatial coverage and connectivity of its chief competitor—the auto-freeway system—and approach the fare recovery rates of other large, dense American cities.

Making effective fixed-guideway transit investments: indicators of success

This report provides a data-driven, indicator-based model for predicting the success of a fixed guideway transit project based on expected project ridership and resulting changes in transit system usage. Applying this analytical model can help local, regional, and state transportation planning agencies determine whether a proposed improvement project merits investment in more detailed planning analysis. The analytical model encompasses a spreadsheet tool and a handbook detailing its application. The handbook makes up Volume 1 of this report. The final research report makes up Volume 2 and includes the detailed literature review, a presentation of the conceptual framework for the analytical model, a summary of the quantitative analysis methods and findings, and an overview of the case studies used to formulate and test the analytical model. The spreadsheet tool is available separately for download from the report web page at www.trb.org.

Cities, Automation, and the Self-parking Elephant in the Room

Over the next 25 years, automated vehicles could fundamentally alter not just how people travel, but where they choose to live and how cities form and grow. These changes and uncertainty about their timing, scale, and nature present substantial challenges for the city planners, traffic engineers, and other public officials who need to make regulatory and investment decisions that will coincide with the shift from humanto computer-driven vehicles. For example, today’s decision to invest in a new rail line will likely require five-to-ten years of planning and construction and have a service life of another 30-to-50 years. Over this same period, self-driving buses and cars may have substantially changed the underlying nature of the demand for, and provision of, public transportation. Similarly, today’s justification for a highway investment or road widening may look out of touch, given expectations about how vehicle automation could increase the number and speed of vehicles that can move on each highway lane. In this essay, we summarize some of the technological and behavioral uncertainties that limit our ability to predict when and how vehicle automation will affect cities. We then present a simple framework for planning under the uncertain conditions presented by autonomous vehicles, and conclude with a discussion of parking policy. Whether automated vehicles lead to revolution in shared mobility, or a substantial increase in singleor even zero-occupancy car travel, the relationship between parking and shops, housing, and offices will change. Parking policy is also one of the few areas of the transportation system where local municipalities have much direct control. Most importantly, there is already a strong case for parking reform in the absence of automated vehicles.

Toward Sustainable Urban Futures

This book advances the idea of moving beyond mobility as a platform for achieving more sustainable urban futures. The first chapter adopted the term urban recalibration as a framework for doing so. Rather than sweeping reforms or a Kuhnian paradigm shift, urban recalibration calls for a series of calculated steps aimed at a strategic longer-range vision of a city’s future, advancing principles of people-oriented development and place-making every bit as much as private car mobility, if not more. Rather than driving down sustainability metrics such as vehicle miles traveled (VMT) per capita in one fell swoop through dramatic changes, it entails a series of 1 to 2 percent recalibration “victories”—intersection by intersection, neighborhood by neighborhood—that cumulatively move beyond the historically almost singular focus on mobility, making for better communities, better environments, and better economies. With urban recalibration, change is more evolutionary than revolutionary.

The Global South

The United Nations Conference on Housing and Sustainable Urban Development met in Quito, Ecuador, in October 2016 to launch a new global commitment to sustainable urban development. Habitat III, as the conference is called, resulted in the adoption of the New Urban Agenda, which prioritizes the relationship between urbanization and sustainable development and promotes a global vision of just, safe, healthy, accessible, affordable, resilient, and sustainable cities for all. These objectives fit well with the call for planning beyond mobility. However, as the New Urban Agenda emphasizes, the challenges of sustainable urban development in the Global South can be daunting. High poverty rates and poor access to jobs and education hinder economic and social opportunities. Achieving a better balance between mobility and place might seem less important in places where there is not enough investment in mobility or place, not to mention education or other infrastructure. Nevertheless, poor design around new transportation infrastructure increases travel times, decreases safety, and encourages a shift to private cars. By ignoring the safety and comfort of pedestrians and cyclists, local governments not only treat poorer residents like second-class citizens but virtually guarantee that they will switch to cars and motorcycles as they get wealthier.

Intersecting Residential and Transportation CO2 Emissions: Metropolitan Climate Change Programs in the Age of Trump

This article uses a series of fixed-ratio projections and scenarios to explore the potential for local residential energy conservation mandates and compact growth programs to reduce locally based CO2 emissions in eleven representative US metropolitan areas. Averaged across all eleven metros, residential energy conservation mandates could reduce residential CO2 emissions in 2030 by an average of 30 percent over and above 2010 levels. In terms of implementation, residential conservation standards were found to be goal-effective, cost-effective, scale-effective, and in the case of new construction standards, reasonably resistant to local political pushback. Local compact growth programs do not perform as well. If accompanied by aggressive efforts to get drivers out of their cars, compact growth programs could reduce auto-based 2030 CO2 emissions by as much as 25 percent over and above any emissions reductions attributable to higher fuel economy standards. Unaccompanied by modal diversion programs, the stand-alone potential for local compact growth programs to reduce auto-based CO2 emissions falls into a more modest range of 0 to 7 percent depending on the metropolitan area. Based on past performance, local compact growth programs are also likely to have problems in terms of their goal- and scale-efficiency, and their potential to incur political pushback.

3 Where do bike lanes work best? a bayesian spatial model of bicycle lanes and bicycle crashes

US municipalities are introducing bicycle lanes into their roadway infrastructure to promote bicycle use, increase roadway safety and improve public health. The aim of this study was to identify specific locations where bicycle lanes, if created, could most effectively reduce crash rates. Previous research has found that bike lanes reduce crash incidence, but a lack of comprehensive (e.g., city-wide) bicycle traffic flow data has limited researchers’ ability to assess relationships at high spatial resolution and for all locations within a study region. Our unit of analysis was the street segment in Philadelphia, PA (n=37,673). We used Bayesian conditional autoregressive logit models to relate the odds that a reportable bicycle injury crash occurred on a street segment between 2011 and 2014 to characteristics of the street (street class, vehicle and bicycle traffic volume, one way, presence of streetcar tracks and bike lanes) and adjacent intersections (number of exits, stop type). Model 1 identified that crashes are 30% more likely to occur on segments with bicycle lanes (OR=1.30; 95 CI: 1.18, 1.51), perhaps due to unmeasured bicycle traffic through these locations. Model 2 included interaction terms between bicycle lanes and the other street and intersection characteristics, thereby addressing the problem of unknown bicycle traffic flows. In this model, bicycle lanes were associated with 45% reduced crash odds in streets segments adjacent to intersections with 4 exits (OR=0.55; 95% CI: 0.38; 0.80) and with 37% reduced crash odds in streets adjacent to intersections with one- or two-way stop signs (OR=0.63; 95% CI: 0.46; 0.88). The effectiveness of bicycle lanes appears to depend most substantially on the configuration of the adjacent intersections. Results also suggest locations at which the greatest absolute reduction in bicycle crash odds could occur by installing bicycle lanes.