YuLuLeah's repositories
UE-problem-for-PHEV-and-ICEV
Network user equilibrium problems for the plug-in electric vehicles and gasoline vehicles subject to road length constraints
ABM-Trafic-grid-commute
The Commute behavior, Traffic Congestion, and Parking model simulates traffic moving in a simplified city grid with several perpendicular one-way streets that forms an intersection. It allows you to control global variables, such as the parking ratio and the number of people, and explore traffic dynamics, particularly traffic congestion measured by average speed and average waiting time for parking, which add to the total utility. This model gives the cars destinations (house or work) to investigate the traffic flow of commuting people. The agents in this model use goal-based and adaptive cognition. ## HOW IT WORKS Each time step, the cars face the next destination they are trying to get to (work or house) and attempt to move forward at their current speed and keep a safety speed. If their current distance to the car directly in front of them is less than their safety distance, they decelerate. If the distance is larger than safety distance, they accelerate. If there is a red light or a stopped car in front of them, they stop. In each cycle, each car will be assigned one destination. Traffic lights at the intersection will automatically change at the beginning of each cycle. Once the car parked, it will take 20 seconds to get into the front door of a company and then the car dispears from the map, at the same time a parking spot is empty for the next one. If a car driving through its destination, however the parking spot is not empty, it will keep driving around until spot opens up.
data-driven-optimization-reinforcement-learning-
inde 599 2020 spring
R-SHINY-for-bicycle-count-program
Your team is required to develop a Shiny application for data collection and presentation in R. The interface that you design will include views and controls that can be used to enter and view data, as well as summarize/visualize the data that has been collected.
UW-2020-CSE546
UW 2020 CSE546 HW0-4 Machine Learning