Contract-based safety verification for autonomous driving by Liebenwein, Lucas

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Counterexample-Guided Safety Contracts for Autonomous Driving by DeCastro, Jonathan, Liebenwein, Lucas, Vasile, Cristian-Ioan, Tedrake, Russell L, Karaman, Sertac, Rus, Daniela L

“…However, formally verifying autonomous driving decisions systems is difficult. In this paper, we propose a frame-work for constructing a set of safety contracts that serve as design requirements for controller synthesis for a given scenario. …”
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Pillar-Based Object Detection for Autonomous Driving by Wang, Y, Fathi, A, Kundu, A, Ross, DA, Pantofaru, C, Funkhouser, T, Solomon, J

“…We present a simple and flexible object detection framework optimized for autonomous driving. Building on the observation that point clouds in this application are extremely sparse, we propose a practical pillar-based approach to fix the imbalance issue caused by anchors. …”
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A cloud-assisted design for autonomous driving by Suresh Kumar, Swarun, Gollakota, Shyamnath, Katabi, Dina

“…This paper presents Carcel, a cloud-assisted system for autonomous driving. Carcel enables the cloud to have access to sensor data from autonomous vehicles as well as the roadside infrastructure. …”
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Fast shadow detection for urban autonomous driving applications by Park, Sooho, Lim, Sejoon

“…This paper presents shadow detection methods for vision-based autonomous driving in an urban environment. Shadows misclassified as objects create problems in autonomous driving applications. …”
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Compositional and Contract-based Verification for Autonomous Driving on Road Networks by DeCastro, Jonathan, Alonso-Mora, Javier, Liebenwein, Lucas, Schwarting, Wilko, Vasile, Cristian-Ioan, Karaman, Sertac, Rus, Daniela L

“…Recent advances in autonomous driving have raised the problem of safety to the forefront and incentivized research into establishing safety guarantees. …”
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Consistent Depth Estimation in Data-Driven Simulation for Autonomous Driving by Beveridge, Matthew

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Probabilistic lane estimation for autonomous driving using basis curves by Huang, Albert S., Teller, Seth

“…Lane estimation for autonomous driving can be formulated as a curve estimation problem, where local sensor data provides partial and noisy observations of spatial curves forming lane boundaries. …”
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CarSpeak : a content-centric network for autonomous driving by Suresh Kumar, Swarun

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CarSpeak: a content-centric network for autonomous driving by Suresh Kumar, Swarun, Shi, Lixin, Ahmed, Nabeel, Gil, Stephanie, Katabi, Dina, Rus, Daniela L.

“…This paper introduces CarSpeak, a communication system for autonomous driving. CarSpeak enables a car to query and access sensory information captured by other cars in a manner similar to how it accesses information from its local sensors. …”
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Online risk-aware conditional planning with qualitative autonomous driving applications by Deyo, Matthew Quinn

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A robust motion planning approach for autonomous driving in urban areas by Fiore, Gaston A

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Variational Autoencoder for End-to-End Control of Autonomous Driving with Novelty Detection and Training De-biasing by Amini, Alexander, Araki, Brandon, Rus, Daniela, Schwarting, Wilko, Rosman, Guy, Karaman, Sertac, Rus, Daniela L

“…This paper introduces a new method for end-to-end training of deep neural networks (DNNs) and evaluates it in the context of autonomous driving. DNN training has been shown to result in high accuracy for perception to action learning given sufficient training data. …”
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Learning Robust Control Policies for End-to-End Autonomous Driving From Data-Driven Simulation by Amini, Alexander A, Gilitschenski, Igor, Phillips, Jacob, Moseyko, Julia, Banerjee, Rohan, Karaman, Sertac, Rus, Daniela L

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Autonomous driving systems hardware and software architecture exploration: optimizing latency and cost under safety constraints by Collin, Anne, Siddiqi, Afreen, Imanishi, Yuto, Rebentisch, Eric, Tanimichi, Taisetsu, Weck, Olivier L.

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Development of a simulation-based platform for autonomous vehicle algorithm validation by Banerjee, Rohan Bandopadhay.

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Risk Aware Planning and Probabilistic Prediction for Autonomous Systems under Uncertain Environments by Han, Weiqiao

“…Our model achieves state-of-the-art performance in autonomous driving trajectory prediction tasks.…”
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Team MIT Urban Challenge Technical Report by Leonard, John, Barrett, David, How, Jonathan, Teller, Seth, Antone, Matt, Campbell, Stefan, Epstein, Alex, Fiore, Gaston, Fletcher, Luke, Frazzoli, Emilio, Huang, Albert, Jones, Troy, Koch, Olivier, Kuwata, Yoshiaki, Mahelona, Keoni, Moore, David, Moyer, Katy, Olson, Edwin, Peters, Steven, Sanders, Chris, Teo, Justin, Walter, Matthew

“…These innovations are being incorporated in two new roboticvehicles equipped for autonomous driving in urban environments,with extensive testing on a DARPA site visit course. …”
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Autonomous Vehicle Navigation in Rural Environments Without Detailed Prior Maps by Ort, Teddy, Paull, Liam, Rus, Daniela

“…State-of-the-art autonomous driving systems rely heavily on detailed and highly accurate prior maps. …”
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A general, context-aware pedestrian trajectory prediction model by Jaipuria, Nikita

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