The goal of this research is to develop fundamental theory, efficient algorithms, and realistic experiments for the analysis and design of safety-critical cyber-physical transportation systems with human operators. The research focuses on preventing crashes between automobiles at road intersections, since these account for about 40% of overall vehicle crashes. Specifically, the main objective of this work is to design provably safe driver-assist systems that understand driver?s intentions and provide warnings/overrides to prevent collisions. In order to pursue this goal, hybrid automata models for the driver-vehicles-intersection system, incorporating driver behavior and performance as an integral part, are derived from human-factors experiments. A partial order of these hybrid automata models is constructed, according to confidence levels on the model parameters. The driver-assist design problem is then formulated as a set of partially ordered hybrid differential games with imperfect information, in which games are ordered according to parameter confidence levels. The resulting designs are validated experimentally in a driving simulator and in large-scale computer simulations. This research leverages the potential of embedded control and communication technologies to prevent crashes at traffic intersections, by enabling networks of smart vehicles to cooperate with each other, with the surrounding infrastructure, and with their drivers to make transportation safer, more enjoyable, and more efficient. The work is based on a collaboration among researchers in formal methods, autonomous control, and human factors who are studying realistic and provably correct warning/override algorithms that can be readily transitioned to production vehicles.

The computing landscape is a richly-heterogeneous space including both fixed and mobile nodes with a large variety of sensing, actuation and computational capabilities (including mobile devices, home electronics, taxis, robotic drones, etc.). Cyber-physical applications built on these devices have the potential to gather data on, analyze, and adapt to or control a range of environments. The challenge, however, is that Cyber-Physical Systems (CPSs) are difficult to program, and even more difficult to incorporate from one deployment to another, or to dynamically manage as nodes availability changes. Thus, CPS applications are too often programmed in a brittle fashion that impedes their ability to efficiently use available compute/sense/actuate resources beyond a one-shot deployment. In response, this project is improving CPS design and control in four primary thrusts. First, the project is developing CPSISA, an abstraction layer or intermediate representation to facilitate CPS applications expressing their compute/sense/actuate requirements to lower-level mapping and management layers. Second, the project is exploring methods of providing a Device Attribute Catalog (DAC) that summarizes a region?s available CPS nodes and their capabilities. Third, this research is improving and exploiting the ability to model, predict, and control the mobility of CPS nodes. When some CPS nodes are mobile, the accuracy and performance of a CPS application fundamentally is a function of where nodes will be positioned at any moment in time. This work exploits both static statistical coverage analysis and dynamic prediction and interpolation. Fourth, using CPSISA, DAC, and other resources as input, the team is developing tools to statically or dynamically optimize mappings of CPS applications onto available resources. To test ideas in a detailed and concrete manner, two applications are being studied and deployed. First, the FireGuide application for emergency response assistance uses groups of mobile/robotic nodes for guiding first responders in building fires. Second, a Regional Traffic Management (RTM) application demonstrates ideas at the regional level and will explore CPS scenarios for automobile traffic sensing and dynamic toll pricing. The proposed research program has the potential for broad societal impact. Studies that improve how building emergencies are handled will improve emergency response safety both for occupants and for first responders around the country. Likewise, the deployment plans regarding regional traffic management will improve traffic patterns, fuel efficiency and quality-of-life for commuters across the United States. The research team is distributing the CPSISA, CPSMap, and CPSDyn software frameworks to allow other researchers and developers to make use of them. Extensive industry collaborations foster effective technology transfer. Finally, the project continues and broadens the PIs? prior track records for undergraduate research advising and for mentoring women students and members of under-represented minority groups.

The computing landscape is a richly-heterogeneous space including both fixed and mobile nodes with a large variety of sensing, actuation and computational capabilities (including mobile devices, home electronics, taxis, robotic drones, etc.). Cyber-physical applications built on these devices have the potential to gather data on, analyze, and adapt to or control a range of environments. The challenge, however, is that Cyber-Physical Systems (CPSs) are difficult to program, and even more difficult to incorporate from one deployment to another, or to dynamically manage as nodes availability changes. Thus, CPS applications are too often programmed in a brittle fashion that impedes their ability to efficiently use available compute/sense/actuate resources beyond a one-shot deployment. In response, this project is improving CPS design and control in four primary thrusts. First, the project is developing CPSISA, an abstraction layer or intermediate representation to facilitate CPS applications expressing their compute/sense/actuate requirements to lower-level mapping and management layers. Second, the project is exploring methods of providing a Device Attribute Catalog (DAC) that summarizes a region?s available CPS nodes and their capabilities. Third, this research is improving and exploiting the ability to model, predict, and control the mobility of CPS nodes. When some CPS nodes are mobile, the accuracy and performance of a CPS application fundamentally is a function of where nodes will be positioned at any moment in time. This work exploits both static statistical coverage analysis and dynamic prediction and interpolation. Fourth, using CPSISA, DAC, and other resources as input, the team is developing tools to statically or dynamically optimize mappings of CPS applications onto available resources. To test ideas in a detailed and concrete manner, two applications are being studied and deployed. First, the FireGuide application for emergency response assistance uses groups of mobile/robotic nodes for guiding first responders in building fires. Second, a Regional Traffic Management (RTM) application demonstrates ideas at the regional level and will explore CPS scenarios for automobile traffic sensing and dynamic toll pricing. The proposed research program has the potential for broad societal impact. Studies that improve how building emergencies are handled will improve emergency response safety both for occupants and for first responders around the country. Likewise, the deployment plans regarding regional traffic management will improve traffic patterns, fuel efficiency and quality-of-life for commuters across the United States. The research team is distributing the CPSISA, CPSMap, and CPSDyn software frameworks to allow other researchers and developers to make use of them. Extensive industry collaborations foster effective technology transfer. Finally, the project continues and broadens the PIs? prior track records for undergraduate research advising and for mentoring women students and members of under-represented minority groups.

This project proposes a cross-layer framework in which vehicular wireless networking and platoon control interact with each other to tame cyber-physical uncertainties. Based on the real-time capacity region of wireless networking and the physical process of vehicle movements, platoon control selects its control strategies and the corresponding requirements on the timeliness and throughput of wireless data delivery to optimize control performance. Based on the requirements from platoon control, wireless networking controls co-channel interference and adapts to cyber-physical uncertainties to ensure the timeliness and throughput of single-hop as well as multi-hop broadcast. For proactively addressing the impact of vehicle mobility on wireless broadcast, wireless networking also leverages input from platoon control on vehicle movement prediction. In realizing the cross-layer framework, wireless scheduling ensures agile, predictable interference control in the presence of cyber-physical uncertainties. If successful, this project will lead to a general and rigorous framework for wireless vehicular cyber-physical network control that will enable safe, efficient, and clean transportation. The principles and techniques for taming cyber-physical uncertainties will provide insight into other application domains of wireless networked sensing and control such as unmanned aerial vehicles and smart power grids. This project will also develop integrative research and education on wireless cyber-physical systems through multi-level, multi-component educational activities.

The objective of this inter-disciplinary research is to develop new technologies to transform the streets of a city into a hybrid transportation/communication system, called the Intelligent Road (iRoad), where autonomous wireless devices are co-located with traffic signals to form a wireless network that fuses real-time transportation data from all over the city to make a wide range of new applications possible. The approach is to build new capacities of quantitative bandwidth distribution, rate/delay assurance, and location-dependent security on a pervasive wireless platform through distributed queue management, adaptive rate control, and multi-layered trust. These new capacities lead to transformative changes in the way the transportation monitoring and control functions are designed and operated. Many technical challenges faced by the iRoad system are open problems. New theories/protocols developed in this project will support sophisticated bandwidth management, quality of service, multi-layered trust, and information fusion in a demanding environment where critical transportation functions are implemented. Solving these fundamental problems advances the state of the art in both wireless technologies and transportation engineering. The research outcome is likely to be broadly applicable in other wireless systems. The economic and societal impact of the iRoad system is tremendous at a time when the country is modernizing its ailing transportation infrastructure. It provides a pervasive communication infrastructure and engineering framework to build new applications such as real-time traffic map, online best-route query, intelligent fuel-efficient vehicles, etc. The research results will be disseminated through course materials, academic publication, industry connection, and presentations at the local transportation department.