Vision Zero: on a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput

12/09/2018

∙

We propose an economical, viable, approach to eliminate almost all car accidents. Our method relies on a mathematical model of safety and can be applied to all modern cars at a mild cost.

READ FULL TEXT

Vision Zero: on a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput

On a Formal Model of Safe and Scalable Self-driving Cars

Assisting Drivers During Overtaking Using Car-2-Car Communication and Multi-Agent Systems

A Realistic Cyclist Model for SUMO Based on the SimRa Dataset

Achieving Realistic Cyclist Behavior in SUMO using the SimRa Dataset

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning

Comparing Background Subtraction Algorithms and Method of Car Counting

Two-Hop Connectivity to the Roadside in a VANET Under the Random Connection Model

Vision Zero: on a Provable Method for Eliminating Roadway Accidents without Compromising Traffic Throughput

Related Research

On a Formal Model of Safe and Scalable Self-driving Cars

Assisting Drivers During Overtaking Using Car-2-Car Communication and Multi-Agent Systems

A Realistic Cyclist Model for SUMO Based on the SimRa Dataset

Achieving Realistic Cyclist Behavior in SUMO using the SimRa Dataset

Detection of concealed cars in complex cargo X-ray imagery using Deep Learning

Comparing Background Subtraction Algorithms and Method of Car Counting

Two-Hop Connectivity to the Roadside in a VANET Under the Random Connection Model