A Vehicle Size-Based Dynamic Model of Artificial Driving Risk Potential Fields and Vehicle Interaction Analysis for Highway Driving

TL;DR

This paper introduces a vehicle size-based dynamic model of driving risk potential that accounts for heterogeneity in vehicle sizes, revealing how larger and faster vehicles influence risk fields and vehicle interactions on highways.

Contribution

The study develops an improved risk potential model incorporating vehicle dimensions and analyzes the impact of vehicle size and speed on risk fields and interactions.

Findings

Larger and faster vehicles generate more intense risk fields.

Risk fields extend into adjacent lanes for larger vehicles.

High-risk zones are identified around the tail and head of high-speed vehicles.

Abstract

Traditional driving risk potential field model generally assumes uniform vehicle sizes, which fails to reflect the heterogeneity in real-world traffic environment. This study aims to develop an improved model by introducing the vehicle dimensions into the driving risk potential field framework. Vehicles are categorized based on size into standard-sized vehicles, medium-sized vehicles, and large-sized vehicles. And the interactions between two vehicles and the force field excited by the driving risk potential field are investigated in this paper. Our analysis of the risk field contours at various vehicle speeds and sizes reveals that larger and faster vehicles generate more intense and expansive risk fields, necessitating increased following distances. For larger vehicles, the risk field extends into adjacent lanes. Force field analysis demonstrates that vehicles traveling in adjacent lanes undergo changes in their motion state due to the influence of the force field emanating from the neighboring larger vehicles. The model effectively points out that, for adjacent lanes, the regions surrounding the tail and head of high-speed vehicles represent highly risky zones.