## Lecture scribing instruction (extra credit):

- Please sign up to scribe. Check piazza for the signup sheet.
- Scribe template: Template

Lecture | Date | Subject | Optional Readings | Deadlines | ||||
---|---|---|---|---|---|---|---|---|

Unit 1: Traffic flow fundamentals | Deterministic modeling | ||||||||

1 | W 9/8 | Introduction, context, and administrivia [slides] | ||||||

2 | F 9/10 | Graphical analysis I - time-space diagrams [slides] | ||||||

R1 | M 9/13 | Recitation 1 [recitation 1] | ||||||

T 9/14 | HW1 out | |||||||

3 | W 9/15 | Graphical analysis II - cumulative diagrams [slides] | ||||||

4 | F 9/17 | Vehicle dynamics, kinematics, and behavior (microscopic perspective) [slides] | ||||||

R2 | M 9/20 | Recitation 2 [recitation 2] | ||||||

T 9/21 | HW2 out | |||||||

5 | W 9/22 | Traffic flow theory (macroscopic perspective) [slides] | ||||||

Unit 2: Capturing uncertainty in transportation | Queueing theory | ||||||||

6 | F 9/24 | Uncertainty in transportation - probabilistic concepts [slides] | ||||||

R3 | M 9/27 | Recitation 3 [recitation 3] | ||||||

T 9/28 | CP1 out | |||||||

7 | W 9/29 | Stochastic delays - queuing theory fundamentals [slides] | ||||||

8 | F 10/1 | Stochastic throughput - queuing models [slides] | ||||||

R4 | M 10/4 | Recitation 4 [recitation 4] | ||||||

M 9/4 | HW3 out | |||||||

9 | W 10/6 | Facility dynamics - Markov chains [slides] | ||||||

10 | F 10/8 | Network queues and delays - queuing network models | ||||||

W 10/13 | CP2 out | |||||||

11 | W 10/13 | Stochastic simulation + Quiz review [slides] | ||||||

12 | F 10/15 | Quiz 1 | ||||||

Unit 3: Control & decision making in transportation | Deep reinforcement learning | ||||||||

13 | W 10/20 | Sequential decision problems (deterministic) - dynamic programming [slides] | ||||||

14 | F 10/22 | Stochastic sequential problems - Markov decision processes [slides] | ||||||

F 10/22 | HW4 out | |||||||

R5 | M 10/25 | Recitation 5 [recitation 5] | ||||||

15 | W 10/27 | Advanced dynamic programming - infinite horizon MDPs [slides] | ||||||

16 | F 10/29 | Unknown transitions and rewards - reinforcement learning [slides] | ||||||

R6 | M 11/01 | Recitation 6 [recitation 6] | ||||||

17 | W 11/3 | Handling very large state spaces - deep learning [slides] | ||||||

W 11/3 | CP3 out | |||||||

18 | F 11/5 | Deep reinforcement learning and autonomy in traffic [slides] | ||||||

R7 | M 11/8 | Recitation 7 [recitation 7] | ||||||

Unit 4: Efficiently allocating resources | Mathematical programming | ||||||||

19 | W 11/10 | Linear programs I - modeling mathematical programs [slides] | ||||||

20 | F 11/12 | Linear programs II - graphical analysis [slides] | ||||||

R8 | M 11/15 | Recitation 8 [recitation 8] | ||||||

T 11/16 | HW5 out | |||||||

21 | W 11/17 | Linear program solvers - simplex method [slides] | ||||||

22 | F 11/19 | Integer programs - branch-and-bound + Quiz review [slides] | ||||||

R9 | M 11/22 | Recitation 9 [recitation 9] | ||||||

T 11/23 | CP4 out | |||||||

23 | W 12/1 | Quiz 2 | ||||||

24 | F 12/3 | In-class student presentations | ||||||

25 | W 12/8 | In-class student presentations |

Assignment | Covers (general) | Release Date | Due Date |
---|---|---|---|

HW1 | Unit 1 | T 9/14 | M 9/20 |

HW2 | Unit 1 | M 9/20 | M 9/27 |

CP1 | Unit 1 | M 9/27 | M 10/4 |

HW3 | Unit 2 | M 10/4 | T 10/12 |

CP2 | Unit 2 | T 10/12 | W 10/20 |

HW4 | Unit 3 | W 10/20 | M 11/1 |

Project Proposal | M 11/8 | ||

CP3 | Unit 3 | T 11/2 | M 11/15 |

HW5 | Unit 4 | M 11/15 | T 11/23 |

CP4 | Unit 4 | T 11/23 | W 12/8 |

Project Presentations | F 12/3 | ||

Project Presentations | W 12/8 |