The objective of this research is to develop technologies to improve the efficiency and safety of the road transportation infrastructure. The approach is to develop location-based vehicular services combining on-board automotive computers, in-car devices, mobile phones, and roadside monitoring/surveillance systems. The resulting vehicular Cyber Physical Systems (CPS) can reduce travel times with smart routing, save fuel and reduce carbon emissions by determining greener routes and commute times, improve safety by detecting road hazards, change driving behavior using smart tolling, and enable measurement-based insurance plans that incentivize good driving.
This research develops distributed algorithms for predictive travel delay modeling, feedback-based routing, and road hazard assessment. It develops privacy-preserving protocols for capturing and analyzing data and using it for tasks such as congestion-aware tolling. It also develops a secure macro-tasking software run-time substrate to ensure that algorithms can be programmed centrally without explicitly programming each node separately, while ensuring that it is safe to run third-party code. The research focuses on re-usable methods that can benefit multiple vehicular services, and investigates which lessons learned from this vehicular CPS effort generalize to other situations.
Road transportation is a grand challenge problem for modern society, which this research can help overcome. Automobile vendors, component developers, and municipal authorities have all shown interest in deployment. The education plan includes outreach to local K-12 students and a new undergraduate course on transportation from a CPS perspective, which will involve term projects using the data collected in the project
