Factors influencing the choice of shared bicycles and shared electric bikes in Beijing

AbstractChina leads the world in both public bikeshare and private electric bike (e-bike) growth. Current trajectories indicate the viability of deploying large-scale shared e-bike (e-bikeshare) systems in China. We employ a stated preference survey and multinomial logit to model the factors influencing the choice to switch from an existing transportation mode to bikeshare or e-bikeshare in Beijing. Demand is influenced by distinct sets of factors: the bikeshare choice is most sensitive to measures of effort and comfort while the e-bikeshare choice is more sensitive to user heterogeneities. Bikeshare demand is strongly negatively impacted by trip distance, temperature, precipitation, and poor air quality. User demographics however do not factor strongly on the bikeshare choice, indicating the mode will draw users from across the social spectrum. The e-bikeshare choice is much more tolerant of trip distance, high temperatures and poor air quality, though precipitation is also a highly negative factor. User demographics do play a significant role in e-bikeshare demand. Analysis of impact to the existing transportation system finds that both bikeshare and e-bikeshare will tend to draw users away from the “unsheltered modes”, walk, bike, and e-bike. Although it is unclear if shared bikes are an attractive “first-and-last-mile solution”, it is clear that e-bikeshare is attractive as a bus replacement

Safe by Design: Collecting Traveler Centric Data to Inform Safe Street Design

69A3551747111The transportation safety paradigm for urban transportation \u2013 particularly safety for those walking, cycling, and scooting \u2013 relies on counting crashes to parameterize safety. This reactive, crash-based method is limiting crashes are underreported and devoid of human perception, and their low frequency precludes testing countermeasure effectiveness. Building on diverse safety-critical fields, we hypothesize that urban transportation safety can be measured proactively with traveler biometrics, including eye and head movements, such that high readings of biometric indicators correlate with less safe areas. We collect biometric data from cyclists traversing an urban corridor with a protected, yet not continuously, cycle lane. By isolating and correlating peaks in cyclist biometric measures with infrastructure design, we develop a set of continuous variables \u2013 lateral head movements, gaze velocity, and off-mean gaze distance, both independently and as a vector \u2013 that allow for the evaluation of safe urban infrastructure proactively. The results reflect higher biometric readings correspond to less safe (i.e., unprotected) areas, indicating that safety can be measured proactively with biometric data

The Cysteine Rich Necrotrophic Effector SnTox1 Produced by Stagonospora nodorum Triggers Susceptibility of Wheat Lines Harboring Snn1

The wheat pathogen Stagonospora nodorum produces multiple necrotrophic effectors (also called host-selective toxins) that promote disease by interacting with corresponding host sensitivity gene products. SnTox1 was the first necrotrophic effector identified in S. nodorum, and was shown to induce necrosis on wheat lines carrying Snn1. Here, we report the molecular cloning and validation of SnTox1 as well as the preliminary characterization of the mechanism underlying the SnTox1-Snn1 interaction which leads to susceptibility. SnTox1 was identified using bioinformatics tools and verified by heterologous expression in Pichia pastoris. SnTox1 encodes a 117 amino acid protein with the first 17 amino acids predicted as a signal peptide, and strikingly, the mature protein contains 16 cysteine residues, a common feature for some avirulence effectors. The transformation of SnTox1 into an avirulent S. nodorum isolate was sufficient to make the strain pathogenic. Additionally, the deletion of SnTox1 in virulent isolates rendered the SnTox1 mutated strains avirulent on the Snn1 differential wheat line. SnTox1 was present in 85% of a global collection of S. nodorum isolates. We identified a total of 11 protein isoforms and found evidence for strong diversifying selection operating on SnTox1. The SnTox1-Snn1 interaction results in an oxidative burst, DNA laddering, and pathogenesis related (PR) gene expression, all hallmarks of a defense response. In the absence of light, the development of SnTox1-induced necrosis and disease symptoms were completely blocked. By comparing the infection processes of a GFP-tagged avirulent isolate and the same isolate transformed with SnTox1, we conclude that SnTox1 may play a critical role during fungal penetration. This research further demonstrates that necrotrophic fungal pathogens utilize small effector proteins to exploit plant resistance pathways for their colonization, which provides important insights into the molecular basis of the wheat-S. nodorum interaction, an emerging model for necrotrophic pathosystems

Operating at the individual level: A review of literature and a research agenda to support needs-forward models of transport resource allocation

Transportation equity is defined as the fair distribution of transportation system outcomes, costs, benefits, and services to individuals or communities. For transportation investments, plans, and projects to advance equitable outcomes, proactive equitable allocation mechanisms are necessary. Proactive equitable allocation mechanisms in transportation refer to the mathematical methods that distribute transportation system outcomes across individuals, particularly disadvantaged individuals, who are expected to benefit from the potential intervention. While existing conceptual and empirical equity literature establishes the need for proactive equity-driven transportation interventions, literature reviews on equity-focused mathematical approaches to allocate transportation system resources are limited. To this end, this literature review draws from the transportation engineering and operations research literature that focuses on the design of proactive or speculative mathematical methods through simulation and optimization to allocate transportation system outcomes in an equitable way. Through categorizing the literature based on the mathematical method first, followed by the application, we find a variety of conceptual and mathematical definitions of equity applied to an array of modes, applications, and scales of intervention. We also review the research that incorporates individual disadvantage status in determining the optimal allocation of transportation outcomes and find that many examples define broad categories of disadvantage across population groups, rather than mathematically model the behavior and needs of disadvantaged individuals. These findings are critical in laying out future research directions in equitable allocation methods that authentically center the positionalities of disadvantaged individuals, while also balancing other important transportation system objectives and public engagement strategies

Taxi Drops Off as Transit Grows amid Ride-Hailing’s Impact on Airport Access in New York

This study investigates the relationship between the introduction of ride-hailing services and 1) taxi trips; 2) AirTrain ridership; and 3) parking transactions at two major New York airports: John F. Kennedy International Airport (JFK) and LaGuardia Airport (LGA). Using monthly data that span over a decade, this study applies Bayesian structural time series analysis to examine how taxi trips, AirTrain ridership, and parking transactions have changed since the launch of UberX and Lyft, two of the most popular ride-hailing services in New York City. Results suggest that after the launch of the ride-hailing services, the number of taxi trips (both for drop-offs and pick-ups) decreased at both airports from what it would have been in the absence of ride-hailing services, with the decline being more significant for drop-offs. In contrast, AirTrain ridership continued its growing trend after the launch of UberX and Lyft. The number of parking transactions at JFK continued the mild decline that began before the launch of UberX and Lyft. Our findings indicate that high-quality transit services that connect airports with city centers and intermodal terminals could continue to serve as a crucial airport access mode amid the popularity of ride-hailing services. The findings also highlight the mismatch between taxi drop-offs and pick-ups at the airport and the potential revenue loss from parking decline. The contributions of this study are also methodological, as our study demonstrates the application of a novel statistical method to study the effect of an intervention such as ride-hailing services