An Empirical Estimation on the Impact of Freight Traffic on the Capacity Drop

An Empirical Estimation on the Impact of Freight Traffic on the Capacity Drop

de Swart, Sebas (TU Delft Civil Engineering and Geosciences)

Knoop, V.L. (graduation committee)
Calvert, S.C. (graduation committee)
Snelder, M. (graduation committee)
de Bok, M.A. (graduation committee)

Delft University of Technology

Civil Engineering | Transport and Planning

2021-04-21

In recent years, the amount of traffic on the highways has increased continuously and in particular freight traffic. Despite solutions to maximize roadway capacity, the drop of capacity after congestions sets in, remains an active field of study. The influence of freight traffic on traffic flow has received little attention, especially regarding the capacity drop. The Kaplan-Meier Product Limit Method was used to estimate capacity and recovery distributions for selected sites to overcome stochastic characteristics of traffic flow and investigate the relation between heavy vehicle share and capacity drop at Dutch highways. Furthermore, a simulation study was executed to investigate increased heavy vehicle share scenarios and changing physical and operational characteristics of heavy vehicles. The empirical results show a connection between heavy vehicle share and the capacity drop, although not statistically significant. Currently, chaotic properties of breakdown flow seem to superimpose the impact. However, it is possible that the effect becomes influential as the current maximum observed share of heavy vehicles during breakdown grows from 9% up to 15%, which appeared to be the worst case scenario in simulation. Besides, concern is raised as a decreasing breakdown capacity was observed on several Dutch highways, even after correction with the PCE values of the increasing heavy vehicle share.

Freight Traffic
Capacity Drop
Heavy Vehicle share
Empirical analysis
Simulation
Dutch highways
Kaplan-Meier
Product Limit Method
Passenger Car Equivalents

http://resolver.tudelft.nl/uuid:b1ad66d9-82eb-4bfa-933f-31b0783f649d

Student theses

master thesis

© 2021 Sebas de Swart