published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

Artificial intelligence research is ushering in an era of sophisticated, mass-market transportation technology. While computers can fly a passenger jet better than a human pilot, people still face the dangerous yet tedious task of driving. Intelligent Transportation Systems (ITS) is the field focused on integrating information technology with vehicles and transportation infrastructure. Recent advances in ITS point to a future in which vehicles handle the vast majority of the driving task. Once autonomous vehicles become popular, interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination will be outdated. The bottleneck for efficiency will no longer be drivers, but the mechanism by which those drivers' actions are coordinated. Current methods for controlling traffic cannot exploit the superior capabilities of autonomous vehicles. This thesis describes a novel approach to managing autonomous vehicles at intersections that decreases the amount of time vehicles spend waiting. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this system, agents use a new approach built around a detailed communication protocol, which is also a contribution of the thesis. In simulation, I demonstrate that this mechanism can significantly outperform current intersection control technology-traffic signals and stop signs. This thesis makes several contributions beyond the mechanism and protocol. First, it contains a distributed, peer-to-peer version of the protocol for low-traffic intersections. Without any requirement of specialized infrastructure at the intersection, such a system would be inexpensive and easy to deploy at intersections which do not currently require a traffic signal. Second, it presents an analysis of the mechanism's safety, including ways to mitigate some failure modes. Third, it describes a custom simulator, written for this work, which will be made publicly available following the publication of the thesis. Fourth, it explains how the mechanism is "backward-compatible" so that human drivers can use it alongside autonomous vehicles. Fifth, it explores the implications of using the mechanism at multiple proximal intersections. The mechanism, along with all available modes of operation, is implemented and tested in simulation, and I present experimental results that strongly attest to the efficacy of this approach. / text

Lau Wai Hung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 63-65). / Abstracts in English and Chinese. / abstract --- p.I / 摘要 --- p.II / acknowledgement --- p.III / table of contents --- p.IV / list of figures --- p.VI / Chapter CHAPTER 1 --- introduction --- p.1 / Chapter CHAPTER 2 --- literature review --- p.4 / Chapter 2.1 --- Traffic data collection methods --- p.4 / Chapter 2.2 --- Vision-based traffic monitoring techniques --- p.6 / Chapter 2.2.1 --- Vehicle tracking approaches --- p.7 / Chapter 2.2.2 --- Image processing techniques --- p.10 / Chapter CHAPTER 3 --- methodology --- p.15 / Chapter 3.1 --- Solution Concept --- p.16 / Chapter 3.2 --- System Framework --- p.18 / Chapter 3.2.1 --- Edge Detection Module --- p.20 / Chapter 3.2.2 --- Background Update Module --- p.22 / Chapter 3.2.3 --- Feature Extraction Modules --- p.25 / Chapter CHAPTER 4 --- experiments and evaluation --- p.41 / Chapter 4.1 --- Setup and Data Collection --- p.41 / Chapter 4.2 --- Evaluation Criteria --- p.42 / Chapter 4.3 --- Experimental Results --- p.44 / Chapter 4.3.1 --- Comparing overall accuracies --- p.44 / Chapter 4.3.2 --- Accuracies for different traffic conditions --- p.46 / Chapter 4.3.3 --- Comparing balanced sampling and random sampling --- p.48 / Chapter 4.3.4 --- Comparing day and night conditions --- p.50 / Chapter 4.3.5 --- Testing on time-series of images --- p.52 / Chapter CHAPTER 5 --- analysis --- p.54 / Chapter 5.1 --- Strengths and Weaknesses --- p.54 / Chapter 5.1.1 --- Sobel Edge Histogram --- p.54 / Chapter 5.1.2 --- Horizontal Line Detection --- p.55 / Chapter 5.1.3 --- Block Detection --- p.56 / Chapter 5.1.4 --- Combined Learning --- p.57 / Chapter 5.1.5 --- Overall Framework --- p.58 / Chapter 5.2 --- Future Research --- p.59 / Chapter 5.2.1 --- Static image based monitoring combined with other traffic monitoring approaches --- p.59 / Chapter 5.2.2 --- Horizontal Line Detection as tracked features of vehicles --- p.60 / Chapter 5.2.3 --- Application in aerial image-based system --- p.60 / Chapter CHAPTER 6 --- conclusion --- p.62 / bibliography --- p.63 / appendix a sobel edge detection --- p.66 / appendix b neural network setup --- p.67 / appendix c numerical results --- p.69

Intelligent Transportation Systems (ITS) include a wide range of applications that aim to use state-of-the-art communication and information technologies to enhance and control the flow of traffic. The ability to communicate with cars while travelling on the road is crucial to the success of these systems and thus requires careful studying. This research aims to study the feasibility of deploying wireless communication networks that are capable of collecting data from cars as well as providing them with information about the current traffic situation. We present a platform that integrates a microscopic traffic simulation, Paramics, and a communication network simulator, Omnet++. The integration of both simulators is a key solution to several research problems both on the communications side and on the transportation side. The combined simulator will allow designing and testing ITS Applications, which rely on communication between vehicles, before they are implemented on the streets.

Intelligent Transportation Systems (ITS) include a wide range of applications that aim to use state-of-the-art communication and information technologies to enhance and control the flow of traffic. The ability to communicate with cars while travelling on the road is crucial to the success of these systems and thus requires careful studying. This research aims to study the feasibility of deploying wireless communication networks that are capable of collecting data from cars as well as providing them with information about the current traffic situation. We present a platform that integrates a microscopic traffic simulation, Paramics, and a communication network simulator, Omnet++. The integration of both simulators is a key solution to several research problems both on the communications side and on the transportation side. The combined simulator will allow designing and testing ITS Applications, which rely on communication between vehicles, before they are implemented on the streets.

Numerous local incidents occur on road networks daily many of which may lead to congestion and safety hazards. If vehicles can be provided with information about such incidents or traffic conditions in advance, the quality of driving in terms of time, distance, and safety can be improved significantly. Vehicular Ad Hoc Networks (VANETs) have recently emerged as an effective tool for improving road safety through the propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. This research has presented an effective warning data dissemination scheme which deploys relay strategy and concept of Region of Interest (RoI). A warning data message is characterized as spatio-temporal, implying that both the location and the time of an incident must be considered. Factors such as the type of warning message, the layout of the road network, the traffic density and the capacity of alternative roads are influential in determining the RoI in which the warning message needs to be propagated. In the developed scheme, the type of warning message is taken into account for the determination of the RoI so that the more severe the incident, the wider the RoI. In the selection of the relay point, the border relay area in which the relay point is placed, is adapted to the traffic density so that the higher the traffic density , the narrower the relay area. Traffic statistics are used to calculate the RoI, which is then enclosed in the warning message so that the message is not retransmitted beyond the RoI. Also, the responsibility for retransmitting the message is assigned to the relay node. The data is then disseminated effectively so that vehicles in areas unrelated to the incident are not informed. The primary objective of this research is to provide better understanding of the dissemination of warning data in the context of a vehicular network with the ultimate goal of increasing the possibility of using VANETs for safety applications.

Numerous local incidents occur on road networks daily many of which may lead to congestion and safety hazards. If vehicles can be provided with information about such incidents or traffic conditions in advance, the quality of driving in terms of time, distance, and safety can be improved significantly. Vehicular Ad Hoc Networks (VANETs) have recently emerged as an effective tool for improving road safety through the propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. This research has presented an effective warning data dissemination scheme which deploys relay strategy and concept of Region of Interest (RoI). A warning data message is characterized as spatio-temporal, implying that both the location and the time of an incident must be considered. Factors such as the type of warning message, the layout of the road network, the traffic density and the capacity of alternative roads are influential in determining the RoI in which the warning message needs to be propagated. In the developed scheme, the type of warning message is taken into account for the determination of the RoI so that the more severe the incident, the wider the RoI. In the selection of the relay point, the border relay area in which the relay point is placed, is adapted to the traffic density so that the higher the traffic density , the narrower the relay area. Traffic statistics are used to calculate the RoI, which is then enclosed in the warning message so that the message is not retransmitted beyond the RoI. Also, the responsibility for retransmitting the message is assigned to the relay node. The data is then disseminated effectively so that vehicles in areas unrelated to the incident are not informed. The primary objective of this research is to provide better understanding of the dissemination of warning data in the context of a vehicular network with the ultimate goal of increasing the possibility of using VANETs for safety applications.

Thesis (Ph. D.)--University of California, Riverside, 2009. / Includes abstract. Available via ProQuest Digital Dissertations. Title from first page of PDF file (viewed March 12, 2010). Includes bibliographical references (p. ). Also issued in print.

Urban freeway demand that frequently exceeds capacity has caused many agencies to consider many options to reduce congestion. A series of solutions that falls under the Active Traffic Management (ATM) banner have shown promising potential. Perhaps the most popular ATM strategy is ramp metering. Ramp metering involves limiting the access of vehicles to freeways at an entrance ramp. By doing this, freeway throughput, speeds, and travel time reliability can be increased, while the number of traffic incidents can be decreased. This study examines the application of an innovative ramp metering strategy, Intersection Ramp Metering (IRM), at a section of Loop 1 in Austin, TX. IRM implements the ramp metering function at the intersection immediately upstream of the entrance ramp, rather than on the ramp itself. A microsimulation analysis of this application is performed in VISSIM, and the results confirm that freeway throughput (+10%), and system average travel time (-14%), can be improved, as well as several other performance measures. / text

published_or_final_version / abstract / toc / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning