Marc Miska

A New Multiobjective Signal Optimization for Oversaturated Networks

This paper presents a new methodology for optimizing the signal timing controls of oversaturated networks based on the cell transmission model and a goal programming technique with multiple objectives. The proposed model accounts for intersection spillovers, equity in delays, and system throughputs. This new formulation is solved by genetic algorithms to obtain signal timing plans. A case study with a nine-intersection network and a comparison between the proposed model and the throughput-maximizing strategy are examined. It is found that the new method can efficiently minimize spillovers, balance delay equity, and provide reasonable system throughputs in their respective order for oversaturated networks. The result also indicates that the throughput-maximizing strategy does not always yield minimum spillovers for oversaturated networks and occasionally provides a larger difference in average link delay at a spillover intersection than the proposed model does.

Traffic Data Collection and Its Standardization

Traffic engineers are involved in transport modeling, traffic simulation, operation optimization, and the development of methods to control and analyze traffic itself. New developments of individual traffic, public transport as well as pedestrian movements are the hope to ensure mobility and accessibility in urban areas to secure mobility in the less profitable countryside, to increase safety, and to limit the effects on the environment caused by transportation. Around the globe, governments declare goals in each of the mentioned fields, mostly under the umbrella of intelligent transport systems (ITS) to develop a sustainable transportation for everyone.

An Experimental Space for Conducting Controlled Driving Behavior Studies based on a Multiuser Networked 3D Virtual Environment and the Scenario Markup Language

We present a new framework for conducting controlled driving behavior studies based on multiuser networked 3-D virtual environments. The framework supports: 1) the simulation of multiuser immersive driving; 2) the visualization of surrounding traffic; 3) the specification and creation of reproducible traffic scenarios; and 4) the collection of meaningful driving behavior data. We use our framework to investigate the “rubbernecking” phenomenon, which refers to the slowing down of a driver due to an accident on the opposite side of the road, and its effect on the following drivers. The main contribution of the paper is the Scenario Markup Language (SML) framework, which is composed of: 1) the SML as a practical tool to specify dynamic traffic situations (e.g., an accident) and 2) the Scenario Control System to ensure the reproducibility of particular traffic situations, so that traffic engineers can obtain comparable data and draw valid conclusions. To demonstrate the effectiveness of our framework, we specified the traffic accident scenario in SML and conducted a study about the rubbernecking phenomenon. We report on the results of our study from two viewpoints: 1) the reproducibility of the traffic accident situation (i.e., state variables of interest are recreated successfully in 78% of the cases); and 2) the interactive car-following behavior of human subjects embedded in the traffic situation of the virtual environment.

Is Bus Overrepresented in Bluetooth MAC Scanner data? Is MAC-ID Really Unique?

One of the concerns about the use of Bluetooth MAC Scanner (BMS) data, especially from urban arterial, is the bias in the travel time estimates from multiple Bluetooth devices being transported by a vehicle. For instance, if a bus is transporting 20 passengers with Bluetooth equipped mobile phones, then the discovery of these mobile phones by BMS will be considered as 20 different vehicles, and the average travel time along the corridor estimated from the BMS data will be biased with the travel time from the bus. This paper integrates Bus Vehicle Identification system with BMS network to empirically evaluate such bias, if any. The paper also reports an interesting finding on the uniqueness of MAC-IDs.

Design of open source framework for traffic and travel simulation

For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia; the National Institute of Informatics, Tokyo; and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academics from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.

Road Feature Extraction from High Resolution Aerial Images Upon Rural Regions Based on Multi-Resolution Image Analysis and Gabor Filters

Accurate, detailed and up-to-date road information is of special importance in geo-spatial databases as it is used in a variety of applications such as vehicle navigation, traffic management and advanced driver assistance systems (ADAS). The commercial road maps utilized for road navigation or the geographical information system (GIS) today are based on linear road centrelines represented in vector format with poly-lines (i.e., series of nodes and shape points, connected by segments), which present a serious lack of accuracy, contents, and completeness for their applicability at the sub-road level. For instance, the accuracy level of the present standard maps is around 5 to 20 meters. The roads/streets in the digital maps are represented as line segments rendered using different colours and widths. However, the widths of line segments do not necessarily represent the actual road widths accurately. Another problem with the existing road maps is that few precise sub-road details, such as lane markings and stop lines, are included, whereas such sub-road information is crucial for applications such as lane departure warning or lane-based vehicle navigation. Furthermore, the vast majority of roadmaps aremodelled in 2D space, whichmeans that some complex road scenes, such as overpasses and multi-level road systems, cannot be effectively represented. In addition, the lack of elevation information makes it infeasible to carry out applications such as driving simulation and 3D vehicle navigation.

A Cyber-Physical System Simulator for Risk-Free Transport Studies

Traffic operations result from human decision making and complex multidriver interaction at different behavioral levels. Cyber-Physical System Simulator (CPSS) is a novel platform for conducting controlled and risk-free driving and traveling behavior studies. The key features of CPSS are: (1) simulation of multiuser immersive driving in a three-dimensional (3D) virtual environment; (2) integration of traffic and communication simulators with human driving based on dedicated middleware; and (3) accessibility of multiuser driving simulator on popular software and hardware platforms. This combination of features allows for the easy collection of large-scale data on interesting phenomena regarding the interaction between multiple user drivers, which is not possible with current single-user driving simulators. The papers contribution are threefold: (1) to introduce a multiuser driving simulator based on DiVE, the authors original massively multiuser networked 3D virtual environment; (2) to introduce OpenV2X, a middleware for simulating vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication; and (3) to present two experiments based on the CPSS platform. The first experiment investigates the “rubbernecking” phenomenon, where a platoon of four user drivers experiences an accident in the oncoming direction of traffic. Second, the authors report on a pilot study about the effectiveness of a Cooperative Intelligent Transport Systems advisory system with a focus on V2V communications to identify vehicles that drive at high speed.

Creating interactive driver experiences with the scenario markup language

Serious games became an important device for increasing the awareness of issues that are important to society. One such issue is the environmental impact of driving. To support the training and wide promotion of eco-friendly driving, an appropriate platform and tools are needed. In this paper, we present the Scenario Markup Language (SML), a simple yet expressive language for authoring realistic traffic situations. This effort is part of a novel framework for automatically generating complex scenarios in the transport domain. In particular, SML facilitates the scripting of behavioral driver studies in multi-user online three-dimensional (3D) virtual worlds.

International Traffic Database: Gathering Traffic Data Fast and Intuitive

Gathering real life data, for whatever type of use, is a time consuming job. A lot of data is measured and stored in several places and different formats around the world. While a lot of it is not used, other institutions gather similar data on different locations or, worse, on the same ones. In this way, a lot of money and time is spent unnecessarily (Miska and Lint 2006). Thus, the aim of the International Traffic Database (ITDb) project is to provide traffic data to various groups (researchers, practitioners, public entities) in a format according to their particular needs, ranging from raw measurement data to statistical analysis.

Sustainable management of data driven projects

Sustainable management of data driven projects is vital for the efficiency and success of a project, as well as for the task of knowledge management for the institution or consortium that is working on the project. With partners often being located in separate locations, data is kept redundant, exists in different versions and access is sometimes difficult. With the rise of cloud computing, web-based project management allows to overcome most of these drawbacks. This paper describes the project management framework of the International Traffic Database project, which extends the platform for standardized and geo-referenced traffic data storage, now with the possibility to handle whole project communication and publishing in one place.