Traffic State Estimation and Classification on Citywide Scale Using Speed Transition Matrices

Abstract

The rising need for mobility, especially in large urban centers, consequently results in congestion, which leads to increased travel times and pollution. Advanced traffic management systems are being developed to take the advantage of increased mobility positive effects and minimize the negative ones. The first step dealing with congestion in urban areas is the detection of congested areas and the estimation of the congestion level. This paper presents a a method for a traffic state estimation on a citywide scale using the novel traffic data representation, named Speed Transition Matrix (STM). The proposed method uses traffic data to extract the STMs and to estimate the traffic state based on the Center Of Mass (COM) computation for every STM. The COM-based approach enables the simplification of the clustering process and provides increased interpretability of the resulting clusters. Using the proposed method, traffic data is analyzed, and the traffic state is estimated for the most relevant road segments in the City of Zagreb, which is the capital and the largest city in Croatia. The traffic state classification results are validated using the cross-validation method and the domain knowledge data with the resulting accuracy of 97% and 91%, respectively. The results indicate the possible application of the proposed method for the traffic state estimation on macro- and micro-locations in the city area. In the end, the application of STMs for traffic state estimation, traffic management, and anomaly detection is discussed.

Motorway Bottleneck Probability Estimation in Connected Vehicles Environment Using Speed Transition Matrices

“…To compute CoMs, expected values of the coordinates (origin and destination speed) are computed using Equations ( 2 ) and ( 3 ): where and represent coordinates of the CoM and and represent the marginal distributions for the coordinates. Further explanation of the method can be found in our previous works [ 8 , 21 ].…”

“…Fuzzy rules set for the bottleneck probability estimation is presented in Table 1 . The rules were created using expert knowledge about the bottleneck definition extracted from [ 8 , 19 ]. An important consideration for rule setting was to address the behaviour of the two input parameters and with the corresponding correlations.…”

“…Those data can be incorporated into emerging traffic models to detect bottlenecks efficiently and more accurately. In the context of mentioned research possibilities, this paper proposes a novel method for the road traffic bottleneck detection on motorways using the emerging traffic data modelling technique Speed Transition Matrix (STM) discussed further in [ 8 , 9 ]. The method is based on the CV data collection on the observed motorway, focusing on traffic patterns that emerge between consecutive motorway segments.…”

“…Road traffic states: In this paper, three road traffic states categories are defined based on [ 8 , 19 ]: (i) free-flow, (ii) unstable traffic flow, and (iii) congested traffic flow. Free-flow is defined as traffic conditions with no interactions between vehicles due to low traffic density.…”

The Influence of Quality Management System on the Operation of Periodical Technical Inspection Stations

“…A very important issue represented in the literature is the quality management systems of transport processes [19,20] and safety management systems in transport [21]. The latter aspect concerns a very wide spectrum of activities, including legal and educational aspects [22,23], social [24][25][26], road traffic safety [27][28][29][30][31][32], general safety of the transport system [33][34][35][36][37][38], and resulting from the use and operation of means of transport [39][40][41][42][43][44][45]. Moreover, concerning technical safety [46], as well as related to technical and legal control through actions of the Police and Transport Inspection and other services.…”