# CIVENGR 577: Traffic Flow Theory | UW–Madison

[View on UW Courses](https://uwcourses.com/courses/CIVENGR_577)

## Dataset

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

### repository

twangodev/uwcourses

### schema version

6

### importer version

7

### projection id

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### observed at

2026-09-07T15:55:43.033547+00:00

### built at

2026-09-10T19:50:42.743001+00:00

### courses

8951

### current instructors

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### limited

false

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### term

1272

### departments

| subject   | count |
| --------- | ----- |
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| CHEM      | 101   |
| CHICLA    | 52    |
| CIVENGR   | 133   |
| CLASSICS  | 47    |
| CNP       | 10    |
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| FAMMED    | 22    |
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| FOLKLORE  | 40    |
| FOODSCI   | 43    |
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| GNS       | 38    |
| GREEK     | 27    |
| HDFS      | 41    |
| HEBR-BIB  | 13    |
| HEBR-MOD  | 10    |
| HISTORY   | 233   |
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| INTEGART  | 7     |
| INTEGSCI  | 22    |
| INTER-AG  | 18    |
| INTER-HE  | 11    |
| INTER-LS  | 22    |
| INTEREGR  | 16    |
| INTLBUS   | 21    |
| INTLST    | 50    |
| ISYE      | 83    |
| ITALIAN   | 53    |
| JEWISH    | 56    |
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| KINES     | 128   |
| LACIS     | 26    |
| LANDARC   | 61    |
| LATIN     | 24    |
| LAW       | 120   |
| LEGALST   | 48    |
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| MARKETNG  | 62    |
| MATH      | 153   |
| MDGENET   | 8     |
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| MEDHIST   | 43    |
| MEDICINE  | 60    |
| MEDIEVAL  | 32    |
| MEDPHYS   | 39    |
| MEDSC-M   | 29    |
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| MHR       | 68    |
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| MILSCI    | 16    |
| MM\&I     | 22    |
| MOLBIOL   | 6     |
| MS\&E     | 59    |
| MUSIC     | 165   |
| MUSPERF   | 126   |
| NAVSCI    | 20    |
| NE        | 44    |
| NEURODPT  | 11    |
| NEUROL    | 7     |
| NEURSURG  | 4     |
| NTP       | 11    |
| NURSING   | 111   |
| NUTRSCI   | 65    |
| OBS\&GYN  | 18    |
| OCCTHER   | 39    |
| ONCOLOGY  | 14    |
| OPHTHALM  | 5     |
| OTM       | 43    |
| PATH      | 34    |
| PATH-BIO  | 29    |
| PEDIAT    | 26    |
| PHARMACY  | 31    |
| PHILOS    | 77    |
| PHMCOL-M  | 11    |
| PHMPRAC   | 45    |
| PHMSCI    | 60    |
| PHYASST   | 37    |
| PHYSICS   | 88    |
| PHYSIOL   | 3     |
| PHYTHER   | 37    |
| PLANTSCI  | 52    |
| PLPATH    | 35    |
| POLISCI   | 192   |
| POPHLTH   | 58    |
| PORTUG    | 33    |
| PSYCH     | 101   |
| PSYCHIAT  | 22    |
| PUBAFFR   | 54    |
| PUBLHLTH  | 23    |
| RADIOL    | 11    |
| REALEST   | 41    |
| RELIGST   | 90    |
| RHABMED   | 9     |
| RMI       | 24    |
| RP\&SE    | 102   |
| S\&APHM   | 17    |
| SCANDST   | 73    |
| SLAVIC    | 89    |
| SOC       | 149   |
| SOCWORK   | 87    |
| SOILSCI   | 46    |
| SPANISH   | 83    |
| SRMED     | 21    |
| STAT      | 94    |
| STDYABRD  | 52    |
| STS       | 8     |
| SURGERY   | 25    |
| SURGSCI   | 33    |
| THEATRE   | 91    |
| URBRPL    | 60    |
| UROLOGY   | 5     |
| ZOOLOGY   | 89    |

## course

### run id

20260907T155543-ce3781c4

### semester

1272

### observed at

2026-09-07 15:55:43.033547+00:00

### record version id

343cfc840fb63193d90f623f4d1c85f9351da14686fddebf203a0671db8c4803

### course id

CIVENGR 577

### course uid

course\_db79f7cc3cad92b69c802ef0

### catalog version id

af54fecd45f5d23f68edec0baf5c94aeaba6dc8439757b0680deaab17b88aa1b

### course number

577

### subjects

* CIVENGR

### title

TRAFFIC FLOW THEORY

### description

Comprehensive overview of vehicular traffic flow theory and its use in evaluating congestion and determining control strategies.  Starting from the basic concepts defining traffic streams, existing theories are presented at different scales, including car-following (microsimulation) models, lane-changing models, cellular automata models, the kinematic wave model, and macroscopic/network fundamental diagram.  Techniques for empirical analysis. Connected and automated vehicles.

### requirements text

Graduate/professional standing

### credit offering ids

None recorded.

### llm job id

enrich-8b774950c2b6adfdc46d1b82

### llm output id

4c06747dd4f572d3bc4c30965aad4ae19b1e53bb6b32a2248c4c6a94ec6f38f0

### llm model

nvidia/Qwen3.6-35B-A3B-NVFP4

### llm model revision

1355db6a052410cfd62085d94b58866fd0f2c3c5

### llm task version

14

### llm search status

valid

### llm summary

CIVENGR 577 provides a comprehensive overview of vehicular traffic flow theory, covering models from microsimulation to macroscopic networks, and their application in congestion evaluation and control.

### llm topics

* Traffic flow models: car-following, lane-changing, cellular automata, kinematic wave, and macroscopic fundamental diagrams
* Connected and automated vehicles

### llm skills

* Evaluate traffic congestion and determine control strategies
* Apply techniques for empirical traffic analysis

### llm assumed background

None recorded.

### llm search phrases

* traffic flow theory
* car-following models
* kinematic wave model
* macroscopic fundamental diagram
* traffic congestion control
* connected automated vehicles

### llm requirements status

valid

### llm student summary status

valid

### llm experience status

insufficient\_evidence

### catalog variants

None recorded.

### student summary

#### context hash

8154897afefec47b52d816e97ab162a21d7f498c65351a39b5b4de5357d782bd

#### course id

CIVENGR 577

#### current instructors

None recorded.

#### difficulty workload

None recorded.

#### errors

None recorded.

#### historical context

None recorded.

#### message

No course-specific reviews available

#### offered

false

#### profile hash

5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02

#### quick take

None recorded.

#### student experience

None recorded.

#### task hash

74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68

#### teaching history

None recorded.

#### term id

1272

#### term name

2026 Fall

#### version

2

### requirements

#### nodes

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```

#### notes

None recorded.

#### root

n0

#### status

parsed

### instructors

None recorded.

### offerings

None recorded.

### sections

None recorded.

### grade instructors

None recorded.

### grades

None recorded.

### statistics

#### graded

0

#### counts

* 0
* 0
* 0
* 0
* 0
* 0
* 0

### grade conflicts

None recorded.

### evidence

#### history

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_db79f7cc3cad92b69c802ef0-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_db79f7cc3cad92b69c802ef0-0.json)

#### traces

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_db79f7cc3cad92b69c802ef0-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_db79f7cc3cad92b69c802ef0-0.json)

#### results

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_db79f7cc3cad92b69c802ef0-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_db79f7cc3cad92b69c802ef0-0.json)

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

## instructor Trends

None recorded.

## following

None recorded.
