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Using data derived from 597 face-to-face interviews with ride-hailing users in Chengdu (China), we examined the influence of ride-hailing on travel frequency and mode choice and further analyzed what the main determinants for these are.
The growth of app-based ridesharing, microtransit, and TNCs presents a unique opportunity to reduce congestion, energy use, and emissions through reduced personal vehicle ownership and increased vehicle occupancy, the latter of which is largely dependent on the decisions of individual travelers to pool or not to pool. This research provides key insights into the policy levers that could be employed to reduce vehicle miles traveled and emissions by incentivizing the use of pooled on-demand ride services and public transit. We employ a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San FranciscoBay Area) to examine the opportunities and challenges for drastically expanding the market for pooling, taking into account the nuances in emergent travel behavior and demand sensitivity across on-demand mobility options.
Even as ride-hailing has become ubiquitous in most urban areas, its impacts on individual travel are still unclear. This includes limited knowledge of demand characteristics (especially for pooled rides), travel modes being substituted, types of activities being accessed, as well as possible trip induction effects. The current study contributes to this knowledge gap by investigating ridehailing experience, frequency, and trip characteristics through two multi-dimensional models estimated using data from the Dallas-Fort Worth Metropolitan Area. Ride-hailing adoption and usage are modeled as functions of unobserved lifestyle stochastic latent constructs, observed transportation-related choices, and sociodemographic variables. The results point to low residential location density and people’s privacy concerns as the main deterrents to pooled ridehailing adoption, with non-Hispanic Whites being more privacy sensitive than individuals of other ethnicities.
TNCs provide on-demand mobility service that either complements or competes with transit services. This article studies how TNCs influence changes in urban travel patterns as well as energy and environmental implications.
Existing studies do not distinguish between connected and autonomous vehicles while examining their effects of the driving environment. This article conducts studies with distinguished vehicle types to establish a framework of several adoption scenarios to analyze the stability of the resulting traffic stream. The results demonstrated the ability of connected and autonomous vehicles to improve string stability. The study also found that automation was more effective at preventing shockwave formation and propagation. Under certain model scenarios, potential throughput also increased.
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