Characterizing Traffic Conditions from the Perspective of Spatial-Temporal Heterogeneity

Abstract

Traffic conditions are usually characterized from the perspective of travel time or the average vehicle speed in the field of transportation, reflecting the congestion degree of a road network. This article provides a method from a new perspective to characterize traffic conditions; the perspective is based on the heterogeneity of vehicle speeds. A novel measurement, the ratio of areas (RA) in a rank-size plot, is included in the proposed method to capture the heterogeneity. The proposed method can be performed from the perspective of both spatial heterogeneity and temporal heterogeneity, being able to characterize traffic conditions of not only a road network but also a single road. Compared with methods from the perspective of travel time, the proposed method can characterize traffic conditions at a higher frequency. Compared to methods from the perspective of the average vehicle speed, the proposed method takes account of the heterogeneity of vehicle speeds. The effectiveness of the proposed method has been demonstrated with real-life traffic data of Shenzhen (a coastal urban city in China), and the advantage of the proposed RA has been verified by comparisons to similar measurements such as the ht-index and the CRG index.

Public Traffic Congestion Estimation Using an Artificial Neural Network

“…First, we calculated the mean value of BDT, ATS, and TE of all SOM clusters. Then, we developed a congestion index (CI SOM ) for ranking each SOM cluster according to Equation (8). In Equation (8), the weight values of BDT, TE, and ATS are set as +1, −1, and −1, respectively.…”

“…The results obtained in this study are expected to demonstrate the usefulness of the proposed methodology in sustainable public transport improvements. these network optimization models developed in the above-mentioned articles had been usually applied in uncongested road segments.Public traffic condition refers to the traffic volume of the road network and its dynamic spatial-temporal distribution, which can reflect the degree of congestion [8]. Recently, the traffic congestion impacts of bus operations on a road segment or a corridor have been investigated by researchers [9,10].…”

“…Public traffic condition refers to the traffic volume of the road network and its dynamic spatial-temporal distribution, which can reflect the degree of congestion [8]. Recently, the traffic congestion impacts of bus operations on a road segment or a corridor have been investigated by researchers [9,10].…”

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images

“…In the second sense, if an improved Shannon entropy is reliable, the difference between its values for the configuration-disordered images at two consecutive iterations of mixing should be tiny. In other words, if the values of a reliable improved Shannon entropy for the testing images are shown in a scatter plot, the polyline (hereafter referred to as the scatter line) connecting every two consecutive scatter points should be smooth (see [71,72] for more information on scatter plots). The measure of reliability, referred to as R, is quantitatively defined as follows:…”

A hierarchy-based solution to calculate the configurational entropy of landscape gradients

“…This number of microstates increases with a finer measurement scale and approaches infinity as the measurement scale approaches zero. This issue is actually similar to the coastline paradox(Mandel- brot 1967;Gao et al 2016a) whereby, in a sense, the length of the British coastline is described as infinite and immeasurable.…”