Statistical Traffic State Analysis in Large-scale Transportation Networks Using Locality-Preserving Non-negative Matrix Factorization

Statistical traffic data analysis is a hot topic in traffic management and control. In this field, current research progresses focus on analyzing traffic flows of individual links or local regions in a transportation network. Less attention are paid to the global view of traffic states over the entire network, which is important for modeling large-scale traffic scenes. Our aim is precisely to propose a new methodology for extracting spatio-temporal traffic patterns, ultimately for modeling large-scale traffic dynamics, and long-term traffic forecasting. We attack this issue by utilizing Locality-Preserving Non-negative Matrix Factorization (LPNMF) to derive low-dimensional representation of network-level traffic states. Clustering is performed on the compact LPNMF projections to unveil typical spatial patterns and temporal dynamics of network-level traffic states. We have tested the proposed method on simulated traffic data generated for a large-scale road network, and reported experimental results validate the ability of our approach for extracting meaningful large-scale space-time traffic patterns. Furthermore, the derived clustering results provide an intuitive understanding of spatial-temporal characteristics of traffic flows in the large-scale network, and a basis for potential long-term forecasting.Comment: IET Intelligent Transport Systems (2013

A kinematic wave theory of capacity drop

Capacity drop at active bottlenecks is one of the most puzzling traffic phenomena, but a thorough understanding is practically important for designing variable speed limit and ramp metering strategies. In this study, we attempt to develop a simple model of capacity drop within the framework of kinematic wave theory based on the observation that capacity drop occurs when an upstream queue forms at an active bottleneck. In addition, we assume that the fundamental diagrams are continuous in steady states. This assumption is consistent with observations and can avoid unrealistic infinite characteristic wave speeds in discontinuous fundamental diagrams. A core component of the new model is an entropy condition defined by a discontinuous boundary flux function. For a lane-drop area, we demonstrate that the model is well-defined, and its Riemann problem can be uniquely solved. We theoretically discuss traffic stability with this model subject to perturbations in density, upstream demand, and downstream supply. We clarify that discontinuous flow-density relations, or so-called "discontinuous" fundamental diagrams, are caused by incomplete observations of traffic states. Theoretical results are consistent with observations in the literature and are verified by numerical simulations and empirical observations. We finally discuss potential applications and future studies.Comment: 29 pages, 10 figure

Estimation and prediction of travel time from loop detector data for intelligent transportation systems applications

With the advent of Advanced Traveler Information Systems (ATIS), short-term travel time prediction is becoming increasingly important. Travel time can be obtained directly from instrumented test vehicles, license plate matching, probe vehicles etc., or from indirect methods such as loop detectors. Because of their wide spread deployment, travel time estimation from loop detector data is one of the most widely used methods. However, the major criticism about loop detector data is the high probability of error due to the prevalence of equipment malfunctions. This dissertation presents methodologies for estimating and predicting travel time from the loop detector data after correcting for errors. The methodology is a multi-stage process, and includes the correction of data, estimation of travel time and prediction of travel time, and each stage involves the judicious use of suitable techniques. The various techniques selected for each of these stages are detailed below. The test sites are from the freeways in San Antonio, Texas, which are equipped with dual inductance loop detectors and AVI. ?? Constrained non-linear optimization approach by Generalized Reduced Gradient (GRG) method for data reduction and quality control, which included a check for the accuracy of data from a series of detectors for conservation of vehicles, in addition to the commonly adopted checks. ?? A theoretical model based on traffic flow theory for travel time estimation for both off-peak and peak traffic conditions using flow, occupancy and speed values obtained from detectors. ?? Application of a recently developed technique called Support Vector Machines (SVM) for travel time prediction. An Artificial Neural Network (ANN) method is also developed for comparison. Thus, a complete system for the estimation and prediction of travel time from loop detector data is detailed in this dissertation. Simulated data from CORSIM simulation software is used for the validation of the results

On-board B-ISDN fast packet switching architectures. Phase 2: Development. Proof-of-concept architecture definition report

For the next-generation packet switched communications satellite system with onboard processing and spot-beam operation, a reliable onboard fast packet switch is essential to route packets from different uplink beams to different downlink beams. The rapid emergence of point-to-point services such as video distribution, and the large demand for video conference, distributed data processing, and network management makes the multicast function essential to a fast packet switch (FPS). The satellite's inherent broadcast features gives the satellite network an advantage over the terrestrial network in providing multicast services. This report evaluates alternate multicast FPS architectures for onboard baseband switching applications and selects a candidate for subsequent breadboard development. Architecture evaluation and selection will be based on the study performed in phase 1, 'Onboard B-ISDN Fast Packet Switching Architectures', and other switch architectures which have become commercially available as large scale integration (LSI) devices

Study of architecture and protocols for reliable multicasting in packet switching networks

Group multicast protocols have been challenged to provide scalable solutions that meet the following requirements: (i) reliable delivery from different sources to all destinations within a multicast group; (ii) congestion control among multiple asynchronous sources. Although it is mainly a transport layer task, reliable group multicasting depends on routing architectures as well. This dissertation covers issues of both network and transport layers. Two routing architectures, tree and ring, are surveyed with a comparative study of their routing costs and impact to upper layer performances. Correspondingly, two generic transport protocol models are established for performance study. The tree-based protocol is rate-based and uses negative acknowledgment mechanisms for reliability control, while the ring-based protocol uses window-based flow control and positive acknowledgment schemes. The major performance measures observed in the study are network cost, multicast delay, throughput and efficiency. The results suggest that the tree architecture costs less at network layer than the ring, and helps to minimize latency under light network load. Meanwhile, heavy load reliable group multicasting can benefit from ring architecture, which facilitates window-based flow and congestion control. Based on the comparative study, a new two-hierarchy hybrid architecture, Rings Interconnected with Tree Architecture (RITA), is presented. Here, a multicast group is partitioned into multiple clusters with the ring as the intra-cluster architecture, and the tree as backbone architecture that implements inter-cluster multicasting. To compromise between performance measures such as delay and through put, reliability and congestion controls are accomplished at the transport layer with a hybrid use of rate and window-based protocols, which are based on either negative or positive feedback mechanisms respectively. Performances are compared with simulations against tree- and ring-based approaches. Results are encouraging because RITA achieves similar throughput performance as the ring-based protocol, but with significantly lowered delay. Finally, the multicast tree packing problem is discussed. In a network accommodating multiple concurrent multicast sessions, routing for an individual session can be optimized to minimize the competition with other sessions, rather than to minimize cost or delay. Packing lower bound and a heuristic are investigated. Simulation show that congestion can be reduced effectively with limited cost increase of routings

Freeway Multisensor Data Fusion Approach Integrating Data from Cellphone Probes and Fixed Sensors

Freeway traffic state information from multiple sources provides sufficient support to the traffic surveillance but also brings challenges. This paper made an investigation into the fusion of a new data combination from cellular handoff probe system and microwave sensors. And a fusion method based on the neural network technique was proposed. To identify the factors influencing the accuracy of fusion results, we analyzed the sensitivity of those factors by changing the inputs of neural-network-based fusion model. The results showed that handoff link length and sample size were identified as the most influential parameters to the precision of fusion. Then, the effectiveness and capability of proposed fusion method under various traffic conditions were evaluated. And a comparative analysis between the proposed method and other fusion approaches was conducted. The results of simulation test and evaluation showed that the fusion method could complement the drawback of each collection method, improve the overall estimation accuracy, adapt to the variable traffic condition (free flow or incident state), suit the fusion of data from cellphone probes and fixed sensors, and outperform other fusion methods

Estimating and exploiting the capacity of urban street networks

The paper deals with the problem of estimating and exploiting traffic capacity of different road elements (link, nodes, network) and presents the results obtained by performing a systematic investigation of the role that the parameters of a microscopic simulation model play on the macroscopic representation of different road elements. An analysis of traffic parameters has been performed using a microsimulation software package to identify the most important parameters affecting the arterial capacity and to calibrate driver's behavior models through macroscopic traffic observations

Web-Based Advanced Traveller Information System for Minna Metropolis, Nigeria

Advanced Traveller Information System (ATIS) is used to provide accurate, integrated and comprehensive travel and traffic information to road users. The information helps in both pre-trip and en-route decision making. This study developed a web-based ATIS for Minna metropolis in Nigeria. The information provided is from both primary and secondary sources. The developed ATIS provides information on route guidance, available intercity transport services and hotels in the metropolis. It also allows users to determine both weather and traffic flow conditions. A component of the system makes provision for electronic fare payment and booking of trips and hotel accommodation. The deployment of the ATIS is a source of static and dynamic information