PSU Friday Transportation Seminar 10/4/2013, featuring Michael Mauch of DKS Associates: Real-world traffic trends observed in PORTAL and INRIX traffic data are used to expand the performance measures that can be obtained from Portland Metro's travel demand model to include the number of hours of congestion that can be expected during a typical weekday and travel time reliability measures for congested freeway corridors.
Presentation delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30, during the session entitled Goods Movement - Reaching Destinations Safely and Efficiently.
Prepared by
François Bélisle, Eng., B. Sc., M.A.
Marilyne Brosseau, Eng., M.Eng.
Steve Careau, Eng.
Philippe Mytofir, techn.
Validated by:
Stephan Kellner, Eng., M.Eng.
Traffic volume study-opresentation by ahmed ferdous - 1004137-buetAhmed Ferdous Ankon
Traffic volume study-opresentation by Ahmed ferdous.......Please remind this is not a unique effort..My Classmates and specially Ahasanullah Un iversity Students were a major help...We have tried DATA ANALYSIS part to be a solo doing ..But other parts are nearly copy past from net especially from AUST ian...Hope you can do the whole on your own.....
Our project is the complete study about both Spot speed studies and Speed delay time survey. This topic is a part of Transportation Engineering. This report helps you to understand this topic in detail. This report will also help you to make project on associated topics in traffic engineering. In spot speed, We discussed regarding various methods available to perform the test, Our team practically performed test and established a speed limit zone near a school. Coming to speed delay time survey, we conducted a survey at a selected stretch and came out with solutions to the problems faced by the vehicle users using that stretch.
Presentation delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30, during the session entitled Goods Movement - Reaching Destinations Safely and Efficiently.
Prepared by
François Bélisle, Eng., B. Sc., M.A.
Marilyne Brosseau, Eng., M.Eng.
Steve Careau, Eng.
Philippe Mytofir, techn.
Validated by:
Stephan Kellner, Eng., M.Eng.
Traffic volume study-opresentation by ahmed ferdous - 1004137-buetAhmed Ferdous Ankon
Traffic volume study-opresentation by Ahmed ferdous.......Please remind this is not a unique effort..My Classmates and specially Ahasanullah Un iversity Students were a major help...We have tried DATA ANALYSIS part to be a solo doing ..But other parts are nearly copy past from net especially from AUST ian...Hope you can do the whole on your own.....
Our project is the complete study about both Spot speed studies and Speed delay time survey. This topic is a part of Transportation Engineering. This report helps you to understand this topic in detail. This report will also help you to make project on associated topics in traffic engineering. In spot speed, We discussed regarding various methods available to perform the test, Our team practically performed test and established a speed limit zone near a school. Coming to speed delay time survey, we conducted a survey at a selected stretch and came out with solutions to the problems faced by the vehicle users using that stretch.
This presentation focuses on arterial performance measures, reviewing two successful case studies:
- KAI’s validation of Bluetooth MAC readers and their measurement of signal timing changes using MAC readers along Tualatin-Sherwood Road
- Purdue University’s research, led by Dr. Darcy Bullock to field measure quality of signal timing offsets and vehicle arrivals on green versus red using local controller software
- Peter Koonce provided an overview of arterial performance within the City of Portland and a regional vision for next steps, particularly focused on multi-modal and emergency management applications of the arterial data currently collected and to be collected in the future.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Application of Cumulative Axle Model To Impute Missing Traffic Data in Defect...IJERDJOURNAL
Abstract: An automatic vehicle classification (AVC) station is typically composed of three sensors per lane. Instances of data missing from the traffic datasets collected at such stations can occur as a result of issues such as one of the sensors malfunctioning. Although various data imputation methods, such as autoregressive integrated moving average (ARIMA), exponential smoothing, and interpolation, have been proposed to deal with this problem, they are either too complicated or have significant errors. This paper proposes a model, called the “cumulative axle model,” that minimizes such errors in traffic volume data resulting from a malfunctioning sensor at AVC stations. Evaluations conducted in which missing traffic volume data imputation was simulated using the proposed cumulative axle model indicate that our method has a mean absolute percentage error (MAPE) of 2.92%. This is significantly more accurate than that of conventional imputation methods, which achieve a MAPE of only 10% on average.
BASED ON BTECH CIVIL ENGINEERING SYLLABUS,PRESENTATION OF TRAFFIC VOLUME STUDIES,OBJECTS OF TRAFFIC VOLUME STUDIES
TRAFFIC VOLUME STUDIES IS ONE OF THE TRAFFIC ENGG. STUDIES
This presentation focuses on arterial performance measures, reviewing two successful case studies:
- KAI’s validation of Bluetooth MAC readers and their measurement of signal timing changes using MAC readers along Tualatin-Sherwood Road
- Purdue University’s research, led by Dr. Darcy Bullock to field measure quality of signal timing offsets and vehicle arrivals on green versus red using local controller software
- Peter Koonce provided an overview of arterial performance within the City of Portland and a regional vision for next steps, particularly focused on multi-modal and emergency management applications of the arterial data currently collected and to be collected in the future.
Presentation from NORTHMOST - a new biannual series of meetings on the topic of mathematical modelling in transport.
Hosted at its.leeds.ac.uk, NORTHMOST 01 focussed on academic research, to encourage networking and collaboration between academics interested in the methodological development of mathematical modelling applied to transport.
The focus of the meetings will alternate; NORTHMOST 02 - planned for Spring 2017 - will be led by practitioners who are modelling experts. Practitioners will give presentations, with academic researchers in the audience. In addition to giving a forum for expert practitioners to meet and share best practice, a key aim of the series is to close the gap between research and practice, establishing a feedback loop to communicate the needs of practitioners to those working in university research.
Application of Cumulative Axle Model To Impute Missing Traffic Data in Defect...IJERDJOURNAL
Abstract: An automatic vehicle classification (AVC) station is typically composed of three sensors per lane. Instances of data missing from the traffic datasets collected at such stations can occur as a result of issues such as one of the sensors malfunctioning. Although various data imputation methods, such as autoregressive integrated moving average (ARIMA), exponential smoothing, and interpolation, have been proposed to deal with this problem, they are either too complicated or have significant errors. This paper proposes a model, called the “cumulative axle model,” that minimizes such errors in traffic volume data resulting from a malfunctioning sensor at AVC stations. Evaluations conducted in which missing traffic volume data imputation was simulated using the proposed cumulative axle model indicate that our method has a mean absolute percentage error (MAPE) of 2.92%. This is significantly more accurate than that of conventional imputation methods, which achieve a MAPE of only 10% on average.
BASED ON BTECH CIVIL ENGINEERING SYLLABUS,PRESENTATION OF TRAFFIC VOLUME STUDIES,OBJECTS OF TRAFFIC VOLUME STUDIES
TRAFFIC VOLUME STUDIES IS ONE OF THE TRAFFIC ENGG. STUDIES
Traffic Congestion PowerPoint Presentation, how to reduce traffic congestion, costs of traffic congestion, road accidents and traffic congestion, loss of time due to congestion, pollution, health , diseases, photos, images
This paper proposes algorithms for dynamic travel time prediction to provide reliable real-time
travel time information using probe travel time data collected by a dedicated short range communication (DSRC)
system. The travel time predictions were performed using arrival-time-based travel time; subsequently, the
accuracy of these predictions was evaluated using the concurrent departure-time-based travel time data, which
were also collected by the DSRC system. The prediction methodologies proposed in this research include the
Kalman filter and a newly developed algorithm that uses weighting factors according to probe sample size. An
evaluation of the performance of the two algorithms showed their errors ranged from 5 to 7%, thereby showing
satisfactory results. Considering the fact that the Kalman filter requires historical travel time for prediction, the
similarity between the historical and current data is core factor for reliable travel time prediction. On the other
hand, the newly developed algorithm does not need historical data, thereby the benefit could be enhanced
especially when historical travel time data analogous to current ones are not easily available.
Case Studies in Managing Traffic in a Developing Country with Privacy-Preserv...Biplav Srivastava
Simulation is known to be an effective technique to understand
and manage traffic in cities of developed countries. However, in developing countries, traffic management is lacking due to a wide diversity of vehicles on the road, their chaotic movement, little instrumentation to sense traffic state and limited funds to create IT and physical infrastructure to ameliorate the situation. Under these conditions, in this paper, we present our approach of using the Megaffic traffic simulator as a service to gain actionable insights for two use-cases and cities in India, a first. Our approach is general to be readily used in other use cases and cities; and our results give new insights: (a) using demographics data, traffic demand can be reduced if timings of government offices are altered in Delhi, (b) using a mobile company’s Call
Data Record (CDR) data to mine trajectories anonymously,
one can take effective traffic actions while organizing events
in Mumbai at local scale.
Roland is currently working with TfL on the Surface Intelligent Transport System, which is looking to improve the insight available from existing and new data sources. Have worked on event driven architectures for many years and across many sectors although with a primary focus on Transport.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
1. Beyond Peak Hour Volume-to-Capacity:
Developing Hours of Congestion
Mike Mauch
DKS Associates
2. Presentation Overview
Introduction to the Hours of Congestion (HOC) project
Data sources – PORTAL and tube counts
Observed trends in the count data
HOC model goodness of fit
Peak Spreading
Observed trends and forecasting “hours of congestion”
Concluding Remarks
3. How Can Transportation Decisions Be Made
When Standards Are Not Meaningful?
What does it mean when peak
hour volume to capacity (v/c) ratios
far exceed 1.0?
What is the difference between a
peak hour v/c ratio of 1.3 and 1.6?
How much worse is congestion on
the facility?
Evaluating only peak hour level-of-
service (LOS) provides myopic
understanding of congestion.
A performance measure of the
“duration” of congestion is
needed to evaluate networks in
these conditions
4. Current Regional Travel Demand Models Are Not Built
To Predict Congestion Duration & Peak-Spreading
Trips are developed for daily trip purposes
Peak period trip tables are built with fixed time-of-day
factors
Portland Metro Model Time Periods
AM Peak (7AM - 9AM, 2 hours)
Midday Peak (Noon - 1PM, 1 hour)
PM Peak (4PM - 6PM, 2 hours)
Network congestion affects trip distribution, mode
choice, and assignment, but excess demand is not forced
into shoulder periods
5. Congestion Duration Analysis Can Provide Decision
Makers Insight Into the Reality of Congestion
If financial constraints, land use forecasts, and policies on facility sizing
= severe peak hour failure, how many hours of the day are congested?
Hour
VehiclesperHour
6. Hours of Congestion (HOC) Approach: Data Mining
to Build a Travel Demand Model Post-Processing Tool
Data Mining Sources
PORTAL Data (Database of Freeway Loop Detectors) – 4 yrs of data
ATR Data (Database of Permanent Count Recorders) – 4 yrs of data
Roadway Tube Counts (Sample Daily Hourly Profiles) – 100+ data points
Bus GPS Records (Database of Corridor Travel Speed) – 6 weeks of data
7. Data Mining Must Include Data Cleaning
Data Screening Process
Identify Locations of
Interest
Filter to General Purpose
Lanes
Remove weekends and
holidays
Review data quality
diagnostics and filter out
“suspect” data
455 Valid Detectors
Data
Quality
Filters
Raw
Data
665 Loop Detector Locations
8. Step #1: Can Daily Traffic Volume Be Predicted
From Peak Period & Midday Data Points?
ADT = 1.30 *VolsAM-2 + 10.67* VolsMidday-1 + 1.58*VolsPM-2
9. Step #1: Can Daily Traffic Volume Be Predicted
From Peak Period & Midday Data Points?
ADT = 1.30 *VolsAM-2 + 10.67* VolsMidday-1 + 1.58*VolsPM-2
> summary(lm(ADT~AM2+Midday1+PM2+(-1), data=ODOT))
Call: lm(formula = ADT ~ AM2 + Midday1 + PM2 + (-1), data = ODOT)
Residuals:
Min 1Q Median 3Q Max
-5696.49 -97.86 578.70 1183.60 4131.34
Coefficients:
Estimate Std. Error t value Pr(>|t|)
AM2 1.30360 0.07008 18.60 <2e-16 ***
Midday1 10.66799 0.20618 51.74 <2e-16 ***
PM2 1.57994 0.05039 31.35 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 1544 on 579 degrees of freedom
Multiple R-squared: 0.9987, Adjusted R-squared: 0.9987
F-statistic: 1.465e+05 on 3 and 579 DF, p-value: < 2.2e-16
10. Step #2: Can Hourly Traffic Volume Be Predicted
With Daily, Peak Period & Midday Data Points?
12. Result: A Tool That Can Estimate & Graphically
Display Hourly Volume Profiles
Southbound
13. Result: A Tool That Can Estimate & Graphically
Display Hourly Volume Profiles
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
US - 99 E -- SE Mcloughlin Blvd N/O SE Park Ave, Year 2005
Estimated
Empirical
Northbound
15. The Hours of Congestion Tool Helps Identify and
Assess Locations for Operations Improvements
VehiclesperHour
Hour
Lower Boones Ferry Road (northbound), 2035
16. Project Team Review of HOC application (1/2)
The results of the Hours of Congestion sample
corridor analysis reasonably match empirical data
considering the accuracy of raw model data.
The network plots generated with the Hours of
Congestion results are easy to graphically present
and explain.
The Hours of Congestion application is flexible
enough to be applied to more focused corridor
studies with post-processed volume data used as
inputs.
17. Project Team Review of HOC application (2/2)
The Hours of Congestion data and network plots should be viewed
critically, as queue spillbacks and the corridor-wide impact on hours of
congestion is not captured with this link specific application. This is
similar to conducting traffic signal analysis using isolated HCM
methodology instead of coordinated corridor analysis in Synchro, or
looking at traditional model link v/c plots where congestion does not
impact upstream or downstream results.
Overall, the link-based application is recognized as not being as robust as
a trip-table based Dynamic Traffic Assignment (DTA) or activity based
modeling tool, but it is reasonable as an interim analysis tool applied to
four-step travel model volumes over the next few years as Metro
develops a more robust travel model. Even though the results of the
Hours of Congestion analysis does not adjust trip tables and/or reassign
traffic, the resulting application is quite useful at a macroscopic level as a
prioritization and general policy tool, providing valuable information on
levels (hours) of congestion not otherwise available.
19. Forecasting the Duration of Congestion Improves
Regional Transportation Discussions
Hours of Congestion provides a duration measure for
congested urban networks
Hours of Congestion adds a new dimension to
understanding key regional bottlenecks
Hours of Congestion helps identify and assess locations
for operations improvements
Hours of Congestion provides a comparison to known
nationwide severely congested corridors
20. Hours of Congestion provides a duration measure for
congested urban networks
OR 43 (Macadam Avenue) northbound
at Gaines Street, 2035
I-5 northbound ramp to Marquam Bridge, 2035
VehiclesperHour
Hour
VehiclesperHour
Hour
21. Hours of Congestion adds a new dimension to
understanding key regional bottlenecks
22. Hours of Congestion helps identify and assess
locations for operations improvements
23. Hours of Congestion provides a comparison to known
nationwide severely congested corridors
Location Corridor Year
Hours of
Congestion
per Weekday
Portland, OR
I-5 south of
Columbia River
2009 4 to 5
Portland, OR
I-5 between
I-405 and I-84
2035 12 to 14
New York, NY I-95 2009 15
Chicago, IL I-90/I-94 2009 14
Los Angeles, CA US-101 2009 14
Source 2009 Data: INRIX National Traffic Scorecard 2009 Annual Report
24. HOC – implemented as an embedded model script
or post model run Excel-based application