No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

We propose a framework for planning in unknown dynamic environments with probabilistic
safety guarantees using conformal prediction. Particularly, we design a model predictive …

We propose pro-social control strategies for connected automated vehicles (CAVs) to
mitigate jamming waves in mixed-autonomy multi-lane traffic, resulting from car-following …

We focus on decentralized navigation among multiple non-communicating rational agents at
{\em uncontrolled} intersections, ie, street intersections without traffic signs or signals …

Connected and automated vehicles (CAVs) have emerged as a potential solution to the
future challenges of developing safe, efficient, and eco-friendly transportation systems …

Despite the structure of road environments, imposed via geometry and rules, traffic flows
exhibit complex multiagent dynamics. Reasoning about such dynamics is challenging due to …

Cooperative coordination at unsignalized road intersections, which aims to improve the
driving safety and traffic throughput for connected and automated vehicles (CAVs), has …

We focus on the problem of analyzing multiagent interactions in traffic domains.
Understanding the space of behavior of real-world traffic may offer significant advantages for …

Smooth and safe speed planning is imperative for the successful deployment of autonomous
vehicles. This paper presents a mathematical formulation for the optimal speed planning of …