ITS Berkeley

The internationalization of policy regimes and the reorganization of the state have provided new opportunities for cities to bypass nation-state structures and work with other cities internationally. This provides greater opportunity for cities to learn from each other and could be an important stimulus to the transfer of policies across the globe. Few studies exist however which focus on the processes that shape the search for policy lessons and how they are affected by the institutional context within which they are conducted. This paper describes research conducted in the field of urban...

The proliferation of connected automated vehicles represents an unprecedented opportunity for improving driving efficiency and alleviating traffic congestion. However, existing research fails to address realistic multi-lane highway scenarios without assuming connectivity, perception, and control capabilities that are typically unavailable in current vehicles. This paper proposes a novel AI system that is the first to improve highway traffic efficiency compared with human-like traffic in realistic, simulated multi-lane scenarios, while relying on existing connectivity, perception, and...

We propose a modular modeling framework designed to enhance the capture and validation of uncertainty in autonomous vehicle (AV) trajectory prediction. Departing from traditional deterministic methods, our approach employs a flexible, end-to-end differentiable probabilistic encoder-decoder architecture. This modular design allows the encoder and decoder to be trained independently, enabling seamless adaptation to diverse traffic scenarios without retraining the entire system. Our key contributions include: (1) a probabilistic heatmap predictor that generates context-aware occupancy grids...

Accurately assessing collision risk in dynamic traffic scenarios is a crucial requirement for trajectory planning in autonomous vehicles (AVs) and enables a comprehensive safety evaluation of automated driving systems. To that end, this paper presents a novel probabilistic occupancy risk assessment (PORA) metric. It uses spatiotemporal heatmaps as probabilistic occupancy predictions of surrounding traffic participants and estimates the risk of a collision along an AV’s planned trajectory based on potential vehicle interactions. The use of probabilistic occupancy allows PORA to account for...