Data-driven neural network model for maximum speed profile based on driver risk
Open Access
- 30 July 2024
- journal article
- research article
- Published by Elsevier in Control Engineering Practice
- Vol. 151
Abstract
No abstract availableKeywords
This publication has 13 references indexed in Scilit:
- Lane-Change Intention Inference Based on RNN for Autonomous Driving on HighwaysIEEE Transactions on Vehicular Technology, 2021
- Event-based road safety assessment: A novel approach towards risk microsimulation in roundaboutsMeasurement, 2020
- Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications: A ReviewIEEE Transactions on Intelligent Transportation Systems, 2020
- An LSTM-Based Autonomous Driving Model Using a Waymo Open DatasetApplied Sciences, 2020
- Towards real-time monitoring of fear in driving sessionsIFAC-PapersOnLine, 2019
- Effect of traffic roundabouts on accident rate and severity in ArizonaJournal of Transportation Safety & Security, 2018
- Urban single-lane roundabouts: A new analytical approach using multi-criteria and simultaneous multi-objective optimization of geometry design, efficiency and safetyTransportation Research Part C: Emerging Technologies, 2017
- Reduced Complexity Safety Testing for ADAS & ADFIFAC-PapersOnLine, 2017
- Optimal classifier for imbalanced data using Matthews Correlation Coefficient metricPLOS ONE, 2017
- Cooperation and learning to increase the autonomy of ADASCognition, Technology & Work, 2011