Connected Cities for Smart Mobility toward Accessible and Resilient Transportation
As transportation technology continues to rapidly evolve and develop, New York City is rapidly approaching a world where autonomous vehicles are part and parcel of the urban mobility landscape. A
C2SMART researchers developed a more efficient, secure, blockchain-based system to story mobility data on a distribute ledger. To store this data at scale, researchers leverage InterPlanetary File System (OPFS), a scalable distributed peer-to-peer data storage system, and develop efficient consensus algorithms to prevent users from injecting malicious or fake trajectories into the ledger.
Inappropriate lane changes are responsible for one-tenth of all accidents, due to human drivers’ inaccurate estimation and prediction of the surrounding traffic, illegal maneuver, and inefficient driving skill. Autonomous lane changing is regarded as a solution to reduce these human errors. At present, there are many obstacles to developing automated lane-changing technology, including interactions between vehicles, complex routing choice, and interactions between vehicles and the environment. Building on our prior work on lane keeping and lane changing, this collaborative research project aims to take a significant step forward to develop innovative solutions for autonomous lane change maneuvers.
An NSF project named “study of driving volatility in connected and cooperative vehicle systems” aims at extracting driving volatility, characterized by hard acceleration/braking, jerky movements, sharp lane changes or turns, and abnormally high speeds in a connected vehicle environment. The objective of this project is to model computationally efficient algorithms for predicting driver actions and volatility using information about their prior behaviors combined with positions and motions obtained via wireless communications.
The NYCDOT Team (NYCDOT and C2SMART) will assist the USDOT in understanding and enabling Cooperative Driving for Advanced Connected Vehicles (CD for ACV) in New York City. In partnership with the USDOT, NYCDOT will identify an area in the CV Pilot site as a location to support Advanced Connected Vehicles (ACVs) to better understand the role of infrastructure in supporting and enabling connected driving in an urban environment.
C2SMART researchers are working in partnership with Noblis to provide technical and management support for the ITS Deployment Evaluation program by populating and providing analysis of the ITS Benefits, Costs and Lessons Learned/Best Practices for an ITS Deployment Database. Additionally, C2SMART provides technical and program support for the ITS Deployment Tracking Survey and is providing technical support for modal collaboration on Evidence Based Decision Making (EBDM) to accelerate deployment.
The overall scope of the project is to assess use cases where freeway operations strategies could be improved through the transmission of data between a traffic management system (TMS) and the larger cooperative automated transportation (CAT) system (either directly or through a third party). This assessment should (1) spur development of enhanced and new operational strategies and (2) help agencies justify gaining access to additional CAT data.
As part of USDOT’s Connected Vehicle Project, C2SMART researchers at New York University – in collaboration with NYCDOT and industry partners JHK and Harman – recruited volunteer participants with vision disabilities via local and national organizations to help conduct field tests of a phone application, PED-SIG, which could improve mobility of pedestrians with vision disabilities to navigate safely and independently through New York City.
In this project, the research team will propose a simulation-based approach for the evaluation of traffic control algorithms that will utilize CV technologies. Given the ongoing CV pilot deployment in NYC, the proposed project will tie in to the objectives set out to be achieved as a part of the NYC CV pilot. The City College of New York (CCNY) team will work with NYU and UW researchers to test the models and algorithms in microsimulation and hardware-in-the loop simulations on a NYC-specific network.
Autonomous mobility must be evaluated under more ambitious and holistic standards. This project aims to develop a Responsible Autonomous Mobility framework.