[The slides in this presentation contain the University of Alabama’s logo.]

Slide 1: Student Presentation 2

Title: Traffic Signal Optimization for Connected Vehicles

Student: Md Abu Sufian Talukder, PhD Candidate

Advisor: Alex Hainen, PhD, Associate Professor

Idea

• Develop controller logic to use CAV BSMs to call/extend phases
• Use vehicle trajectory information to anticipate vehicle movements

Benefits

• Reduce delay at intersections; consider vehicles on all approaches
• Increase safety by protecting the dilemma zone
• Expands detection coverage; reduce future detection maintenance

[This slide contains an image of an intersection, signal box, traffic signals, and arrows connecting them.]

Slide 2: Dedicated Short Range Communication Installation
ALDOT and City of Tuscaloosa setting up CV and V2X device

[This slide contains a photograph of bucket truck with a person in the bucket working on a utility pole. A photo of a DSRC box is overlaid on top of the photo. The DSRC photo points to the location on the utility pole that the person is working on.]

Slide 3: Travel Safely: DSRC/SPaT Translation @85 Intx
Connected Vehicles and V2X Applications/Research (C-V2N)

[This slide contains a photo of the SPaT Translator situated among other computers and wires.]

Slide 4: CAV Platform and Smartphone Application in Place!
Free to download and ready to expand for Alabama

[This slide contains a digital map showing many roads with many stop light symbols along the roads.]

Slide 5: Travel Safely: Applied Information ‐ Glance
SPaT and BSM Platform for Data Collection

[This slide contains an image is of a spreadsheet with a list of intersections and an image of an iPhone overlaid on top of the spreadsheet. An arrow points from the iPhone to the bottom row of the spreadsheet and a word bubble is pointing to the iPhone with the phrase “BSM Trajectory Data!!!”]

Slide 6: ALDOT/UA Research
Connected Vehicle Applications

Connected Vehicle Systems Application
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Question: How can connected vehicle Basic Safety Messages (BSMs) are used in traffic control software and algorithms?
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Application 1 Full 100% BSM information to replace detection (future application)	or	Application 2 Freight Priority through existing controller functionality (near term application)

Slide 7: Proposed Application: Signal BSM Logic
Use Basic Safety Messages to Call/Extend Signal Phases

Idea

• Develop controller logic to use CAV BSMs to call/extend phases
• Use vehicle trajectory information to anticipate vehicle movements

Benefits

• Reduce delay at intersections; consider vehicles on all approaches
• Increase safety by protecting the dilemma zone
• Expands detection coverage; reduce future detection maintenance

[This slide contains seven images: (1) a photo of control box labeled “Existing System Output” with an arrow pointing to (2) a photo of the SPaT Translator with an arrow pointing to (3) an iPhone in a holding case. (4) an image of an iPhone in a holding case with an arrow pointing to (5) a detector with an arrow pointing to (6) a photo of a control box labeled “Proposed System Input.”]

Slide 8: First Trajectory Radar BSM Control!
Econolite Sky, 4x Radars to Place Virtual BSM Calls

[This slide contains two images: (1) a photo of traffic signals pointing out radar detection systems installed on the pole and (2) a photo of computer equipment with the radar system hooked up to computer inputs.]

Slide 9: First Trajectory Radar BSM Control!
Econolite Sky, 4x Radars to Place Virtual BSM Calls

[This slide contains two images: (1) a photo of many input ports for various cord types and (2) a photograph of a computer motherboard.]

Slide 10: First Glimpse of Trajectory Data ‐ One Approach, vBSM
Econolite Sky, 4x Radars to Place Virtual BSM Calls

[This slide contains two images: (1) an aerial view of digital rendering of an intersection and (2) a photo of a multilane road and cars and trucks.]

Slide 11: Putting It All Together: C-V2N, SPaT, BSM, vBSM, Sky
Combining Data to Generate Trajectory Data

[This slide contains two images: (1) a photo of a multilane road and (2) a photo from the driver’s seat of a car looking out to a road.]

Slide 12: Trajectories through BSM (CV) and vBSM
Biggest advancement in signal control, and solves CV % rate

[This slide contains two images: (1) a photo of a multilane road and (2) a photo from the driver’s seat of a car looking out to a multilane road. Several lines overlay the both images.]

Slide 13: Signal Control Logic Using Vehicle Trajectory Data
BSM Trajectory Data and Measuring Delay

Talukder, M., Lidbe, A., Tedla, E., Hainen, A. and Atkison, T. (2021). “Trajectory Based Signal Control in Mixed Connected Vehicle Environments.” Journal of Transportation Engineering, Part A: Systems. DOI: 10.1061/JTEPBS.0000510

[This slide contains two images: (1) a computer‐generated image of an intersection with the caption “Real‐time BSM trajectory data and signal control” and (2) a screenshot of the first page of an academic paper titled “Trajectory‐Based Signal Control in Mixed Connected Vehicle Environments.”]

Slide 14: Signal Control Logic Using Vehicle Trajectory Data
Trajectory Data and Control Algorithm! 8-15% Improvement Queues/Delay

BSM Trajectory Data

Raw Trajectory Data							Analyzed Output
Timestep	Front X	Front Y	Rear X	Rear Y	Speed (mph)	Acceleration	Distance from Stopbar (ft)	Delay (seconds)	Cumulative Delay (seconds)
50.0	-66.17	-58.58	-69.93	-59.96	26.72	-0.25	117.18	0.11	0.11
51.0	-55.15	-54.35	-58.89	-55.81	25.43	-1.82	78.51	0.15	0.26
52.0	-45.86	-50.59	-49.57	-52.12	18.84	-3.40	45.66	0.37	0.63
53.0	-39.56	-48.08	-43.30	-49.54	11.65	-3.03	23.50	0.61	1.25
54.0	-36.00	-46.74	-39.75	-48.18	5.63	-2.34	11.30	0.81	2.06
55.0	-34.56	-46.16	-38.29	-47.62	1.76	-1.19	6.57	0.94	3.00
56.0	-34.18	-46.01	-37.92	-47.47	0.36	-0.38	5.46	0.99	3.99
57.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	4.99
58.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	5.99
59.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	6.99
60.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	7.99
61.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	8.99
62.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	9.99
63.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	10.99
64.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	11.99
65.0	-34.15	-46.00	-37.89	-47.46	0.00	0.00	5.37	1.00	12.99
66.0	-30.65	-44.45	-34.33	-46.04	10.30	2.72	-8.72
67.0	-25.35	-41.84	-28.95	-43.62	16.03	2.46	-27.60
68.0	-18.17	-37.56	-21.62	-39.62	21.28	2.27	-54.74
69.0	-9.16	-32.00	-12.58	-34.09	25.73	1.22	-89.34
70.0	1.31	-26.59	-2.27	-28.40	26.71	0.25	-128.01

Talukder, M.A.S., Lidbe, A., Tedla, E., Hainen, A. and Atkison, T. (2021). “Trajectory Based Signal Control in Mixed Connected Vehicle Environments.” Journal of Transportation Engineering, Part A: Systems. DOI: 10.1061/JTEPBS.0000510

[This slide contains a flowchart of Signal Control Algorithm and Traffic Simulation.]

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