| Lecture | Date | Subject | Optional Readings | Deadlines | ||||
|---|---|---|---|---|---|---|---|---|
| Unit 1: Traffic flow fundamentals | ||||||||
| 1 | W 2/7 | Introduction, Context, and Administrivia [slides] | ||||||
| 2 | F 2/9 | Graphical analysis I - Time-space diagrams [slides] | ||||||
| F 2/9 | PSet1+CL1 out | |||||||
| R1 | M 2/12 | Recitation 1 [slides] | ||||||
| 3 | W 2/14 | Graphical analysis II - Cumulative diagrams [slides] | ||||||
| 4 | F 2/16 | Microscopic traffic models - Vehicle dynamics, kinematics, and behavior [slides] | ||||||
| R2 | T 2/20 | Recitation 2 [slides] | ||||||
| 5 | W 2/21 | Macroscopic traffic models - Traffic flow theory [slides] | ||||||
| Unit 2: Queueing systems | ||||||||
| 6 | F 2/23 | Uncertainty in transportation - Probabilistic concepts [slides] | ||||||
| R3 | M 2/26 | Recitation 3 [slides] | ||||||
| 7 | W 2/28 | Queuing theory fundamentals - Stochastic delays [slides] | ||||||
| W 2/28 | PSet1+CL1 due PSet2+CL2 out | |||||||
| 8 | F 3/1 | Queuing models - Stochastic throughput [slides] | ||||||
| R4 | M 3/4 | Recitation 4 [slides] | ||||||
| 9 | W 3/6 | Markov chains - Beyond basic facility dynamics [slides] | ||||||
| 10 | F 3/8 | Stochastic simulation [slides] | ||||||
| F 3/8 | Pset 2 due | |||||||
| R5 | M 3/11 | Recitation 5 [slides] | ||||||
| 11 | W 3/13 | Network queues and delays - Queuing network models, Quiz review [slides] | ||||||
| 12 | F 3/15 | Quiz 1 | ||||||
| Unit 3: Machine learning for traffic control | ||||||||
| R6 | M 3/18 | Recitation 6 (Quiz1 Review) | ||||||
| 13 | W 3/20 | Markov decision processes - Modeling sequential decision problems [slides] | ||||||
| 14 | F 3/22 | Dynamic programming - Solving deterministic finite horizon MDPs [slides] | ||||||
| F 3/22 | CL2 due PSet3+CL3 out | |||||||
| Mar 25-29 | Spring Break | |||||||
| R7 | M 4/1 | Recitation 7 [slides] | ||||||
| 15 | W 4/3 | Dynamic programming, Part 2 - Solving stochastic finite horizon MDPs [slides] | ||||||
| 16 | F 4/5 | Reinforcement Learning - Solving MDPs from samples [slides] | ||||||
| R8 | M 4/8 | Recitation 8 [slides] | ||||||
| 17 | W 4/10 | Deep reinforcement learning - Solving large-state MDPs [slides] | ||||||
| 18 | F 4/12 | Advanced topics in reinforcement learning [slides] | ||||||
| Unit 4: Optimizing transportation resources | ||||||||
| R9 | M 4/15 | Recitation 9 [slides] | ||||||
| 19 | W 4/17 | Linear programs I - Modeling mathematical programs [slides] | ||||||
| W 4/17 | PSet3+CL3 due PSet4+CL4 out | |||||||
| 20 | F 4/19 | Linear programs II - Graphical analysis [slides] | ||||||
| R10 | M 4/22 | Recitation 10 [slides] | ||||||
| 21 | W 4/24 | Linear program solvers - Simplex method [slides] | ||||||
| 22 | F 4/26 | Integer programs - Branch-and-bound, Quiz review [slides] | ||||||
| R11 | M 4/29 | Recitation 11 [slides] | ||||||
| 23 | W 5/1 | Intelligent Coordination for Sustainable Roadways [slides] | ||||||
| W 5/1 | PSet4 due | |||||||
| 24 | F 5/3 | Quiz 2 | ||||||
| 25 | W 5/8 | In-class student presentations | ||||||
| 26 | F 5/10 | In-class student presentations | CL4+Projeect Report due | |||||
| Assignment | Covers (general) | Release Date | Due Date |
|---|---|---|---|
| PSet1+CL1 | Unit 1 | F 2/9 | W 2/28 |
| PSet2 | Unit 2 | W 2/28 | F 3/8 |
| CL2 | Unit 2 | W 2/28 | F 3/22 |
| PSet3+CL3 | Unit 3 | F 3/22 | W 4/17 |
| Project Proposal | F 4/5 | ||
| PSet4 | Unit 4 | W 4/17 | W 5/1 |
| CL4 | Unit 4 | W 4/17 | F 5/10 |
| Project Presentations | W 5/8 or F 5/10 (before your presentation) | ||
| Project report (if required) | F 5/14 |