BestMile to collaborate with NYU on the design of next-generation urban transportation systems

BestMile and the New York University will work together on how big data can inform the design of next-generation of urban transportation systems within the framework of the NSF Faculty Early Career Development (CAREER) Program projects. The project aims to provide answers to questions such as how should a service operator best deploy autonomous vehicles or inform travelers in real time to optimize service and learning potential while simultaneously acknowledging their privacy and how can private service providers best partner with government to fill the gaps in public transit systems.

The project will leverage BestMile’s expertise on autonomous vehicle systems operations, and drive innovation and entrepreneurship by defining new functional roles that mix transportation, computer science, and economics and best practices for the successful operation of autonomous vehicle in large-scale and highly congested urban areas. This will culminate in a test bed in New York City that is expected to shape a next-generation national interdisciplinary research center on “smart transit” over the next decade.

The research, led by Dr Joseph Chow, marries three theories together in order to address these new mobility problems in smart cities: dynamic resource allocation under uncertainty, agent-based machine learning, and privacy optimization in a network context. All three are necessary because transportation systems need to be optimized holistically, but data is typically obtained from multiple travelers or vehicles in operation. As such, agent learning and minimization of privacy concerns in the system optimization is needed. The methodology expands the science of inverse optimization by integrating it with dynamic network optimization with privacy control as constraints on the estimated parameters.

Full press release from BestMile: