Virtual Mobility Lab for Innovative Transportation Research
Funding sources: CFI, with Chris Bachmann and Bruce Hellinga
Project Overview:
This project is intended to establish a new Virtual Mobility Lab (VML) which will feature a set of state-of-the art, multi-modal pedestrian, biking and driving simulators, transportation data collection devices, and supporting computing platforms. The lab will be linked to our external partners’ cloud portals for both offline and online access to big data (pedestrian, cyclist, and motorized traffic flows) from hundreds of Miovision and third-party traffic sensors (e.g., cameras, loops, Bluetooth/Wifi detectors) being instrumented at over 300 intersections in the Region of Waterloo (ROW). In addition to the required VR simulation software systems, the VML will also be equipped with state-of-the-art transport systems modelling and simulation software such as INRO EMME (a multimodal travel demand analysis system), PTV Vissim (a microscopic multi-modal traffic flow simulator), and Trafficware Synchro (a macroscopic traffic analysis and signal optimization tool).
Advancing Traffic Management Using Bluetooth/WIFI and Connected Vehicle Data
Funding sources: NSERC ALLIANCE + OCE-VIP
Project Overview:
The proposed research is a collaborative effort between the University of Waterloo and SMATS aiming to develop new traffic performance measurement and signal control systems using Bluetooth/Wifi and CV data. Specifically, the proposed research is to achieve the objectives of developing new metrics for assessing the road traffic performance at various spatiotemporal scales; developing new AI-based traffic signal control methods that can take advantage of the new Big Traffic Data sources; and exploring innovative simulation-based techniques for assessing the effectiveness of the proposed performance metrics and control models. The proposed research will address the challenge posed by two strikingly different data sources: high-frequent but low-quality Bluetooth/Wifi data vs. low-frequent but high-quality CV data. It will generate new knowledge, innovative traffic analysis and signal control methodologies, and new models and tools that can be immediately tested and implemented in the field, benefiting Ontario and all municipalities across Canada.
Collaborative Research for Improve Rail Safety
Funding sources: Transport Canada
Project Overview:
This is a collaborative research program participated by the University of Alberta, McGill University and York University, funded by Transport Canada. The program includes five projects aiming at addressing a wide range of issues related to rail transportation: 1.Safety management of railway crossings – developing and refining Transport Canada’s risk assessment and countermeasure analysis tool – GradeX; (Drs. Liping Fu and Luis Miranda-Moreno) 2.Risk assessment and causality analysis of train derailments (Drs. Peter Park and Liping Fu) 3.Real-time safety monitoring and conflict analysis using video technology and machine learning (Drs. Luis Miranda-Moreno and Liping Fu) 4.Connected Vehicle (CV) technologies for improving user warning at grade crossings (Drs. Tony Qiu, Tae Kwon and Liping Fu) 5.Mobile data collection system for improving data updating and sharing of rail network inventory (Dr. Liping Fu)
Intelligent Systems for Sustainable Urban Mobility (ISSUM)
Funding sources: Ontario Research Fund
Project Overview:
Recent technological developments have created new opportunities to improve the transportation system. ISSUM is a joint project with five researchers from York University and University of Waterloo that aims to captalise on these technological developments and apply them. The goal of this project is to research and develop integrated intelligent systems for sensing, analysis, simulation and 3D visualization of urban population mobility. The components that are related my research focus on the following: a). develop improved techniques for road and traffic condition monitoring, such as integrating estimates from video analytics with crowd-sourced road condition data and RWIS weather data to yield more accurate and complete coverage; b). develop improved traffic network signal optimization algorithms that can make use of new data sources such as queue detection from video cameras, Bluetooth/Wifi data, and crowdsource travel time data from smartphones. We will also investigate the potential of integrating a self-learning, evolving optimization process to reduce the computational demand.
Optimal RWIS Sensor Density and Location
Development of guidelines for determining the optimal location and density of RWIS to achieve more efficient and effective winter maintenance operations.
Funding sources: The Aurora Program
Project Overview:
Accurate and timely information on road weather and surface conditions (RSC) in winter seasons is a necessity for road authorities to optimize their winter maintenance operations and improve the safety and mobility of the traveling public. One of the primary tools for acquiring this information is road weather information systems (RWIS) that include various environmental and pavement sensors for collecting real-time data on precipitation, pavement temperature, snow coverage, etc. Many transportation agencies have invested millions of dollars in establishing their current RWIS network and continue expanding their network for better winter maintenance decision support and traveller information provision.
While effective in providing real-time information on road weather and surface conditions, RWIS stations are costly to install and operate and therefore can only be deployed at a limited number of locations. Considering the vast road network that often needs to be monitored and the kind of varied road conditions that could occur during winter events, RWIS stations must be placed strategically so that they are collectively most informative in providing the inputs required for accurate estimation of the road weather and surface conditions of the whole highway network.
Thus, the primary goal of this project is to develop a methodology for determining the optimal RWIS sensor density and location over a highway network. In particular, the research has the following specific objectives:
1. Conduct a thorough review on literature related to the characterization, estimation and forecasting of winter road weather and road surface condition (RSC), cost-benefit analysis of RWIS, and methodologies and models for solving location problems;
2. Synthesize the current best practice and guidelines for expanding RWIS network and locating RWIS as well as regular weather stations;
3. Develop a quantitative understanding of spatial and temporal variation of road weather and surface conditions based on both RWIS and local weather data. The key parameters of interest include air temperature, surface temperature, and snow cover,
4. Develop guidelines and an optimization model for determining the the optimal number and location of RWIS sensors for different climate types.
The proposed research will begin in Oct. 2012 and be completed by Oct. 2014.
Automated Winter Road Surface Condition Monitoring System
Project Overview:
Monitoring of winter road surface conditions during and after a snow storm is essential for most transportation agencies in Canada who are responsible for winter road maintenance. Information on road surface conditions can be used to assess the need for maintenance service, compare the effectiveness of different treatment methods, and evaluate the quality of the maintenance services delivered by contractors across different maintenance yards.
Real-time information on road surface conditions is also invaluable to the road users who can use the information to improve their travel and driving decisions such as where, when and in what mode to travel. Currently, monitoring of winter road surface conditions is mostly done through personal observations and manual recording, which is limited in repeatability, details and timeliness. While recent developments in sensor technologies such as continuous friction measurement equipment (CFME), web-based surveillance video, and spectroscopic snow and ice cover sensors have afforded new opportunities for quick and objective assessment of road surface conditions, they are costly for implementation and limited in spatial coverage and completeness. The proposed project is to further advance our new winter road condition monitoring solution featuring innovative applications of machine vision, artificial intelligence, and data fusion techniques on a platform of cloud-based wireless and Internet technologies.
The prototype solution includes a fully automated data collection unit consisting of a GPS, a camera, an IR thermometer, and interfaces to other sensors such as plowing/salting status. The data are processed onboard and then transmit to a central server where data from a large number of participating vehicles is processed to generate road surface condition information that is of high spatial, temporal and lateral coverage. The availability of such complete information has the potential to profoundly change the winter maintenance practice and will benefit all Canadians with improved mobility, road safety, and environmental protection.
Development and Evaluation of an Adaptive Traffic Control System...
Development and Evaluation of an Adaptive Traffic Control System for Urban Networks Based on Video Sensor Data
Funding sources: NSERC Engage Program, 2012-2013
Project Overview:
This project is to address two technical challenges faced by the industrial partner in the process of developing a new video-based, adaptive intersection traffic signal control system.
The first challenge is to determine the current state of the traffic network, such as link volumes, turning movements, size and speed of platoons, based on the company’s video sensor data. The video traffic data includes traffic volumes entering and exiting each approach of an intersection being monitored, which by itself is incomplete for the purpose of traffic signal control. The missing state variables along with those of the intersections without any camera must be estimated using models so that all traffic in the controlled area are considered in signal optimization.
The second challenge is how to predict the future state of the traffic network based on the current traffic state, historical traffic patterns, and a proposed signal control plan. Without a reliable prediction model, the signal optimization process could just yield suboptimal myopic solutions. This Engage project will help the company develop a truly innovative traffic management solution, which will enhance the company’s position to become a leading traffic solution provider in Canada. The new traffic control system is expected to benefit all Canadians by minimizing traffic delay, improving intersection safety, and reducing pollution and fuel consumptions.
Evaluation and Optimization of Snow/Ice Control Operations for Railway Platforms
Development of relevant guidelines that Go Transit could use for implementing a
cost-effective platform winter maintenance program.
Funding sources: Metrolink - Go Transit
Project Overview:
Railway platforms must be kept free of snow and ice all the time as any slip falls at these locations could have fatal consequences. At the platforms that do not have canopies or snow melting systems installed, this high level of service requirement would mean that snow and ice control operations, such as plowing and salting, must be deployed frequently and/or excessively. However, snow clearing operations on a railway platform could interfere with the normal operation of the train service, which is a significant safety concern. As a result, railway flagmen have to be deployed to coordinate the snow clearing and train operations, which is not only costly itself but also imposes additional constraints on when plowing and salting can be done. The availability of flagmen is often limited, creating uncertainty as to when the crew can plow and salt the platform during a significant storm event. Therefore, heavier-than-usual amounts of salts are commonly applied to maintain an acceptable level of safety.
However, excessive application of salts could cause several other problems. First of all, salts have been shown to be detrimental to the environment and corrosive to the infrastructure (e.g., platform concrete, lamp posts, shelters and tracks) and vehicles. Secondly, salt residuals on the platform could be carried into the trains by passengers, causing door malfunctions and damages to the train body. Lastly, residual salt runoff from the platform is a strong electrolyte at a high level of concentration, which could cause nearby crossing signals to be short-circuited.
To address these challenges, GO Transit is developing a comprehensive winter maintenance plan to reduce salt use while maintaining a safe walking and waiting environment for its patrons. An integral component of this plan is to adopt practices that reduce salt use, such as Environment Canada’s Best Salt Management Practices, anti-icing strategies, and use of pre-wetted salt, brine, and organic alternatives. However, no scientific and uniform guidelines currently exist on what snow and ice control methods, materials, and application rates should be applied for railway platforms. The primary goal of this project is to develop relevant guidelines that Go Transit could use for implementing a cost effective platform winter maintenance program.
Winter Road Maintenance - Performance Measurement and Improvement
Development of Output and Outcome Models for End-results Based Winter Road Maintenance Standards
Funding sources: MTO, Aurora, Salt Institute
Safety Benefit Analysis and Modeling
This component investigates the quantitative relationship between road safety (maintenance outcome) and road surface conditions (RSC) measures (maintenance output).
Mobility Benefit Analysis and Modeling
This component investigates the quantitative relationship between traffic mobility (maintenance outcome) and RSC measures (maintenance output).
Performance Measures and Service Standards
The objective of this component is to evaluate alternative performance measures for monitoring winter road maintenance operations with a specific focus on their advantages and limitations as maintenance performance indicators to link maintenance input to maintenance outcomes. The research will focus mainly on the three performance categories recommended in the NCHRP Project 6-17 "Performance Measures for Snow and Ice Control Operations", namely, bare pavement status (e.g. BP recovery time), traffic flow (e.g. speed) and crash risk (e.g. friction).
RSC Monitoring Technologies and Tools
The first objective of this component is to evaluate the performance of some existing and new RSC monitoring technologies. The second objective is to develop models and tools for RSC estimation and forecasting.
Snow and Ice Control of Parking Lots and Sidewalks (SICOPS)
Optimum Deicing and Anti-icing for Parking Lots and Sidewalks
Funding sources: NSERC - CRD, Landscape Ontario
Canada spends more than $1.1 billion dollars annually on winter snow and ice control of roads, parking lots and sidewalks, which includes application of approximately 5 million tonnes of salt. While the use of this large amount of salts makes the public safer, they also cause damages to the environment, the infrastructure and the vehicles – a growing public concern.
Significant research efforts have been devoted to the development of improved snow and ice control strategies, methods, and materials. However, most of these studies have focused on roadway maintenance with few defensible and uniform guidelines available for snow and ice control of parking lots and sidewalks. This lack of uniform salting guidelines, in combination with the private owners' desire to minimize their business risk and legal exposure, has resulted in excessive quantities of salts being applied in these areas.
The main objective of this project is to determine the optimum salt application rates for parking lots and sidewalks through a series of rigorous scientific tests under some specific range of weather events and local conditions. The project is divided into three components: a) Test and optimization of deicing treatments, b) Test and optimization of anti-icing treatments, and 3) Evaluation of organic deicing and anti-icing products. The proposed research is application focused with some elements of basic research. The results from the research will be adopted, initially by the members of Landscape Ontario and ultimately by all maintenance contractors across Ontario, which will improve professionalism and environmental stewardship while reducing over-salting and operational costs. The findings from this research are also applicable to other provinces in Canada and thus benefit all Canadians.
Safety Analysis of Highway-Railway Grade Crossings
Models and Tools for Evaluating the Safety of Highway-Railway Grade Crossings in Canada
Funding sources: Transport Canada
1. A Decision Support Model for Prioritizing Safety Improvement Programs at High-Risk Grade Crossings (completed)
Highway-rail grade crossing collisions are a source of concern for regulators, railway authorities and the public-at-large. Each year in Canada, about 50 people lose their lives as a direct result of grade-crossing collisions (Transport Canada, Railway Safety Facts, 1996). There are over 20,000 highway-rail grade crossings in Canada, covering a wide spectrum of physical characteristics, control devices and usage. To improve safety at all 20,000 grade crossings to a uniform standard would be prohibitively expensive and impractical. Accordingly, any comprehensive safety program must begin by first identifying those crossings where the risk of crashes is unacceptably high, and where safety countermeasures are most warranted. The objective of this research was to develop a methodology and models that would enable this type of analysis.
As a result of this project, a web based application called GradeX (www.gradex.ca) has been developed which implements a risk-based approach to the process of screening highway-
railway grade crossings for safety improvement. The system accounts both the expected frequency of collisions as well as their expected consequences (fatalities, personal injuries and property damages). GradeX has become a valuable decision support tool for Transport Canada safety engineers and safety inspectors and railway and highway authorities to screen high risk crossings and develop cost-effective safety improvement programs. It integrates a comprehensive risk-based analysis framework with a simple interface for easy access to a set of complex statistical models and a large repository of inventory and collision data for highway-railway grade crossings in Canada.
2. Benefit Assessment of Grade Crossing Regulatory Proposal (active)
The main objective of this project component is to develop an improved procedure for quantifying the expected benefit of the Transport Canada's grade crossing regulatory proposal. GradeX was developed mainly for the purpose of evaluating the risk of highway-railway grade crossings and identifying the high-risk crossings for safety improvement. While its current version has integrated some of the basic functions for cost benefit analysis (CBA), it misses many countermeasures and safety factors that must be considered in evaluating the new regulations.
3. Improvement and Development of Collision Risk and Treatment Effectiveness Models for GradeX(proposed)
This research is to make some improvements to the GradeX model with the following specific objectives: investigate safety trend of Canadian crossings based on historical collision data and upgrading projects by incorporating trend terms and major external variables pertaining to changes in policy, safety improvement programs and other factors; recalibrate the risk models implemented in the current version of GradeX using latest inventory and collision data as well the state-of-the-art modeling techniques and hotspot identification methods, investigate and document various risk mitigation countermeasures currently available, or likely to become available in the foreseeable future, in terms of their implementation costs and expected effects; develop estimates on accident modification factors using a before-after observational analysis within the Bayesian framework for the typical crossing treatment methods used in Canada.
Organic Products for Snow and Ice Control
Evaluation of the Field Performance of Organic Products for Snow and Ice Control
Funding sources: City of Burlington, Town of Oakville, MTO
Many municipalities such as Burlington and Oakville are under increasing pressure to maintain high level of safety and mobility of their highways and streets in the winter seasons, while working with limited financial resources. Salts, both in solid and liquid forms, remains to be a primary mean for winter road maintenance due to their effectiveness in breaking and preventing the bonding of snow and ice to road surfaces. Large amounts of salts are applied every year to the highways and streets, which has increasingly become a public concern due to their detrimental effect to the environment, the infrastructure and the vehicles. Transportation agencies are actively seeking ways to reduce salt use while keeping their road safe and moving. New deicing chemicals and additives, mostly bio-based, are being developed in the industry which promises to delivery better snow and ice control performance with minimum environmental side effects. However, information on the field performance of these new chemicals as compared to regular salts is still not available to the users. How are their effectiveness related to the climate and weather conditions? What is their comparative performance in field as compared to conventional materials? What are the optimal mixing ratios and application rates when used in combination of regular salts and brines?
The main objective of this project is to evaluate the effectiveness of several organic products used as either pre-wetting agents or additives to enhance the performance of regular rock salts or salt brines. The project focus is specifically on the field performance of these products in some specific climate conditions. While it is known that the effectiveness of these products depends on the proportion (or ratio) by which these products are mixed with salt or brine as well as the application rate of the end mixtures, this project considers only the ratios and application rates recommended by the product providers and used by the two municipalities.