Eco-Vehicle Speed Control at Signalized Intersections using I2V Communication Driving Transportation with Technology Dr. Hesham Rakha, Dr. Kyoungho Ahn & Raj Kishore Kamalanathsharma Center for Sustainable Mobility Virginia T ech Transportation Institute (VTTI), Blacksburg, VA VTTI E-mail: hrakha@vt.edu. Phone: +1-540-231-1505 1
Overview Introduction Literature Review Driving Transportation with Technology • Control Logic • Analytical Modeling Model Description • Physical Modeling • Fuel/Emissions Modeling Example Illustration Case Studies Eco-Vehicle Speed Control Application VTTI Conclusions & Recommendations 2
Introduction The research develops an eco-speed control system to reduce vehicle fuel consumption in the vicinity of signalized Driving Transportation with Technology intersections. I2V SPaT Vehicle Trajectory Display Uses I2V Using available Using state-of- Vehicle-speed is communication SPaT and the-art vehicle assumed to be to receive SPaT queued vehicle fuel force-followed. information at information consumption Alternately, an upcoming optimize the and acceleration instantaneous traffic signal. vehicle models, fuel velocity trajectory. consumption of advisory can be vehicle displayed to the trajectories are driver. VTTI compared. 3
Similar Research Author Findings Shortcomings Barth et al. [3] • Studied TSS to drivers using CMS • Used TTR info to advise and in-vehicle devices. drivers not to slow down • Found 40% savings if red is near. Driving Transportation with Technology Asadi & Vahidi • Developed a cruise control which • Alternate speed profiles [4] reduces Pr(reach stop-bar @ red). not studied using fuel • Showed 47% savings. consumption models. Tielert et al. • Used VISSIM simulation to find • Used PHEM model for [5] factors affecting fuel savings if I2V comparison and not communication is present optimization. Malakorn & • Studied a CACC based on I2V • No FC model in Park [6] • min{length of dec & acc} & objective. min{idling time} • Downstream neglected. VTTI Mandava et al. • Optimal instantaneous velocity to • No FC model in [7] drivers using TSS. objective • min{rate of dec/acc} 4
Model Description Previous publications used a simplified objective function. Here, the system computes a “proposed time Driving Transportation with Technology to reach intersection” using • SPaT information • Queued vehicle information • Approaching vehicle information Computes a “proposed fuel-optimal trajectory” using • Vehicle deceleration and acceleration models VTTI • Microscopic fuel consumption models • Roadway characteristics 5
Model Description Lead-vehicle Vehicle information acceleration (V2V) models Driving Transportation with Technology Queued vehicle Fuel- information consumption models (V2I & I2V) Fuel- SPaT info. From upcoming Roadway optimal intersection characteristics VTTI trajectory (I2V) 6
Model Logic Signal is currently GREEN • Case 1: GREEN will continue so that vehicle can pass through at current speed. Driving Transportation with Technology • Case 2: GREEN will end soon but vehicle can legally pass through intersection during the green or yellow indication if it speeds up within speed limit. • Case 3: GREEN will end soon and vehicle cannot pass during this phase. Signal is currently RED • Case 4: RED will continue but vehicle needs to be delayed to receive GREEN indication. VTTI • Case 5: RED will end soon so that vehicle will receive GREEN when it reaches stop-line at current speed. 7
Model Logic Cases 1,2, 3 and 5 are fairly simple Case 4 requires trajectory optimization every time step within detection zone. Driving Transportation with Technology Min{fuel consumed} Subject to • Fixed travel distance upstream. • Fixed time to reach intersection. • Variable speed at intersection. VTTI • Vehicle acceleration characteristics downstream to accelerate back to initial speed. 8
Model Logic Speed trajectory at intersection is divided into: • Upstream section (deceleration to achieve delay) & • Downstream section (accelerate to original speed) Driving Transportation with Technology • Cruising section to maintain a constant distance of travel. VTTI 9
Deceleration Model TTG = t seconds Conserve x and t : DTI = x meters − − 2 2 v v v v x = + = + and a s r a s t x x Approach speed = v a m/s r d v 2 d s Driving Transportation with Technology Speed at signal = v s m/s Combining them: Delay required = ∆ t seconds − − 2 2 v v 1 v v = + − a s a s t x Veh. deceleration = d m/s 2 d v 2 d s Cruising dist. = x r m Solving for v a : ( ) = − ⋅ + ⋅ − + 2 v v d t d d t 2 v t 2 x s a a For any v a , x r is given by: VTTI − 2 2 v v = − a s x x r 2 d 10
Acceleration Model Rakha & Lucic Model [8] was used. • Vehicle dynamics model. Driving Transportation with Technology • Acceleration = Resultant Force/mass • Resultant Force = Tractive Force - Resistive Force P = βη µ F min 3600 f , m g p d ta v ρ c VTTI ( ) = + + + 2 r 0 R C C A v mg c v c mgG d h f r 1 r 2 25.92 1000 11
Fuel Consumption Model Virginia T ech Comprehensive Power-based Fuel Model (VT -CPFM) Type 1 21 . Driving Transportation with Technology • Based on instantaneous power α + α + α ∀ ≥ 2 ( ) ( ) ( ) 0 P t P t P t = 0 1 2 FC t ( ) α ∀ < ( ) 0 P t 0 • Parameters α 0 , α 1 and α 2 can be calibrated using EPA fuel economy ratings. • Does not result in a bang-bang control VTTI • Optimum acceleration is not necessarily full throttle acceleration 12
Example Illustration Simulation was conducted for different approach speeds considering the following Driving Transportation with Technology parameters: • TTG = t =14 s • DTI = x = 200 m • Approach speed = v a = 20 m/s • Delay required = ∆ t = 4 s • d min = 0.82 m/s 2 (computed) VTTI • d max = 5.90 m/s 2 (limiting). 13
VTTI Driving Transportation with Technology Example Illustration 14
Simulation Results Cruising Fuel (l) Acceleration Fuel (l) Upstream Fuel (l) Fuel consumed in seven cases of 30% throttle by Chevy Malibu (l) 0.045 Driving Transportation with Technology optimum 0.04 Fuel Consumed (l) 0.035 0.03 0.025 0.02 0.015 0.01 0.005 0 VTTI 1 2 3 4 5 6 7 Case Number (increasing initial deceleration>> ) 15
Case Studies Experiment repeated using various sets of • Approach speeds Driving Transportation with Technology • Desired delay estimates • Vehicle Types 80 cases simulated maintaining a constant DTI of 200 m. VTTI [ ] = → + × − FC ds ( ) FC v ( v ) FC ( v ) x x − i i s a cruise a max i acc 16
Case Studies Four vehicles were tested: • Vehicles selected were available at VTTI and Driving Transportation with Technology thus were validated using field measurements Vehicle 1 Vehicle 2 Vehicle 3 Vehicle 4 Vehicle Info SAAB Mercedes Chevy Chevy Model 95 R350 Tahoe Malibu Year 2001 2006 2008 2007 Engine Size (L) 2.3 3.5 5.3 2.2 EPA Rating (City/Highway) 21/30 16/21 14/20 24/34 VTTI Fuel-optimal speed 45.9mph 37.3mph 37.3mph 41.6mph 17
Sample Results (Fuel-consumption matrix) Less fuel consumed Driving Transportation with Technology More fuel consumed VTTI Inference 1: The greater the acceleration level, the higher is the fuel consumed. 18
Sample Results (fuel consumed in ml at 20% throttle) Results from two separate simulated cases are shown below (for 20% throttle) and are color coded according to fuel consumed. Driving Transportation with Technology Va = 20m/s, TTG = 14s, DTI = 200m Va = 11m/s, TTG = 22s, DTI = 200m dec(m/s 2 ) SAAB R350 TAHOE MALIBU dec(m/s 2 ) SAAB R350 TAHOE MALIBU 0.8163 50.90 76.00 59.20 44.60 0.1736 20.20 23.90 27.90 17.90 1 47.50 70.00 55.50 42.20 0.25 20.10 23.90 27.30 18.00 1.25 47.00 67.00 53.00 41.70 0.5 20.30 24.20 27.40 18.60 1.5 46.00 67.50 52.40 42.20 0.75 21.00 24.20 27.20 18.90 1.75 45.70 66.90 53.20 42.00 1 21.20 24.50 27.30 18.80 2 45.40 66.40 52.80 41.60 1.5 21.20 24.50 27.30 18.80 2.5 45.10 65.90 52.20 41.40 2 21.40 24.80 27.40 18.90 3 46.00 65.40 51.80 41.20 3 21.40 24.80 27.50 18.90 4 45.70 65.40 51.70 41.10 4 21.40 24.80 27.50 19.00 VTTI 5 45.70 64.90 51.30 41.90 5 21.40 24.80 27.50 19.00 Inference 2: Fuel-optimal case may not always involve minimal deceleration level 19
Fuel-optimal Speeds Sample Results Chevy Tahoe 37.3 mph Chevy Malibu 41.6 mph (deceleration in m/s 2 in optimum case) Chevy Tahoe Chevy Malibu Approach Speed (mph) Approach Speed (mph) Driving Transportation with Technology 25 35 45 55 25 35 45 55 2 1.00 2.00 1.00 4.75 2 0.25 0.50 1.75 2.50 Delay (s) Delay (s) 4 5.75 3.50 5.75 5.00 4 5.75 1.25 5.75 3.00 6 2.75 5.00 5.75 5.50 6 0.25 1.00 5.75 5.50 8 0.75 5.75 5.75 5.50 8 3.25 5.75 4.50 5.75 10 3.75 5.75 5.25 5.75 10 1.00 5.75 4.75 4.25 Inference 3: Deceleration in fuel-optimal case is proportional to VTTI (a) Approach Speed (b) Delay to be induced in the trajectory 20
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