The objective of this research is to scale up the capabilities of fully autonomous vehicles so that they are capable of operating in mixed-traffic urban environments (e.g., in a city such as Columbus or even New York or Istanbul). Such environments are realistic large-city driving situations involving many other vehicles, mostly human-driven. Moreover, such a car will be in a world where it interacts with other cars, humans, other external effects, and internal and external software modules. This is a prototypical CPS with which we have considerable experience over many years, including participation in the recent DARPA Urban Challenge. Even in the latter case, though, operation to date has been restricted to relatively “clean” environments (such as multi-lane highways and simpler intersections with a few other vehicles). The approach is to integrate multidisciplinary advances in software, sensing and control, and modeling to address current weaknesses in autonomous vehicle design for this complex mixed-traffic urban environment. All work will be done within a defined design-and-verification cycle. Theoretical advances and new models will be evaluated both by large-scale simulations, and by implementation on laboratory robots and road-worthy vehicles driven in real-world situations. The research address significant improvements to current methods and tools to enable a number of formal methods to move from use in limited, controlled environments to use in more complex and realistic environments. The theory, tools, and design methods that are investigated have potential application for a broad class of cyber-physical systems consisting of mobile entities operating in a semi-structured environment. This research has the potential to lead to safer autonomous vehicles and to improve economic competitiveness, the nation's transportation infrastructure, and energy efficiency. The richness of the domain means that expected research contributions can apply not only to autonomous vehicles but, also, to a variety of related cyber-physical systems such as service robots in hospitals and rescue robots used after natural disasters. The experimental research laboratory for the project is used for undergraduate and graduate courses and supports new summer outreach projects for high-school students. Research outcomes are integrated with undergraduate and graduate courses on component-based software.

The objective of this research is to study, develop and implement a comprehensive set of techniques that will eventually enable automobiles to be driven autonomously. The approach taken is to (a) address cyber-physical challenges of reliable, safe and timely operations inside the automobile, (b) tackle a range of physical conditions and uncertainties in the external environment, (c) enable real-time communications to and from the automobile to other vehicles and the infrastructure, and (d) study verification and validation technologies to ensure correct implementations. Intellectual Merits: The project seeks to make basic research contributions in the domains of safety-critical real-time fault-tolerant distributed cyber-physical platforms, end-to-end resource management, cooperative vehicular networks, cyber-physical system modeling and analysis tools, dynamic object detection/recognition, hybrid systems verification, safe dynamic behaviors under constantly changing operating conditions, and real-time perception and planning algorithms. Multiple intermediate capabilities in the form of active safety features will also be enabled. Broader Impacts: Automotive accidents result in about 40,000 fatalities and 3 million injuries every year in the USA. The global annual cost of road injuries is $518 billion. Many accidents are due to humans being distracted. Autonomous vehicles controlled by ever-vigilant cyber-physical systems can lead to significant declines in accidents, deaths and injuries. Autonomous vehicles can also offload driving chores from humans, and make time spent in automobiles more productive. Vehicular networks can help find the best possible routes to a destination in real-time. Broader impacts in this area are amplified by the project's partnerships with companies in the transportation and agricultural technology industries, and in information technology. Broader impacts are also sought through demonstrations and outreach to attract students into science and technology, and in particular to cyber-physical systems research.

This project has two closely related objectives. The first is to design and evaluate new Cyber Transportation Systems (CTS) applications for improved traffic safety and traffic operations. The second is to design and develop an integrated traffic-driving-networking simulator. The project takes a multi-disciplinary approach that combines cyber technologies, transportation engineering and human factors. While transportation serves indispensible functions to society, it does have its own negative impacts in terms of accidents, congestion, pollution, and energy consumption. To improve traffic safety, the project will develop and evaluate novel algorithms and protocols for prioritization, delivery and fusion of various warning messages so as to reduce drivers? response time and workload, prevent conflicting warnings, and minimize false alarms. To improve traffic operations, the project will focus on the design of next generation traffic management and control algorithms for both normal and emergency operations (e.g. during inclement weather and evacuation scenarios). Both human performance modeling methods and human subjects? experimental methods will be used to address the human element in this research. As the design and evaluation of CTS applications requires an effective development and testing platform linking the human, transportation and cyber elements, the project will also design and develop a simulator that combines the main features of a traffic simulator, a networking simulator and a driving simulator. The integrated simulator will allow a human driver to control a subject vehicle in a virtual environment with realistic background traffic, which is capable of communicating with the driver and other vehicles with CTS messages. Background traffic will be controlled by a realistic driver model based on our human factors research that accounts for CTS messages? impact on driver behavior. Intellectual Merits: The project explicitly considers human factors in the design and evaluation of CTS safety and operations applications, a topic which has not received adequate attention. Moreover, the proposed integrated simulator represents a first-of-a-kind simulator with unique features that can reduce the design and evaluation costs of new CTS applications. Broader Impacts: The proposed research can improve the safety, efficiency and environmental-friendless of transportation systems, which serve as the very foundation of modern societies and directly affects the quality of life. The integrated simulator will be used as a tool for teenage and elderly driver education and training, and to inspire minority, middle and high school students to pursue careers in math, science, and computer-related fields