Autonomous driving challenge: To Infer the property of a dynamic object based on its motion pattern using recurrent neural network

by   Mona Fathollahi, et al.

In autonomous driving applications a critical challenge is to identify action to take to avoid an obstacle on collision course. For example, when a heavy object is suddenly encountered it is critical to stop the vehicle or change the lane even if it causes other traffic disruptions. However,there are situations when it is preferable to collide with the object rather than take an action that would result in a much more serious accident than collision with the object. For example, a heavy object which falls from a truck should be avoided whereas a bouncing ball or a soft target such as a foam box need not be.We present a novel method to discriminate between the motion characteristics of these types of objects based on their physical properties such as bounciness, elasticity, etc.In this preliminary work, we use recurrent neural net-work with LSTM cells to train a classifier to classify objects based on their motion trajectories. We test the algorithm on synthetic data, and, as a proof of concept, demonstrate its effectiveness on a limited set of real-world data.


page 1

page 4


Collision Avoidance Detour for Multi-Agent Trajectory Forecasting

We present our approach, Collision Avoidance Detour (CAD), which won the...

Data and Knowledge for Overtaking Scenarios in Autonomous Driving

Autonomous driving has become one of the most popular research topics wi...

Towards Explainable Inference about Object Motion using Qualitative Reasoning

The capability of making explainable inferences regarding physical proce...

Flash: Fast and Light Motion Prediction for Autonomous Driving with Bayesian Inverse Planning and Learned Motion Profiles

Motion prediction of road users in traffic scenes is critical for autono...

Recurrent Neural Networks for video object detection

There is lots of scientific work about object detection in images. For m...

VM-MODNet: Vehicle Motion aware Moving Object Detection for Autonomous Driving

Moving object Detection (MOD) is a critical task in autonomous driving a...

Phase Space Reconstruction Network for Lane Intrusion Action Recognition

In a complex road traffic scene, illegal lane intrusion of pedestrians o...

Please sign up or login with your details

Forgot password? Click here to reset