Noah T. Curran (University of Michigan), Kang G. Shin (University of Michigan), William Hass (Lear Corporation), Lars Wolleschensky (Lear Corporation), Rekha Singoria (Lear Corporation), Isaac Snellgrove (Lear Corporation), Ran Tao (Lear Corporation)

ETAS Best Short Paper Award Runner-Up!

On urban roadways, “dooring” remains a serious problem to the safety of pedestrians, cyclists, and other vulnerable road users (VRUs). Existing solutions that address this concern remain inadequate, as they either place unreasonable expectations on the pedestrians or rely on prohibitively expensive additions to the vehicle’s sensing capabilities. Consequently, typical consumer vehicles are not yet equipped with such a technology, and practical dooring prevention still remains a safety concern.
To address this problem, we propose a driver safety system for dooring prevention called S-Door that uses existing resources available in every modern vehicle: Bluetooth Low-Energy (BLE). Since a modern vehicle is distributively equipped with multiple BLE transceivers, we leverage each transceiver to observe BLE advertising data (AD) packets that consumers’ smart devices passively transmit. From these AD packets, we extract information that we can use to localize the VRU device without pairing with the device. With this information, we propose two methods for localization based on BLE versions ≤5.0 and ≥5.1, respectively. Our solutions are capable of alerting the driver of all instances of an oncoming VRU. Due to S-Door’s use of existing vehicle BLE hardware, we may extend this application to modern vehicles through a firmware update—no physical modification is necessary.

View More Papers

OptRand: Optimistically Responsive Reconfigurable Distributed Randomness

Adithya Bhat (Purdue University), Nibesh Shrestha (Rochester Institute of Technology), Aniket Kate (Purdue University), Kartik Nayak (Duke University)

Read More

Ghost Domain Reloaded: Vulnerable Links in Domain Name Delegation...

Xiang Li (Tsinghua University), Baojun Liu (Tsinghua University), Xuesong Bai (University of California, Irvine), Mingming Zhang (Tsinghua University), Qifan Zhang (University of California, Irvine), Zhou Li (University of California, Irvine), Haixin Duan (Tsinghua University; QI-ANXIN Technology Research Institute; Zhongguancun Laboratory), Qi Li (Tsinghua University; Zhongguancun Laboratory)

Read More

Access Your Tesla without Your Awareness: Compromising Keyless Entry...

Xinyi Xie (Shanghai Fudan Microelectronics Group Co., Ltd.), Kun Jiang (Shanghai Fudan Microelectronics Group Co., Ltd.), Rui Dai (Shanghai Fudan Microelectronics Group Co., Ltd.), Jun Lu (Shanghai Fudan Microelectronics Group Co., Ltd.), Lihui Wang (Shanghai Fudan Microelectronics Group Co., Ltd.), Qing Li (State Key Laboratory of ASIC & System, Fudan University), Jun Yu (State Key…

Read More

BinaryInferno: A Semantic-Driven Approach to Field Inference for Binary...

Jared Chandler (Tufts University), Adam Wick (Fastly), Kathleen Fisher (DARPA)

Read More