ITS implementation plan for the Gold Coast area

ITS needs to be used to reinforce the planned major changes to the road functional hierarchy in the District, namely: • the use of Southport-Burleigh Rd. (SBR) as the major regional corridor; • the removal of through traffic from the GCH; • the use of Oxley Dr./Olsen Av./Ross St./NBR as another major north-south by-pass; • the use of Smith St.; NSR/Queen St.; NBR and Reedy Creek Rd. – West Burleigh Road as the major east-west access corridors. There is a need to integrate the proposed ITS measures into the current related plans for the Pacific Motorway and into the overall traffic control strategies for the area as a whole. In addition, the staging of the proposed plan needs to take into account the planned DMR capital Works Program. An index representing the degree of priority to be attached to each network link was developed to assist in the phased implementation of ITS technologies over the next 5 years. 'ITS Index' is made up of five variables, namely: • Accident rate factor • AADT • Volume/Capacity ratio • Delay • % Commercial Vehicles The main components of the ITS plan are shown diagrammatically in Figure 1. The latter assumes that the high level of ITS implementation on the Pacific Motorway will be extended in time to the remainder of that Highway. To assist in the implementation of the road hierarchy system, a new static signage plan should be implemented. This plan needs to reinforce the changes by clearly assigning single road names to corridors and by placing new signs at appropriate locations. Capturing Traffic Data The following corridors should be equipped with automatic traffic monitoring capability in priority order: High Priority ? SBR corridor from Smith St. connection to Reedy Creek Rd. ? Smith St. from Pacific Highway to High St. ? GCH from Pacific Highway to North St. Medium Priority ? Nerang-Broadbeach Rd/Ross St. to Nerang-Southport Rd. ? Nerang-Southport Rd from Pacific Highway to SBR ? Nerang-Broadbeach Rd from Pacific Highway to SBR The Smith St. link from the Pacific Motorway to Olsen Ave. should be considered as a freeway for monitoring purposes. The GCH along the coastal strip needs to be treated as a local distributor rather than as the major corridor. As a result, the future traffic surveillance priority should be low. At least one permanent environmental (vehicle emissions) monitoring station should be set up as part of the ITS plan. The most appropriate site for such a station would seem to be on the SBR corridor at the vicinity of Hooker Blv. intersection. Pacific Highway The Pacific Motorway project will set the benchmark for freeway incident detection and traffic management in the State. The high level of ITS implementation on the Motorway section will create a significant gap in performance and expectation, relative to the remainder of the Highway. It is recommended that the southern sections of the Pacific Highway be equipped to the equivalent level of traffic data collection and surveillance as the newly upgraded Motorway section, under a staged program. Travel Time Savings The travel time benefits of the full implementation of ITS over the network are likely to be of the order of at least 5 percent of vehicle-hours travelled on the affected links. At a discount rate of 6 percent, the total present value of the gross travel time benefit over 10 years is of the order of $200 million

Regional Data Archiving and Management for Northeast Illinois

This project studies the feasibility and implementation options for establishing a regional data archiving system to help monitor and manage traffic operations and planning for the northeastern Illinois region. It aims to provide a clear guidance to the regional transportation agencies, from both technical and business perspectives, about building such a comprehensive transportation information system. Several implementation alternatives are identified and analyzed. This research is carried out in three phases. In the first phase, existing documents related to ITS deployments in the broader Chicago area are summarized, and a thorough review is conducted of similar systems across the country. Various stakeholders are interviewed to collect information on all data elements that they store, including the format, system, and granularity. Their perception of a data archive system, such as potential benefits and costs, is also surveyed. In the second phase, a conceptual design of the database is developed. This conceptual design includes system architecture, functional modules, user interfaces, and examples of usage. In the last phase, the possible business models for the archive system to sustain itself are reviewed. We estimate initial capital and recurring operational/maintenance costs for the system based on realistic information on the hardware, software, labor, and resource requirements. We also identify possible revenue opportunities. A few implementation options for the archive system are summarized in this report; namely: 1. System hosted by a partnering agency 2. System contracted to a university 3. System contracted to a national laboratory 4. System outsourced to a service provider The costs, advantages and disadvantages for each of these recommended options are also provided.ICT-R27-22published or submitted for publicationis peer reviewe

Proactive Assessment of Accident Risk to Improve Safety on a System of Freeways, Research Report 11-15

This report describes the development and evaluation of real-time crash risk-assessment models for four freeway corridors: U.S. Route 101 NB (northbound) and SB (southbound) and Interstate 880 NB and SB. Crash data for these freeway segments for the 16-month period from January 2010 through April 2011 are used to link historical crash occurrences with real-time traffic patterns observed through loop-detector data. \u27The crash risk-assessment models are based on a binary classification approach (crash and non-crash outcomes), with traffic parameters measured at surrounding vehicle detection station (VDS) locations as the independent variables. The analysis techniques used in this study are logistic regression and classification trees. Prior to developing the models, some data-related issues such as data cleaning and aggregation were addressed. The modeling efforts revealed that the turbulence resulting from speed variation is significantly associated with crash risk on the U.S. 101 NB corridor. The models estimated with data from U.S. 101 NB were evaluated on the basis of their classification performance, not only on U.S. 101 NB, but also on the other three freeway segments for transferability assessment. It was found that the predictive model derived from one freeway can be readily applied to other freeways, although the classification performance decreases. The models that transfer best to other roadways were determined to be those that use the least number of VDSs–that is, those that use one upstream or downstream station rather than two or three.\ The classification accuracy of the models is discussed in terms of how the models can be used for real-time crash risk assessment. The models can be applied to developing and testing variable speed limits (VSLs) and ramp-metering strategies that proactively attempt to reduce crash risk

Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures

Reinforcement learning (RL) constitutes a promising solution for alleviating the problem of traffic congestion. In particular, deep RL algorithms have been shown to produce adaptive traffic signal controllers that outperform conventional systems. However, in order to be reliable in highly dynamic urban areas, such controllers need to be robust with the respect to a series of exogenous sources of uncertainty. In this paper, we develop an open-source callback-based framework for promoting the flexible evaluation of different deep RL configurations under a traffic simulation environment. With this framework, we investigate how deep RL-based adaptive traffic controllers perform under different scenarios, namely under demand surges caused by special events, capacity reductions from incidents and sensor failures. We extract several key insights for the development of robust deep RL algorithms for traffic control and propose concrete designs to mitigate the impact of the considered exogenous uncertainties.Comment: 8 page

Using Operations Data for Planning the the Delaware Valley: First Steps

Real-time traffic operations data has been gathered for several years on an increasing number of roads throughout the Delaware Valley. The archives of this data are a tremendous potential resource for transportation planning. Use of the data, however, has posed significant technical challenges. This report summarizes how the data can be used, the state of operations data for planning in the Delaware Valley, and the results of two case studies. The first case study used data from the Pennsylvania Department of Transportation's Dynac system about speed and travel time on a section of I-76. The second case study used data provided by the I-95 Corridor Coalition Vehicle Probe Project (VPP) from INRIX, a private-sector traffic data company. The second case study analyzed duration of congestion on weekdays in 2009 for freeways in the Delaware Valley. This analysis was used in the region's 2011 Congestion Management Process

An Unsupervised Feature Learning Approach to Improve Automatic Incident Detection

Sophisticated automatic incident detection (AID) technology plays a key role in contemporary transportation systems. Though many papers were devoted to study incident classification algorithms, few study investigated how to enhance feature representation of incidents to improve AID performance. In this paper, we propose to use an unsupervised feature learning algorithm to generate higher level features to represent incidents. We used real incident data in the experiments and found that effective feature mapping function can be learnt from the data crosses the test sites. With the enhanced features, detection rate (DR), false alarm rate (FAR) and mean time to detect (MTTD) are significantly improved in all of the three representative cases. This approach also provides an alternative way to reduce the amount of labeled data, which is expensive to obtain, required in training better incident classifiers since the feature learning is unsupervised.Comment: The 15th IEEE International Conference on Intelligent Transportation Systems (ITSC 2012

Transit Performance Measures in California

This research is the result of a California Department of Transportation (Caltrans) request to assess the most commonly available transit performance measures in California. Caltrans wanted to understand performance measures and data used by Metropolitan Planning Organizations (MPOs) and transit agencies to help it develop statewide measures. This report serves as a summary reference guide to help Caltrans understand the numerous and diverse performance measures used by MPOs and transit agencies in California. First, investigators review the available literature to identify a complete transit performance framework for the purposes of organizing agency measures, metrics, and data sources. Next, they review the latest transit performance measures documented in planning reports for the four largest MPOs in California (San Francisco Bay Area, Los Angeles, San Diego, and Sacramento). Researchers pay special attention to the transit performance measures used by these MPOs, because these measures are available for the majority of California’s population. Finally, investigators summarize 231 performance measures used by a total 26 local transit agencies in the State of California, based on transit planning documents available on the internet

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio