Safe Driving Capacity of Autonomous Vehicles

TL;DR

This paper formalizes safety and efficiency in autonomous driving using linear temporal logic, introduces metrics for safe driving throughput and capacity, and compares perception-based and cooperative vehicle systems.

Contribution

It provides formal definitions of safety states, introduces the concepts of SDT and SDC, and analyzes their differences between PBV and CBV systems.

Findings

SDC of PBV is upper-bounded by that of CBV.

Formal safety definitions using LTL are proposed.

Analysis of factors affecting SDT.

Abstract

An excellent self-driving car is expected to take its passengers safely and efficiently from one place to another. However, different ways of defining safety and efficiency may significantly affect the conclusion we make. In this paper, we give formal definitions to the safe state of a road and safe state of a vehicle using the syntax of linear temporal logic (LTL). We then propose the concept of safe driving throughput (SDT) and safe driving capacity (SDC) which measure the amount of vehicles in the safe state on a road. We analyze how SDT is affected by different factors. We show the analytic difference of SDC between the road with perception-based vehicles (PBV) and the road with cooperative-based vehicles (CBV). We claim that through proper design, the SDC of the road filled with PBVs will be upper-bounded by the SDC of the road filled with CBVs.