Electric vehicles (EVs) are becoming increasingly popular due to their eco-friendly nature and lower operating costs. However, predicting whether a customer will purchase an EV or not can be challenging as it depends on various factors such as demographics, personal preferences, and financial considerations.
In this project, we aim to develop a machine learning model that can accurately predict if a customer will buy an electric vehicle or not, based on a set of relevant features. By leveraging historical data and advanced algorithms, we can uncover patterns and relationships that influence a customer’s decision-making process.
The primary objective of this project is to build a reliable prediction model that can assist automotive companies, dealerships, and policymakers in understanding customer behavior and making informed decisions. This could include tailoring marketing strategies, optimizing inventory management, or designing targeted incentives to promote EV adoption.
Variable
Definition
1 BuyEV
purchase choice
2 PriceBudgetRatio
price of EV divided by respondent's highest budget
3 range
driving range of EV in scenario
4 HomeSlowChgWalkTime
walking time (minutes) from home to nearest slow charging
5 WorkSlowChagWalkTime
walking time (minutes) from work to nearest slow charging
6 FastChgTime
fast charging time (minutes) from empty to full charge
7 TownToFastChgDriveTime
driving time from any place in town to a fast-charging station (minutes)
8 HwyFastChgDistance
average distance (miles) between two fast charging stations on highway
9 gender
What is your gender?
10 race
Which race best describes you?
11 state
In what state or U.S. territory do you live?
12 license
Do you have a valid driver’s license?
13 edu
What is the highest level of education you have completed?
14 employment
Which of the following categories best describes your employment status?
15 hsincome
What was your household income last year?
16 hhsize
How many people currently live in your household?
17 housit
What is your housing situation?
18 residence
In what type of residence do you live?
19 move
Do you plan to move out from your current house within the next 3 years?
20 all_car
How many cars do you own?
21 new_car
If any, how many of your cars were new when they were purchased?
22 ev
How many electric cars do you own?
23 new_ev
If any, how many of your electric cars were new when they were purchased?
24 home_parking
What is your parking situation at home?
30 HomeChgAvai
Do you have an electrical outlet or electric vehicle (EV) charging facility at your usual home parking space?
31 work_parking
What is your usual parking situation at your place of work/school?
32 WorkChgAvai
Are electric vehicle (EV) charging facilities available at your place of work/school? i.e. Could you plug in an EV and charge it while parking at work/school?
33 buycar
Do you plan to buy a car in the next 3 years?
34 zipcode
your current home ZIP code
35 dmileage
Suppose you are replacing your car. How far do you typically drive the car to be replaced daily?
36 long_dist
How many long distance trips (i.e. trips more than 50 miles from your home) did you make by driving the car to be replaced last month?
37 gascost
Approximately how much money did you spend on gasoline for the car to be replaced last month?
38 age
In what year were you born? Age of respondent (years)=2019-answer
39 used_car_owner
whether respondent owns used car
40 used_ev_owner
whether respondent owns used EV
41 used
whether respondent answered used car scenario
42 NextCarBudget
Highest budget of next car chosen from the drop down menu in numerical form (eg. 10000)
43 PopDensity
Population density of home zipcode (based on 2010 Census)
44 orphan
whether the respondent is identified as a garage orphan who does not have an off-street home parking space or accessible electricity outlets for home charging
45 ev_owner
whether the respondent is an EV owner
46 priceshow
price of EV shown in each scenario
47 zip_median_home_value
Median home value of zipcode.
48 state_elec_price
Electricity price in each state (cent per kwh).
49 state_high_temp
State annual average high temperature over the entire state between 1991-2020.
50 state_precip
State annual average precipitation.
final calculate the score as output
convert output pdf :
link :
https://drive.google.com/file/d/1dmzq7b53MspDOkS9kJEWO7cYEnJ3TXgK/view?usp=sharing
