As cities move toward “smart city” paradigms they will engage more and more with private mobility operators. Examples of these efforts include the Mobility Data Specification from LA DOT. Data sharing for such ecosystems require mechanisms to preserve the competitive privacy of operators’ operational policies. In our latest paper, we develop one such mechanism using concepts of constrained entropy maximization and inverse optimization constraints to ensure synthetic queries exhibit certain desirable features. This work will be presented at ISTTT23 in Lausanne and is funded by NSF CMMI-1652735.
Susan will be joining Elisabetta Cherchi’s group to work on electric vehicle shared mobility systems starting this fall. We wish her all the best!
Recent news suggest the importance of studying the roles of public transit and mobility-on-demand services in competition and cooperation. We developed an integrated dynamic platform that can incorporate transit rides as a leg in the MOD service and showed that for certain scenarios (such as Manhattan trips from Long Island via LIRR) the MOD services will naturally converge to providing feeder access because it is more cost-effective. Joint work (NYU/LISER) with Tai-Yu Ma, Saeid Rasulkhani, and Sylvain Klein. Funding support from the Luxembourg National Research Fund (INTER/MOBILITY/17/11588252) and NSF CMMI-1634973.
A major issue in the development of reinforcement learning algorithms for autonomous vehicles is the need to make them reflect the preferences of travelers better. One of the ways to do that is to incorporate user schedule preferences under reliability-based route selection criteria into the learning mechanism. This work led by Jinkai Zhou investigates the potential of such an integration. We used data collected from queries from Google Maps to mimic airport shuttle services to train a multi-armed bandit algorithm to see how it is impacted by the consideration of on-time arrival reliability. The work was funded by NSF CMMI-1652735.
Postdoc opportunity: Saif Eddin Jabariand I are looking to hire a jointly supervised postdoc at NYU Abu Dhabi to start as early as this fall, in the area of OR/transportation systems with interests in MaaS/shared mobility/multimodal networks. If interested, please feel free to reach out to me (firstname.lastname@example.org).
Mobility-as-a-Service will only work if cities can evaluate markets of multiple operators, and consider not just ridership but also the incentives for transferring costs (fares, access/egress, wait time, in-vehicle time) between operators and travelers. Saeid Rasulkhani and Dr. Chow just published a new modeling framework that explicitly considers these trade-offs, developed with funding from NSF (CMMI-1634973).
Link to paper: dx.doi.org/10.1016/j.trb.2019.04.008
Research from the BUILT lab on “Doubly-constrained rebalancing for one-way electric carsharing systems with capacitated charging stations”, from Ted Pantelidis, Li Li (NYUAD), Tai-Yu Ma (LISER), Joseph Chow, and Saif Jabari (NYUAD) has been accepted for presentation at the INFORMS TSL Workshop in Vienna. The workshop’s theme is ““Transportation in the sharing economy”. The project is funded by C2SMART with data shared by BMW ReachNow.
Preliminary work for this project was previously presented at the 98th Annual Meeting of the TRB in Washington DC.
The work from student researchers Saeid Rasulkhani and Ted Pantelidis will be presented at the Tenth Triennial Symposium on Transportation Analysis (TRISTAN X) on June 17-21 at Hamilton Island near the Great Barrier Reef in Australia. The NSF-funded (CMMI-1634973) research is entitled “A many-to-many stable matching cost allocation model for multimodal Mobility-as-a-Service”, where we develop a novel methodology to extend earlier work to handle cost allocation analysis for multiple operators splitting a traveler’s trip. This ongoing work has resulted in major breakthroughs in facilitating design of integrated services between different operators and transport agencies within a true “Mobility-as-a-Service” setting, providing to them a tool like how the classic “traffic assignment problem” helped roadway planning in the last few decades. We are finalizing our computational experiments and will be submitting this to a journal for publication.
Nick’s thesis work, which involves simulation of en-route transfers to better understand their impacts under different transit operating strategies, was recently featured in a TEDx TUM talk by Tommaso Gecchelin, a co-founder of NEXT Future Transportation.
Nick Caros was a MS student in the Transportation Planning & Engineering program in the Department of Civil & Urban Engineering. He worked as a research assistant in the BUILT lab through funding from C2SMART and completed his MS degree with a thesis in January 2019. He has one conference proceeding and 2 manuscripts under peer review in international journals from his time here.
Brian Yueshuai He and Prof. Chow’s work on “Optimal privacy control for transport network data sharing” has been accepted for a poster at ISTTT 23, the bi-annual international symposium on transportation and traffic theory.
The International Symposium on Transportation & Traffic Theory series is since its first issue in 1959 the main gathering for the world’s transportation and traffic theorists, and for those who are interested in gaining (or contributing to) a deeper understanding of the field. The Symposium deals with both scientific and operational aspects of transportation and traffic, spanning all modes of transport, and covering freight as well as private and public transport.
In more 30 podium presentations the attendants will be informed about the latest scientific insights on transportation and traffic theory. For more information about the symposium, see here.