11 Search Results

Ridesharing has become an increasingly popular transportation method over the past decade. Transportation network companies such as Uber and Lyft generally provide two types of rideshare services: personal rideshare, in which users ride alone or with individuals they know, and pooled rideshare, in which users ride with passengers they do not know but share similar routes. Pooled rideshare is capable of reducing energy consumption and traffic in the transportation system in comparison to personal rideshare. Despite the growth in trip volume, ridesharing usage is still low compared to other popular transportation methods in the U.S., particularly traveling in one’s ownmore » personal vehicle. Furthermore, pooled rideshare usage is lower than personal rideshare. To understand riders’ preferences, a national survey (N = 2884) was conducted in the U.S. to investigate users’ choice behaviors in rideshare services examining personal versus pooled rideshare. Each survey respondent completed 20 stated-preference scenarios where participants choose between a personal or pooled rideshare option. Based on the responses, a mixed logit model was developed to capture the choice behavior preferences of the participants. The model unveiled the impact of demographic and trip attribute variables on users’ rideshare preferences. The discussion encompassed insights into demographic backgrounds and trip attributes, accompanied by a set of policy recommendations aimed at enhancing future pooled rideshare utilization.« less

Pooled ridesharing offers on-demand, one-way, cost-effective transportation for passengers traveling in similar directions via a shared vehicle ride with others they do not know. Despite its potential benefits, the adoption of pooled rideshare remains low in the United States. This exploratory study aims to evaluate potential service improvements and features that may increase users’ willingness to adopt the service. The study analyzed transportation behaviors, rideshare preferences, and willingness to adopt pooled rideshare services among 8296 U.S. participants in 2025, building on findings from a 2021 nationwide survey of 5385 U.S. participants. The study incorporated 77 actionable items developed from themore » results of the 2021 survey to assess whether addressing specific user-generated topics such as safety, reliability, convenience, and privacy can improve pooled rideshare use. A side-by-side comparison of the 2021 and 2025 data revealed shifts in transportation behavior, with personal rideshare usage increasing from 22% to 28%, public transportation from 21% to 27%, and pooled rideshare from 6% to 8%, while personal vehicle (79%) use remained dominant. Participants rated features such as driver verification (94%), vehicle information (93%), peak time reliability (93%), and saving time and money (92–93%) as most important for improving rideshare services. A pre-to-post analysis of willingness to use pooled rideshare utilizing the actionable items as per respondents’ preferences showed improvement: “definitely will” increased from 15.9% to 20.1% and “probably will” rose from 35.6% to 47.7%. These results suggest that well-targeted service improvements may meaningfully enhance pooled rideshare acceptance. This study offers practical guidance for Transportation Network Companies (TNCs) and policymakers aiming to improve pooled rideshare as well as potential future research opportunities.« less

Building on our prior research with a national survey sample of 5385 US participants, the Pooled Rideshare Acceptance Model (PRAM) was built upon two factor analyses. This exploratory study extends the PRAM framework using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) to examine how 16 demographic variables influence and interact with the acceptance of Pooled Rideshare (PR), filling a gap in understanding user segmentation and personalization. Using a national sample of 5385 US participants, this methodological approach allowed for the evaluation of how PRAM variables such as safety, privacy, service experience, and environmental impact vary across diverse groups, includingmore » gender, generation, driver’s license, rideshare experience, education level, employment status, household size, number of children, income, vehicle ownership, and typical commuting practices. Factors such as convenience, comfort, and passenger safety did not show significant differences across the moderators, suggesting their universal importance across all demographics. Furthermore, geographical differences did not significantly impact the relationships within the model, suggesting consistent relationships across different regions. The findings highlight the need to move beyond a “one size fits all” approach, demonstrating that tailored strategies may be crucial for enhancing the adoption and satisfaction of PR services among various demographic groups. The analyses provide valuable insight for policymakers and rideshare companies looking to optimize their services and increase user engagement in PR.« less

This manuscript provides actionable recommendations to enhance user satisfaction and address existing barriers regarding pooled rideshare (PR) in the United States. Despite PR’s intended benefits, such as reduced traffic congestion and cost savings, its adoption remains limited. To identify these actionable items, a U.S. nationwide survey with 5385 participants explored transportation preferences, barriers, and motivators for PR use in the summer of 2021. First, two factor analyses were conducted. The first factor analysis identified the five factors associated with one’s willingness to consider PR (time/cost, traffic/environment, safety, privacy, and service experience). The second factor analysis revealed the four factors relatedmore » to ways to optimize one’s PR experience (comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety). Privacy concerns, for instance, were found to reduce the likelihood of PR adoption by 77%, and convenience had the potential to increase it by 156%. A structural equation model evaluated the relationships among these nine key factors influencing PR usage to develop the Pooled Rideshare Acceptance Model (PRAM). The privacy, safety, trust service, and convenience factors each had a significant large effect (Cohen’s f² > 0.35) on the model. PRAM was extended using multigroup analyses to reveal the nuanced impact of 16 demographics, including gender, generation, rideshare experience, etc., highlighting the need for tailored strategies to improve PR acceptance through the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMAs). Multiple workshops were held with diverse audiences to translate the team’s findings to date into 84 actionable recommendations, categorized across topical areas like safety, routing, driver and passenger selection, user education, etc. These findings are a foundation for a future study to determine which items resonate with different user groups. In the meantime, the actional items serve as a user-driven resource for policymakers, transportation network companies, and researchers, offering a roadmap to potential improvements to PR services to address existing concerns with the goal of increasing the usage of PR.« less

This study analyzes various human factors considerations in estimating discounts for pooled rideshare trips. The discounts are utilized in an optimization-based rideshare assignment strategy (proactive strategy) and compared against each other, as well as a heuristic strategy attempting to replicate current real-world pooling rates. Simulations within Austin, Texas and Greenville, South Carolina, reveal the proactive strategy’s ability to increase average vehicle occupancy by 0.23 persons/mile in Austin and 0.52 persons/mile in Greenville. A significant ability to decrease trip rejections and increase profitability is also observed. Finally, the strengths of particular combinations of factors are discussed relative to their effectiveness inmore » each region.« less

Ridesharing has become an increasingly prevalent form of transportation. Although transportation network companies such as Uber and Lyft initially started as a personal rideshare service where individuals ride alone or with people they know, rideshare services have been expanded to pooled rideshare—a dynamic rideshare system where an individual rides with passengers they do not know. Despite the growth in rideshare services worldwide, the use of pooled rideshare in the U.S.A. is relatively low compared to other forms of transportation. A national U.S. survey (N = 5385) was conducted to investigate reasons why individuals are willing or unwilling to consider pooledmore » rideshare. Exploratory and confirmatory factor analyses were performed, where the exploratory factor analysis suggests five factors, specifically, service experience, time/cost, traffic/environment, privacy, and safety. Model fit indices of the confirmatory factor analysis verified that these five factors can represent the factors behind riders’ willingness to consider pooled rideshare. Furthermore, a binomial logistic regression was conducted to explore how the five factors influence riders’ willingness to consider pooled rideshare. The three factors that influence riders’ willingness to consider pooled rideshare were service experience (B = 1.05), traffic/environment (B = .38), and time/cost (B = .26), while a lack of privacy (B = −1.46) can be a deterrent for pooled rideshare. Safety is important for those who are both willing and unwilling to consider the use of pooled rideshare. Understanding these factors is important for the future of pooled rideshare services in the U.S.A.« less

Rideshare use has grown significantly, beginning with solo riders and evolving to pooled rideshare. Pooled rideshare involves sharing a ride with stranger(s). Despite the growth in rideshare services worldwide, the use of pooled rideshare in the U.S. is relatively low within all rideshare trips and compared to other forms of transportation, e.g., driving one's personal vehicle. A national survey of 5,385 individuals was conducted to identify factors influencing riders' willingness to consider pooled rideshare. Exploratory and confirmatory factor analyses were performed. The survey results indicated five factors: service experience, time/cost, traffic/environment, privacy, and safety. Understanding these factors is crucial formore » the future of dynamic ridesharing services in the U.S.« less

Due to the advancements in real-time information communication technologies and sharing economies, rideshare services have gained significant momentum by offering dynamic and/or on-demand services. Rideshare service companies evolved from personal rideshare, where riders traveled solo or with known individuals, into pooled rideshare (PR), where riders can travel with one to multiple unknown riders. Similar to other shared economy services, pooled rideshare is beneficial as it efficiently utilizes resources, resulting in reduced energy usage, as well as reduced costs for the riders. However, previous research has demonstrated that riders have concerns about using pooled rideshare, especially regarding personal safety. A U.S.more » national survey with 5385 participants was used to understand human factor-related barriers and user preferences to develop a novel Pooled Rideshare Acceptance Model (PRAM). This model used a covariance-based structural equation model (CB-SEM) to identify the relationships between willingness to consider PR factors (time/cost, privacy, safety, service experience, and traffic/environment) and optimizing one’s experience of PR factors (vehicle technology/accessibility, convenience, comfort/ease of use, and passenger safety), resulting in the higher-order factor trust service. We examined the factors’ relative contribution to one’s willingness/attitude towards PR and user acceptance of PR. Privacy, safety, trust service, and convenience were statistically significant factors in the model, as were the comfort/ease of use factor and the service experience, traffic/environment, and passenger safety factors. The only two non-significant factors in the model were time/cost and vehicle technology/accessibility; it is only when a rider feels safe that individuals then consider the additional non-significant variables of time, cost, technology, and accessibility. Privacy, safety, and service experience were factors that discouraged the use of PR, whereas the convenience factor greatly encouraged the acceptance of PR. Despite the time/cost factor’s lack of significance, individual items related to time and cost were crucial when viewed within the context of convenience. This highlights that while user perceptions of privacy and safety are paramount to their attitude towards PR, once safety concerns are addressed, and services are deemed convenient, time and cost elements significantly enhance their trust in pooled rideshare services. This study provides a comprehensive understanding of user acceptance of PR services and offers actionable insights for policymakers and rideshare companies to improve their services and increase user adoption.« less

The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals riding alone or with acquaintances) initially dominated the market, the popularity of pooled ridesharing (individuals sharing rides with people they do not know) has grown globally. However, pooled ridesharing remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. Based on a large, national U.S. survey (N = 5385), the results of exploratory and confirmatory factormore » analyses suggested that four key factors influence riders’ willingness to consider pooled ridesharing: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. A binomial logistic regression was conducted to determine how the four factors influence one’s willingness to consider pooled ridesharing. The two factors that positively influence riders’ willingness to consider pooled ridesharing are vehicle technology/accessibility (B = 1.10) and convenience (B = 0.94), while lack of passenger safety (B = –0.63) and comfort/ease of use (B = –0.17) are pooled ridesharing deterrents. Understanding user-centered design and service factors are critical to increase the use of pooled ridesharing services in the future.« less

Connected and automated vehicles (CAVs) can plan and actuate control that explicitly considers performance, system safety, and actuation constraints in a manner more efficient than their human-driven counterparts. In particular, eco-driving is enabled through connected exchange of information from signalized corridors that share their upcoming signal phase and timing (SPaT). This is accomplished in the proposed control approach, which follows first principles to plan a free-flow acceleration-optimal trajectory through green traffic light intervals by Pontryagin's Minimum Principle in a feedback manner. Urban conditions are then imposed from exogeneous traffic comprised of a mixture of human-driven vehicles (HVs) - as wellmore » as other CAVs. As such, safe disturbance compensation is achieved by implementing a model predictive controller (MPC) to anticipate and avoid collisions by issuing braking commands as necessary. The control strategy is experimentally vetted through vehicle-in-the-loop (VIL) of a prototype CAV that is embedded into a virtual traffic corridor realized through microsimulation. Up to 36% fuel savings are measured with the proposed control approach over a human-modelled driver, and it was found connectivity in the automation approach improved fuel economy by up to 26% over automation without. Additionally, the passive energy benefits realizable for human drivers when driving behind downstream CAVs are measured, showing up to 22% fuel savings in a HV when driving behind a small penetration of connectivity-enabled automated vehicles.« less