Modeling and interpreting road geometry from a driver's perspective using variational autoencoders

[1]  Samuel Labi,et al.  Efficacies of roadway safety improvements across functional subclasses of rural two-lane highways. , 2011, Journal of safety research.

[2]  Charles Goldenbeld,et al.  Supporting drivers in forming correct expectations about transitions between rural road categories. , 2011, Accident; analysis and prevention.

[3]  A James McKnight,et al.  Young novice drivers: careless or clueless? , 2003, Accident; analysis and prevention.

[4]  Burcu Akinci,et al.  A semi-automated method for extracting vertical clearance and cross sections in tunnels using mobile LiDAR data , 2016 .

[5]  Kilian M. Pohl,et al.  Variational AutoEncoder For Regression: Application to Brain Aging Analysis , 2019, MICCAI.

[6]  Lutz Eckstein,et al.  Data-Driven Maneuver Modeling using Generative Adversarial Networks and Variational Autoencoders for Safety Validation of Highly Automated Vehicles , 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

[7]  Yunze He,et al.  Near infrared nighttime road pedestrians recognition based on convolutional neural network , 2019, Infrared Physics & Technology.

[8]  Eric T. Donnell,et al.  Understanding Speed Concepts , 2009 .

[9]  Hojjat Adeli,et al.  A New Neural Dynamic Classification Algorithm , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[10]  Joseph E. Hummer,et al.  Evaluation of GIS Applications for Horizontal Curve Data Collection , 2012 .

[11]  Marko Čičković,et al.  Influence of Human Behaviour on Geometric Road Design , 2016 .

[12]  Mark Stevenson,et al.  Streetscape augmentation using generative adversarial networks: insights related to health and wellbeing , 2019, Sustainable Cities and Society.

[13]  Filip Karlo Dosilovic,et al.  Explainable artificial intelligence: A survey , 2018, 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[14]  Michael Eliseev,et al.  Using 3D-modeling Technologies to Increase Road Safety , 2017 .

[15]  Saeid Sanei,et al.  Deep Neural Architectures for Mapping Scalp to Intracranial EEG , 2018, Int. J. Neural Syst..

[16]  Karim El-Basyouny,et al.  Exploring the association between speed and safety: A path analysis approach. , 2016, Accident; analysis and prevention.

[17]  Yung-Ching Liu,et al.  Fatigued driver's driving behavior and cognitive task performance: Effects of road environments and road environment changes , 2009 .

[18]  Yichang Tsai,et al.  Automatic Horizontal Curve Identification and Measurement Method Using 1 GPS Data 2 , 2017 .

[19]  Hojjat Adeli,et al.  A novel machine learning‐based algorithm to detect damage in high‐rise building structures , 2017 .

[20]  Tianqi Chen,et al.  Empirical Evaluation of Rectified Activations in Convolutional Network , 2015, ArXiv.

[21]  Said M. Easa,et al.  State of the Art of Highway Geometric Design Consistency , 1999 .

[22]  Soumith Chintala,et al.  Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.

[23]  Mark Stevenson,et al.  Middle-aged Drivers' subjective categorization for combined alignments on mountainous freeways and their speed choices. , 2019, Accident; analysis and prevention.

[24]  Roberto Murcio,et al.  Modelling urban networks using Variational Autoencoders , 2019, Appl. Netw. Sci..

[25]  Cláudio Rosito Jung,et al.  An Improved Linear-Parabolic Model for Lane Following and Curve Detection , 2005, XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'05).

[26]  Guy H. Walker,et al.  Self Explaining Roads and situation awareness , 2013 .

[27]  Christoph Stiller,et al.  Kalman Particle Filter for lane recognition on rural roads , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[28]  Jan Theeuwes,et al.  Self-explaining roads , 1995 .

[29]  Duo Xu,et al.  Quantifying drivers' visual perception to analyze accident-prone locations on two-lane mountain highways. , 2018, Accident; analysis and prevention.

[30]  Hojjat Adeli,et al.  A novel unsupervised deep learning model for global and local health condition assessment of structures , 2018 .

[31]  Yang Ma,et al.  A convolutional neural network method to improve efficiency and visualization in modeling driver’s visual field on roads using MLS data , 2019 .

[32]  Hamish W. Mackie,et al.  Road user behaviour changes following a self-explaining roads intervention. , 2013, Accident; analysis and prevention.

[33]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[34]  Zhigang Du,et al.  The Impact of Rhythm-Based Visual Reference System in Long Highway Tunnels , 2017 .

[35]  Jaehoon Jung,et al.  3D virtual intersection sight distance analysis using lidar data , 2018 .

[36]  Tarek Sayed,et al.  Influence of Vertical Alignment on Horizontal Curve Perception: Phase II: Modeling Perceived Radius , 2002 .

[37]  T J Triggs,et al.  THE EFFECTS OF ROAD CURVE GEOMETRY AND APPROACH DISTANCE ON JUDGEMENTS OF CURVE EXIT ANGLE , 1982 .

[38]  Taghi M. Khoshgoftaar,et al.  A survey on Image Data Augmentation for Deep Learning , 2019, Journal of Big Data.

[39]  Fred L. Mannering,et al.  An empirical analysis of driver perceptions of the relationship between speed limits and safety , 2009 .

[40]  Yuren Chen,et al.  Safety reliability evaluation when vehicles turn right from urban major roads onto minor ones based on driver's visual perception. , 2016, Accident; analysis and prevention.

[41]  Paul Schonfeld,et al.  Bilevel Highway Route Optimization , 2010 .

[42]  Hong Wang,et al.  A Novel Method of Building Functional Brain Network Using Deep Learning Algorithm with Application in Proficiency Detection , 2019, Int. J. Neural Syst..

[43]  Xiaohua Zhao,et al.  A Study of the Relationship Between Driver Fatigue and Monotonous Road Environment , 2012 .

[44]  Miguel A. Molina-Cabello,et al.  Vehicle type detection by ensembles of convolutional neural networks operating on super resolved images , 2018, Integr. Comput. Aided Eng..

[45]  Alberto Holgado-Barco,et al.  Semiautomatic Extraction of Road Horizontal Alignment from a Mobile LiDAR System , 2015, Comput. Aided Civ. Infrastructure Eng..

[46]  Peter E.D. Love,et al.  Revisiting Quality Failure Costs in Construction , 2018 .

[47]  Mohamadreza Banihashemi.  Effect of horizontal curves on urban arterial crashes. , 2016, Accident; analysis and prevention.