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3. Emission-based traffic responsive signal control system
Khalighi, F., and Christofa, E. 2015. Emission-based Signal Timing Optimization for Isolated Intersections. Transportation Research Record: Journal of the Transportation Research Board, 2487:1-14, doi:10.3141/2487-01.Khalighi, F., 2015. A Real-time Signal Control System to Minimize Emissions at Isolated Intersections, MSc. Thesis, University of Massachusetts Amherst.
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Research Objectives
Given the lack of a real-time signal control system that minimizes total emissions of cars and buses by utilizing modal-based emission estimation:
Develop an analytical model to estimate emissions using macroscopic traffic stream characteristics and modal emission estimation
Design a traffic responsive signal control system that minimizes total emissions of cars and buses at isolated intersections.
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Assumptions
Impact of bus stops on auto and transit operations are ignored
Transit vehicles travel in mixed lanes along with autos
Vehicles arrive at a constant rate
Analytical models developed:
to infer trajectories given certain macroscopic characteristics such as arrival rate and saturation flow
assuming that auto and transit vehicle arrival times are known in real-time
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ITS Technologies for real-world implementation
Sensing Systems (detectors) Vehicle arrival rates Travel times
Automated Vehicle Location (AVL)Systems Bus dwell times at stopstravel
timesarrival times
Source:http://www.precisiontrafficsafety.com/products/sensys/
Source: www.tc.umn.edu
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subject to:
(Minimum green for each phase and lane group)
(Constant cycle length)
Min
Mathematical Program
Total Emissions of Cars and Buses
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Methodology
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Methodology
d1,T
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VSP (Vehicle Specific Power)value
VSPmode
emissionrate
Speed Acceleration Links grade
Assumptions:o Links grade = 0o Constant cruising speed = 45 (km/hr)o Constant acceleration/deceleration rates
- Cars: acceleration rate = 3 (ms2
) and deceleration rate = 4 (ms2
)- Buses: acceleration rate = 2 (m
s2) and deceleration rate = 2 (m
s2)
Modal Emission Rate Estimation
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Emission Rates
Vehicle Type
Operating Mode
HC
Gasoline Autos
Acceleration
7.7
2.5
Deceleration
0.9
0.5
Cruising
1.2
0.4
Idling
0.3
0.4
Diesel Buses
Acceleration
263.5
2.1
Deceleration
45.0
1.3
Cruising
133.3
1.7
Idling
45.0
1.3
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Test Site: Mesogeion & Katechaki Avenues, Athens, Greece
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-20%
-15%
-10%
-5%
0%
5%
0.4 0.5 0.6 0.7 0.8 0.9
% C
hang
e in
Em
issi
on (H
C) f
rom
Ve
hicl
e-ba
sed
to E
mis
sion
-bas
ed
Opt
imiz
atio
n
Intersection Flow Ratio (Y)
Auto Bus Total
Results: Comparison with Vehicle-based optimizationEffect of Auto Demand
Auto demand increases
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Findings
Reduction in overall emissions and transit emissions
The lower the auto demand, the higher the overall reduction in emissions
Results depend on the vehicle technology and emission factors
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Current and Future Work
Real-time signal control system with TSP that accounts for stochasticity in transit vehicle arrivals
Real-time signal control system to minimize person delay and emissions
Prediction algorithms for vehicle arrivals using low resolution AVL data
Extension of real-time signal control systems to networks
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Thank you
Yashar Zeinali Farid ([email protected])
Farnoush Khalighi ([email protected])
Eleni Christofa ([email protected])
3. Emission-based traffic responsive signal control systemResearch ObjectivesAssumptionsITS Technologies for real-world implementationMathematical ProgramMethodologyMethodologyModal Emission Rate EstimationEmission RatesTest Site: Mesogeion & Katechaki Avenues, Athens, GreeceResults: Comparison with Vehicle-based optimizationFindings Current and Future WorkSlide Number 14
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