e-go: an innovative electric car sharing project in roma...
TRANSCRIPT
Dipartimento di Ingegneria
E-GO: An Innovative Electric Car
Sharing Project in Roma Tre
University
Stefano Carrese, Tommaso Giacchetti, Marialisa Nigro, Sergio Maria Patella
Department of Engineering, Roma Tre University
Junior ConsultingDipartimento di
Ingegneria
E–GO car sharing project timeline
04-2016
05-2016
06-2016
07-2016
09-2016
10-2016
11-2016
01-2017
04-2017
05-2017
Five years project – three stages:
first stage: service planning, infrastructural
implementation, financial feasibility and
demand analysis;
second stage: supervision of the starting
phase and effective users response;
third stage: opening of the service to a wider
area of Rome
2/21
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E- GO Car Sharing First Stage (1)
Designing phase:
LISELEC
1999, La Rochelle.
France
25 Peugeot 106s and 25
Citroen Saxos
Now named Yélomobile
Orix Car Share
1997, Japan
400 Nissan vehicles
Turned in hybrids and
gasoline vehicles
UCR Intellishare
1999, Riverside
campus, California
25Honda EV Plus
Ended in 2010
CAR 2 GO
2011, Amsterdam.
Netherlands
300 Electric Smart Fortwo
Working
Autolib’
2011, Paris. France
3000 Bolloré Bluecar and
1200 stations
Sizing problem…
Share’ngo
2015, Italy
1500 ZD (Florence,
Milan, Rome)
Working
1°
Genera
tio
n o
f E
V C
ar
Shari
ng
2°
Genera
tio
n o
f E
V C
ar
Shari
ng
3/21
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E- GO Car Sharing First Stage (2)
Designed as a “one way” station based car sharing:
Ex-ante survey - On-line RP and SP survey to 1,200
potential users: 960 respondents
RP section:
socio-economic characteristics and mobility habits;
behavioural attitudes (green attitude, out of pocket, sharing
attitude)
SP section:
evaluation 3 fee scenarios
20 Renault Twizy
2 seats, 60 Km
10 Renault Zoe
4 seats, 180 Km
eco-friendly and money-saving
attributes are those that most
influence EV Car Sharing choice
(Burkhardt e Millard-Ball, 2006)
27 recharge st. in Campus
100 in the city
4/21
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Mobility characteristics
Distances:
34% of the sample performs a short-distance home-university trip
(less or equal then 5 km); 28% a medium-distance trip (more than 5
km, but less or equal than 15 km); 16% a long-distance trip (more than
15 km but less or equal than 25 km). The remaining ones perform a
trip longer than 25 km;
Modal shift:
off-site students mostly choose the public transport alternative for
their trips (67%);
for on-site students there is a comparable choice between the
automobile and the public transport;
Other users: higher values of private vehicle (70%)
Other:
92% of respondents has a driving license;
public transport subscription is not diffused: about 52% of the sample
declared to not have any kind of subscription.5/21
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Adoption of the new car sharing system
For home-university trips:
80% (students and off-site students); 83% (others);
71% CS integrated with public transport
The adoption decreases with the increase of the distances
to be travelled (85% d < 5km; 55% d > 50 km);
Frequency: 3 days/week
For other trip purposes:
86%; 92% (off-site students);
No difference between male/female;
Reduction of the adoption of CS with the increase of
the household income:
Out of pocket: less than 50 € per month for the 80% of the
students.
6/21
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Green attitude How much users are environmental conscious and open
minded about new sustainable transport modes?
GA is not linked to the user’s gender, the economic conditions and to
the level of education;
about 70% of respondents over 45 years old declared to be aware of
environment;
public transport users show higher GA values.
degree of care about
energy and
environmental
sustainability issues
1 2 3 4 5
7/21
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Sharing attitude Cohousing and car sharing – car pooling use:
SA decreases with the increase of age and income;
Males are slightly more opened to share goods and services than
females from our sample (respectively 60% full sharing attitude and
47% full sharing attitude);
Green Attitude and SA are positively correlated.
8/21
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SP survey
Fee scenarios:
After the proposed fees, respondents are invited to express
their willingness to subscribe the proposed service:
about the 24% of the respondents declared to be interested in using the
proposed service for home-University trips;
the 28% for not home-work trips closed to University
Easy morning Easy evening FlexibleWorking
day
8:00-20:00
[0,21 €/min]9:00-19:00 [0,25 €/min]
9:00-19:30
[0,23 €/min]
Evening -
nigh time
20:00-8:00
flat [18 €]
19:00-9:00
flat [15 €]
19:30-9:00
flat [16 €]
Special
time
windows
- -
Lunch break 12:00-
14:00
flat [6€]
Weekend From Saturday 11:00-to
Monday 8:00
flat [25 €]
From Saturday 11:00-to
Monday 9:00
flat [23 €]
From Friday 19:30 to
Monday 9:00
flat [30 €]
The most
chosen one. It
is a good offer
during the
“working” day,
thus it is more
oriented to
catch demand
for potential
trips inside the
University
9/21
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E- GO Car Sharing First Stage: moving to
free floating
Pilot test: from mid-September 2016 to the end of
November 2016:
100 users resulted available from the ex-ante survey involved
in using the service for free;
Critical issues:
Recharge stations not available;
Security and policy issues: if the recharge station is kept by
an E-GO vehicle: damages by owners of other electric vehicles;
Safety issues.
Second survey - On-line RP and SP survey
Demand modelling (Zhou et al., 2009, Katzev, 2003, Lane,
2005, Efthymiou et al. 2016, De Luca et al. 2016)
10/21
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Stated modal shift with the free-floating
E-GO
Home-work trips:
Other activities:
11/21
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Deriving demand models for Home-Work
trips
Rho - square 0.413
Adjusted rho - square 0.383
Init log likelihood -66.909
Final log likelihood -33.271
Calibration Results:
Systematic Utilities:
MNL
CAR CS PTVCAR= ASCcar*one + βt t_car + βcost* cost_car
VCS= ASCCS*one + βt* t_CS + βcost* cost_CS
VPT= ASCPT*one + βt* t_PT + βcost* cost_PT
12/21
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Deriving demand models for other
activities (1)
Systematic Utility :
Calibration Results
Rho - square 0.503
Adjusted rho - square 0.449
Init log likelihood -92.673
Final log likelihood -46.079
CS PTCAR
NL
VCAR= ASCcar*one + βcost* cost_car
VPT= ASCPT*one + βcost* cost_PT
VCS= ASCCS*one + βcost* cost_CS + βt_dest t_dest
Private
Public
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Deriving demand models for other
activities (2)
Rho - square 0.440
Adjusted rho - square 0.376
Init log likelihood -94.060
Final log likelihood -52.693
Calibration Results:
Systematic Utility:
CNL
CAR CS PT
VCAR= ASCcar*one + βcost* cost_car
VCS= ASCCS*one + βcost* cost_CS
Private
Public
Private_S1_CAR
Private_S3_CS
Public_S2_PT
Public_S3_CS
VPT= ASCPT*one + βcost* cost_PT + βfreq * freq
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Sensitivity analysis: E-GO fee
e.g. 30 minutes Trip
Starting Cost 10% 20% 30%
8.10€Increase 8.90€ 9.70€ 10.50€
Decrease 7.30€ 6.50€ 5.70€
Home-Work Trips Other activities Trips
15/21
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E-GO and change the mode for the main
trip
Home-work trips with auto mode: 33% shall use
public transport (modifying modal shift), if E-GO is
available for other activities trips.
16/21
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Second stage: from January 2017 the service is:
Free floating (operative area) and counts for 400 members.
E-Go Car Sharing Now
17/21
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E-Go Car Sharing available infrastructures
Engineering recharge park
Reserved slot Recharge point
1.Book the car 2.Report damages
3.Start the rental 4.Leave the car
18/21
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E-Go Car Sharing governance & management
Roma Tre e-go management team
Fleet Management (1 resource)
Refloating team (2 resources)
Reserch team (Prof. Stefano Carrese)
Marketing team (20 ambassador)
Registration office
Innovation and new business team
Recharge points maintenance
Call center service
Website & social communication
Fleet insurance & leasing cost
Fleet Management support
19/21
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Marketing
20/21
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Electric Car Sharing…..and more
21/21
http://greenmetric.ui.ac.id/overall-ranking-2016/