Shared Mobility

Achieving Higher Taxi Outflows from a Congested Drop-off Lane: A Simulation-Based Policy Study

Yang, Fangyi
Gu, Weihua
Michael Cassidy
Li, Xin
Li, Tiezhu
2019

We examine special lanes used by taxis and other shared-ride services to drop-off patrons at airport and rail terminals. Vehicles are prohibited from overtaking each other within the lane. They must therefore wait in a first-in-first-out queue during busy periods. Patrons are often discharged from vehicles only upon reaching a desired drop-off area near the terminal entrance. When wait times grow long, however, some vehicles discharge their patrons in advance of that desired area. A train station in Eastern China is selected as a case study. Its FIFO drop-off lane is presently managed by...

Subsidizing Transportation Network Companies to Support Commutes by Rail

Darling, Wesley
Michael Cassidy
2024

We explore how rail transit’s first- and last-mile issue might be addressed by partnering with transportation network companies (TNCs) like Uber and Lyft. The goal is to lure high-income commuters to shift from cars to TNCs and rail. We also explore how rail and TNC partnerships can improve travel for low-income commuters who currently rely on low-frequency bus service. We parametrically test subsidizing TNC fares for feeder services in the San Francisco Bay Area inan idealized fashion. Inputs such as the residents’ value of time and vehicle ownership were taken from various local data...

Could Transportation Network Companies Help Improve Rail Commuting?

Darling, Wesley
Michael Cassidy
2024

Commuter rail is known to have a “first- and last-mile” problem (i.e., a lack of options for getting commuters to and from a rail station). The first- and last-mile dilemma creates inequalities in access. For example, high-income commuters drive to work (forgoing transit altogether), middle-income commuters drive to a rail station and pay to park, and low-income commuters rely on feeder buses or walking to reach a rail station. Transportation network companies (TNCs), like Uber and Lyft, are a viable option for connecting travelers to rail stations, especially for those who don’t own a car...

Privacy-Preserving MaaS Fleet Management

Belletti, Francois
Alexandre Bayen
2017

On-demand traffic fleet optimization requires operating Mobility as a Service (MaaS) companies such as Uber, Lyft to locally match the offer of available vehicles with their expected number of requests referred to as demand (as well as to take into account other constraints such as driver’s schedules and preferences). In the present article, we show that this problem can be encoded into a Constrained Integer Quadratic Program (CIQP) with block independent constraints that can then be relaxed in the form of a convex optimization program. We leverage this particular structure to yield a...

Spatio-temporal Road Charge: A Potential Remedy for Increasing Local Streets Congestion

Alexandre Bayen
Forscher, Teddy
2017

US population. Additionally, the emergence of large ridesourcing or transportation network companies (TNCs) totaling up to tens of thousands of registered drivers in single cities (all using the same routing app), there is further consolidation. Across the US, this has led to new or increased congestion patterns that are progressively asphyxiating local streets due to so-called “cut-through traffic.” As neighborhoods have started to realize this, private citizens have begun to resist, by trying to sabotage or trick the apps, or shaming the through traffic through opinion articles, and news...

Resiliency of Mobility-as-a-Service Systems to Denial-of-Service Attacks

Thai, Jérôme
Yuan, Chenyang
Alexandre Bayen
2018

Mobility-as-a-Service (MaaS) systems, such as ride-sharing services, have expanded very quickly over the past years. However, the popularity of MaaS systems make them increasingly vulnerable to denial-of-service (DOS) attacks, in which attackers attempt to disrupt the system to make it unavailable to the customers. Expanding on an established queuing-theoretical model for MaaS systems, attacks are modeled as a malicious control of a fraction of vehicles in the network. We then formulate a stochastic control problem that maximizes the passenger loss in the network in steady state, and solve...

To Pool or Not to Pool? Understanding the Time and Price Tradeoffs of OnDemand Ride Users – Opportunities, Challenges, and Social Equity Considerations for Policies to Promote Shared-Ride Services

Susan Shaheen
Lazarus, Jessica
Caicedo, Juan
Alexandre Bayen
2021

On-demand mobility services including transportation network companies (also known as ridesourcing and ridehailing) like Lyft and Uber are changing the way that people travel by providing dynamic mobility that can supplement public transit and personal-vehicle use. However, TNC services have been found to contribute to increasing vehicle mileage, traffic congestion, and greenhouse gas emissions. Pooling rides ⎯ sharing a vehicle by multiple passengers to complete journeys of similar origin and destination ⎯ can increase the average vehicle occupancy of TNC trips and thus mitigate some of...

To Pool or Not to Pool? Understanding Opportunities, Challenges, and Equity Considerations to Expanding the Market for Pooling

Lazarus, Jessica
Caicedo, Juan
Alexandre Bayen
Susan Shaheen
2021

On-demand mobility services such as bikesharing, scooter sharing, and transportation network companies (TNCs, also known as ridesourcing and ridehailing) are changing the way that people travel by providing dynamic, on-demand mobility that can supplement public transit and personal-vehicle use. Adoption of on-demand mobility has soared across the United States and abroad, driven by the flexibility and affordability that these services offer, particularly in urban areas where population density and land use patterns facilitate a reliable balance of supply and demand. The growth of app-based...

Guest Editorial Special Issue on Modeling Dynamic Transportation Networks in the Age of Connectivity, Autonomy and Data

Savla, Ketan
Du, Lili
Samaranayake, Samitha
Ban, Xuegang Jeff
Alexandre Bayen
2022

The recent emergence of new technologies and systems such as connected and automated vehicles (CAVs), novel incentive and routing platforms, and shared mobility services is making a significant impact on traffic flow in road networks. The rapid development of these innovations, powered by new capabilities in data collection, communication, and vehicle autonomy raises both great opportunities and new challenges for managing and controlling the transportation network efficiently. It is thus imperative to integrate the emerging systems into a dynamic transportation network analysis, and to...

The Impact of the Sharing Economy on Latent Individual Modal Preference

Schade, Maitagorri Helene
Elizabeth Deakin
Cervero, Robert
Joan Walker
2017

Mobility patterns in our cities are changing with the onset of shared mobility services. However, publicly available information on the use of shared mobility services is lagging behind. This study set out to fill this data gap by gathering web-based travel diary survey from carsharing and Transportation Network Company (TNC) users in the San Francisco Bay Area. Respondents were screened to be regular users of shared mobility services. The shared use reported in our sample was primarily car sharing and TNC, with bike sharing not being reported enough to be studied here. Our analysis drew...