Evaluation of Single Vehicle Data in Dependence of the Vehicle-Type, Lane, and Site

TL;DR

This paper investigates how vehicle type, lane, and site affect traffic flow characteristics and introduces improved measurement and aggregation methods with better statistical properties.

Contribution

It provides new insights into dependencies of traffic parameters and proposes enhanced measurement and aggregation techniques.

Findings

Vehicle type, lane, and site significantly influence fundamental diagrams.

Proposed methods show improved statistical reliability over conventional approaches.

Study enhances understanding of traffic flow variability.

Abstract

In this paper we study dependencies of fundamental diagrams, time gap distributions, and velocity-distance relations on vehicle types, lanes and/or measurement sites. We also propose measurement and aggregation methods that have more favourable statistical properties than conventional methods.