KLK721: Improved Simulation of Driver Behavior: Modeling Protected and Permitted Left-Turn Operations at Signalized Intersections

Principal Investigators

Ahmed Abdel-Rahim and Karen Den Braven

Type of Research

20% basic; 80% applied research

Project Objectives

This project addresses several of the NIATT goals as cited in the Strategic Plan:  

      Goal 1, Strategy 1.1 (Improve our nation’s transportation research database)
      Goal 3, Strategies 3.1,3.4 (Enlarge our interdisciplinary teams of faculty and
                                          develop new knowledge using research groups)

This project is a completely new area of endeavor for NIATT.  The vehicle and traffic centers are proposing to jointly examine the feasibility of combining the area of traffic operations with that of vehicle performance.
Background

The Clean Air Act (CAA) requires EPA to regularly update its mobile source emission models. EPA continuously collects data and measures vehicle emissions to make sure the Agency has the best possible understanding of mobile source emissions.  MOVES2010 is the state-of-the-art upgrade to EPA’s modeling tools for estimating emissions from highway vehicles, based on analysis of emission test results. The name “MOVES” is an acronym for “Motor Vehicle Emission Simulator.” MOVES2010 replaces the previous model for estimating on-road mobile source emissions, MOBILE6.2. The new model, MOVES2010, has been designed to do calculations with information in databases, using the open source database management software known as MySQL.

MOVES2010 will become EPA’s approved motor vehicle emission factor model for estimating volatile organic compounds (VOCs), nitrogen oxides (NOx), carbon monoxide (CO), direct particulate matter (PM10 and PM2.5) and other pollutants and precursors from cars, trucks, motorcycles, and buses by state and local agencies outside of California.  EPA intends to include in the notice a two-year grace period for using MOVES2010 for transportation conformity purposes.

A comparison between MOVES 2010 and MOBILE6.2 emission output revealed the following:

  • For volatile organic compounds (VOCs): For all the urban counties modeled, mobile source VOC emissions were lower using MOVES2010 than previously estimated using MOBILE6.2. This difference is most noticeable for Tier 1 and newer vehicles, especially for evaporative emissions.

  • For oxides of nitrogen (NOx): Emissions from both light- and heavy-duty trucks are higher than previously estimated. Using MOVES2010 and assuming no change in extended idle activity as a fraction of total activity, EPA projects that uncontrolled extended idle emissions from heavy-duty vehicles will become a significant share of the on-road mobile source NOx inventory in the future. In some urban areas of the country, in fact, extended idle emissions could comprise approximately one quarter of total heavy-duty NOx emissions by 2020. This increase in the fraction of overall emissions represented by idling emissions is due to the fact that new heavy-duty vehicle standards are driving down regular exhaust emissions, making the idle fraction bigger by comparison.

  • For PM2.5: EPA’s estimate of mobile source PM2.5 emissions using MOVES2010 is significantly higher compared to MOBILE6.2 for both light- and heavy-duty vehicles and for all of the urban areas modeled. For passenger cars and light trucks, these increases are based on data developed as part of EPA’s Kansas City study, which showed much higher PM2.5 emissions at low ambient temperatures than previously known. For heavy-duty trucks, MOVES2010 incorporates new data from a large study of trucks conducted by the Coordinating Research Council (known as the CRC E-55 study) which includes deterio­ration effects on in-use emissions. MOVES2010 also models the impact of vehicle speed and load on PM emissions, showing very high rates of PM generation in stop-and-go traffic conditions. This high emission rate consists of the emissions produced while the engine is under increased load while accelerating (i.e., the “go” phase of stop-and-go driving) as well as the emissions produced while the vehicle is stopped and therefore not accumu­lating any mileage, thus resulting in higher overall emissions per total mile driven.

Most traffic operations software packages do not use the MOVES or MOBILE5 models. A number of microscopic traffic models predict vehicle emissions from look-up tables on a second-by second basis as a function of vehicle type, speed, and acceleration. CORSIM, a microscopic model, uses unpublished vehicle emission rates from dynamometer testing as the basis of its emissions model. The program determines the total emissions on each link by applying the default emission rates (based on speed and acceleration) to each vehicle for each second the vehicle travels on the given link. Another microscopic model, INTEGRATION, computes the fuel consumption for each vehicle on a second-by-second basis as a function of speed and acceleration. It then estimates vehicle emissions on a second-by-second basis as a function of the fuel consumption, ambient air temperature, and the extent to which a particular vehicle’s catalytic converter has already been warmed up during an earlier portion of the trip.

SYNCHRO, a macroscopic traffic model, contains a simplified emissions model. SYNCHRO predicts vehicle emissions by first predicting fuel consumption, which is calculated as a function of vehicle-miles, total delay in veh-hr/hr, and total stops in stops per hour. Then, the fuel consumption is multiplied by an adjustment factor (differs depending on the type of emissions) to estimate vehicle emissions.

Other macroscopic traffic models, such as Transyt-7F, Passer II-90, HCS, and SIGNAL97, do not include emission predictors. Because these are widely used traffic models, it is difficult for traffic analysts to estimate vehicle emissions in many cases.

The University of California at Riverside as part of the National Cooperative Highway Research Project (NCHRP) 25-11 conducted a project the led to the development of  an emissions model for Light-Duty Vehicle (LDV) as a function of the vehicle's operating mode. The model, which was based on laboratory dynamometer testing, used a total of 47 parameters to estimate vehicle tailpipe emissions, of which 16 are readily available and 31 need to be calibrated under laboratory conditions. Another model, MEASURE, predicts vehicle emissions as a function of engine power, kinetic energy, speed, and acceleration. This model is different than the EPA’s MOVES and MOBILE5 from a traffic parameter standpoint in that it uses both speed and acceleration as model inputs, rather than just speed.

Note that while these models predict fuel use and emissions, none of them uses the resulting information to examine whether modified traffic operations could significantly improve these. 

One particular area where vehicle road load has proven to be crucial is in the accurate prediction of the “real-world MPG” for plug-in hybrid vehicles.  Effects of driver behavior in the form of an “aggressive” versus “non-aggressive” driver have been noted.  However, the calculated MPG for these vehicles can vary by an order of magnitude, far more than can be accounted for by driver behavior.  In addition, the calculations vary significantly from one location to another, one city to another, suggesting that the local traffic patterns and signaling are an important factor.

The output of the proposed exploratory research project should provide a means to determine whether the coupling of vehicle modeling with traffic flow information can provide a better means to predict vehicle performance, and assist in developing more efficient traffic operations protocols for signalized intersection approaches.
Task Descriptions

Task 1: Documentation of existing literature and the state-of-the-practice in the area of fuel consumption and emission modeling.
This task will be jointly executed by both the CE and ME graduate students. Topics covered in the literature search will include: fuel consumption and emission estimate procedures in microscopic and macroscopic traffic simulation models; data input/output and emission and fuel consumption tables in the EPA MOVES model, relationship between vehicle trajectory at signalized intersection approaches and fuel consumption and emissions; and rates of fuel use and emission during each “mode” of travel throughout the intersection approach: acceleration, deceleration, cruise, and idle.

Task 2: Model fuel consumption and emissions for an urban arterial.
This task will be executed by the CE student. A case study of an urban corridor will be modeled using both the VISSIM microscopic simulation model and the MOVES model. The objective of this task is to document the input data needed for the model, the calibration and validation process, an the fuel consumption and emission output.

Task 3: Relate fuel use and emissions to each “mode” of travel throughout the intersection approach: deceleration, idle, acceleration, and cruise.
This task will be conducted by the ME student. Lab tests will be conducted to collect fuel consumption and emission data under different engine operating states in the lab.  Output from these lab tests will be used to calibrate and validate different fuel use and emissions models.

Task 4: Field data collection.
This task will be conducted by both the CE and ME students. In this task, the lab data will be further expanded by field data collected under different field operation conditions (outside temperature, vehicle type, etc.)

Task 5: Comparing field data with microscopic simulation and MOVES model parameters.
This task will be executed jointly by both the CE and ME students. The task will focus on comparing the field data with those used in the microscopic simulation and MOVES fuel consumption and emissions tables. The objective of this Task is to assess the validity of the fuel consumption and emissions data included in the microscopic simulation and MOVES models as they relate to signalized intersection operations.  The output of this task will be used to identify data and research needs in this area

Task 6: Project final report.

 

Task

Description

I.

Technical Tasks

1

Literature Review

Topics covered in the literature search will include: fuel consumption and emission estimate procedures in microscopic and macroscopic traffic simulation models; data input/output and emission and fuel consumption tables in the EPA MOVES model, relationship between vehicle trajectory at signalized intersection approaches and fuel consumption and emissions; and rates of fuel use and emission during each “mode” of travel throughout the intersection.

2

Model fuel consumption and emissions

A case study of an urban corridor will be modeled using both the VISSIM microscopic simulation model and the MOVES model. The objective of this task is to document the models input data need, the calibration and validation process, an the fuel consumption and emission output.

3

Relate fuel use and emissions to different travel modes in signalized intersection approaches

Lab tests will be conducted to collect fuel consumption and emission data under different engine operating conditions in the lab. Output from these tests will be used to calibrate and validate different fuel use and emissions models.

4

Field data collection

Lab data will be further expanded by field data collected under different field operation conditions (outside temperature, vehicle type, etc.).

5

Comparing field data with models’ parameters

The task will focus on comparing the field data with the data used in the microscopic simulation and MOVES fuel consumption and emissions tables. The objective of this Task is to assess the validity of the fuel consumption and emissions data included in the microscopic simulation and MOVES models as they relate to signalized intersection operations.

II.

Technology Transfer

1

Presentations

Present several papers at national SAE, ITE, and TRB conferences and at regional and national combustion institute conferences.

2

Papers

Submit several peer-reviewed papers to SAE, ASME, TRB, and ASCE for publication.

3

Theses

Prepare and defend MSME and MSCE theses.

4

Reports

Prepare annual NIATT report.

5

Outreach

The project report will provide guidelines for transportation agencies on how to model and estimate fuel consumption and emissions savings that could result for signal improvement projects.

Milestones
Budget Information

The total amount of funding requested for this project is $70,557.

Student Involvement

Two graduate students, one from the CE department and one from the ME department, will be involved in this project.

 

Student

Candidate

Months

1

CE graduate student

MSCE

12

1

ME graduate student

MSME

12

 2

Total Graduate Students

 

 

Technology Transfer Activities

Two Master’s theses.

Papers to SAE, TRB, ASME and ASCE on results from the work.

Potential Benefits of the Project:

This combined research area is a new one for NIATT.  While the PIs have experience separately in the areas of traffic operations and vehicle performance (including fuel use and emissions measurement), this project has the potential to tie traffic operations management decisions with vehicle operating conditions.  This first effort will involve determining the state of the art in this area, and determining how best to try to intertie signalized intersection design with vehicle design and performance.

Project status

Complete

Final Report

KLK721_N12-12

 

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