SlideShare une entreprise Scribd logo
1  sur  23
Télécharger pour lire hors ligne
micromobility
when
attacks
US National Household Travel Survey 2017
VEHICLE TRIPS 220,430,000,000
VEHICLE MILES OF TRAVEL (VMT) 2,105,882,000,000 mi
PERSON TRIPS 371,152,000,000
PERSON MILES OF TRAVEL (PMT) 3,970,287,000,000 mi
2.1
Trillion miles
3.9
Trillion miles
Car Trip Distance Distribution (US) (n=748,918)
OneWayTrips(%)
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
Trip Distance (miles)
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79
One-way Trips (%)
Lognormal approximation
𝝻 Location parameter 1.65
𝞂 scale parameter 0.95
Arithmetic Mean 8.2
Median 5.2
Mode 2.1
Arithmetic Std. Dev. 7.8
Geometric Mean 5.21
Geometric Std. Dev 2.59
2/3 Min 2.01
2/3 Max 13.46
95% Min 0.78
95% Max 34.81
US Car
Miles/trip
(MEASURED)
TripsProbability
0
5
10
15
20
0 1.5 3 4.5 6 7.5 9 10.5 12 13.5 15 16.5 18 19.5
Trip Distance Probability
Log-normal Approximation
NYC Taxi
New York CITI Bike n = 42.7 million
Miles/trip
TripsProbability
Probability Density Functions
0
0.03
0.06
0.09
0.12
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Log-normal Approximations
0
0.03
0.06
0.09
0.12
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Miles/trip
(MEASURED, EUCLIDEAN)
New York CITI Bike n = 42.7 million
(MEASURED, EUCLIDEAN)
TripsProbability
0
0.03
0.06
0.09
0.12
Miles
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
0
0.03
0.06
0.09
0.12
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
TripsProbability0
0.024
0.048
0.072
0.096
0.12
-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3
0
0.024
0.048
0.072
0.096
0.12
-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3
ln(Distance)
Boston Hubway n = 3.3 million
Miles/trip
TripsProbability
Miles/trip
(MEASURED, EUCLIDEAN)
Probability Density Functions
0
0.04
0.08
0.12
0.16
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Log-normal Fit
0
0.025
0.05
0.075
0.1
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Chicago Divvy n = 11.5 million
Miles/trip
TripsProbability
Miles/trip
(MEASURED, EUCLIDEAN)
Probability Density Functions
0
0.025
0.05
0.075
0.1
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Log-normal Fit
0
0.025
0.05
0.075
0.1
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
DC Capital Bike Share n = 5.7 million
Miles/trip
TripsProbability
Miles/trip
(MEASURED, EUCLIDEAN)
Probability Density Functions
0
0.023
0.045
0.068
0.09
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Log-normal Approximations
0
0.023
0.045
0.068
0.09
0.1
0.6
1.1
1.6
2.1
2.6
3.1
3.6
4.1
4.6
5.1
5.6
6.1
6.6
7.1
7.6
Zürich E-Bike Sharing
Miles/trip
TripsProbability
Miles/trip
(MEASURED, EUCLIDEAN)
0
0.018
0.035
0.053
0.07
0.1
0.5
0.9
1.3
1.7
2.1
2.5
2.9
3.3
3.7
4.1
4.5
4.9
5.3
5.7
6.1
6.5
6.9
7.3
7.7
8.1
8.5
8.9
9.3
9.7
PDF
0
0.018
0.035
0.053
0.07
0.1
0.5
0.9
1.3
1.7
2.1
2.5
2.9
3.3
3.7
4.1
4.5
4.9
5.3
5.7
6.1
6.5
6.9
7.3
7.7
8.1
8.5
8.9
9.3
9.7
Log-Normal Approximation Z Bikes
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
2017-07-NE
2017-06-NE
2017-05-NE
2017-04-NE
2017-03-NE
2017-02-NE
2017-01-NE
2016-12-NE
2016-11-NE
2016-10-NE
2016-09-N
2016-08-N
2016-07-NE
2016-06-N
2016-04-NE
2016-03-N
2016-02-N
2016-01-NE
2015-12-NE
2015-11-NE
2015-10-NE
2015-09-N
2015-08-N
2015-07-NE
2015-06-N
2015-05-N
2015-04-NE
2015-03-N
2015-02-N
2015-01-NE
2014-12-NE
2014-11-NE
2014-09-N
2014-08-N
2014-07-NE
2014-06-N
2014-05-N
2014-03-N
2014-02-N
2014-01-NE
2013-12-NE
2013-11-NE
2013-10-NE
2013-09-N
2013-08-N
2013-07-NE
<𝝻, 𝞂> parameters Seasonal variance Boston v. NYC
𝞂
𝝻
Boston
NYC
NYC
Boston
Swiss Modal Distributions
0%
8%
15%
23%
30%
0.01.0
3.04.0
6.07.0
9.010.0
12.013.0
15.016.0
18.019.0
21.022.0
24.025.0
27.028.0
30.031.0
33.034.0
36.037.0
39.040.0
42.043.0
45.046.0
48.049.0
51.052.0
54.055.0
57.058.0
60.061.0
63.064.0
66.067.0
69.070.0
72.073.0
75.076.0
78.079.0
81.082.0
84.085.0
87.088.0
90.091.0
93.094.0
96.097.0
99.0100.0
CH 1 CHWalking CH 1
0%
4%
8%
12%
16%
0.01.0
3.04.0
6.07.0
9.010.0
12.013.0
15.016.0
18.019.0
21.022.0
24.025.0
27.028.0
30.031.0
33.034.0
36.037.0
39.040.0
42.043.0
45.046.0
48.049.0
51.052.0
54.055.0
57.058.0
60.061.0
63.064.0
66.067.0
69.070.0
72.073.0
75.076.0
78.079.0
81.082.0
84.085.0
87.088.0
90.091.0
93.094.0
96.097.0
99.0100.0
2 CHCycling 2
0%
1%
3%
4%
5%
0.01.0
3.04.0
6.07.0
9.010.0
12.013.0
15.016.0
18.019.0
21.022.0
24.025.0
27.028.0
30.031.0
33.034.0
36.037.0
39.040.0
42.043.0
45.046.0
48.049.0
51.052.0
54.055.0
57.058.0
60.061.0
63.064.0
66.067.0
69.070.0
72.073.0
75.076.0
78.079.0
81.082.0
84.085.0
87.088.0
90.091.0
93.094.0
96.097.0
99.0100.0
3 CHSmall moped 3
0%
1%
2%
2%
3%
0.01.0
3.04.0
6.07.0
9.010.0
12.013.0
15.016.0
18.019.0
21.022.0
24.025.0
27.028.0
30.031.0
33.034.0
36.037.0
39.040.0
42.043.0
45.046.0
48.049.0
51.052.0
54.055.0
57.058.0
60.061.0
63.064.0
66.067.0
69.070.0
72.073.0
75.076.0
78.079.0
81.082.0
84.085.0
87.088.0
90.091.0
93.094.0
96.097.0
99.0100.0
5 CHMotorcycle driver 5
0%
1%
2%
2%
3%
0.01.0
3.04.0
6.07.0
9.010.0
12.013.0
15.016.0
18.019.0
21.022.0
24.025.0
27.028.0
30.031.0
33.034.0
36.037.0
39.040.0
42.043.0
45.046.0
48.049.0
51.052.0
54.055.0
57.058.0
60.061.0
63.064.0
66.067.0
69.070.0
72.073.0
75.076.0
78.079.0
81.082.0
84.085.0
87.088.0
90.091.0
93.094.0
96.097.0
99.0100.0
7 CHCar driver 7
0%
1%
2%
2%
3%
0.01.0
3.04.0
6.07.0
9.010.0
12.013.0
15.016.0
18.019.0
21.022.0
24.025.0
27.028.0
30.031.0
33.034.0
36.037.0
39.040.0
42.043.0
45.046.0
48.049.0
51.052.0
54.055.0
57.058.0
60.061.0
63.064.0
66.067.0
69.070.0
72.073.0
75.076.0
78.079.0
81.082.0
84.085.0
87.088.0
90.091.0
93.094.0
96.097.0
99.0100.0
8 CHCar passenger 8
Addressable Market in Trip Distances for Various Modes
0.1mi.
1mi.
10mi.
100mi.
1000mi.
10000mi.
WalkUK
ZHWalking
ikes(NYCCitiBike)
-bike(NereZurich)
ZHschoolbus
ZHCycling
ZHTram/metro
NYCTaxi
CHWalking
CHTaxi
PersonalBicycle
etransport(Uber?)
BusinLondon
ZHCardriver
ZHCarpassenger
rlocalbusEngland
Taxi/minicabUK
USCar
CHMicromobility
ZHTrain
ublictransportUK
vanpassengerUK
CardriverUK
MotorcycleUK
ndonUnderground
CHCycling
ike(max.25km/h)
CHTram/metro
CHSmallmoped
CHOther
CHschoolbus
SurfaceRailUK
ar/Funicular/skilift
otorcycle(<50cc)
late(max45km/h)
Motorcycledriver
CHCardriver
torcyclepassenger
CHBus(Postauto)
CHCarpassenger
CHBoat
CHTruck
Bus(longdistance)
CHTrain
Non-localbusUK
assengerAirTravel
CHAircraft
2/3 Min
2/3 Max
Median
95% Min
95% Max
MICROMOBILITY
Car Trip Distance Distribution (US) (n=748,918)
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79
Lognormal approximation
US Car
US Car Trips <31, >30mi. Vehicle Trips Distribution (US) (n=748,918)
OneWayTrips(count)
0
10,000,000,000
20,000,000,000
30,000,000,000
40,000,000,000
50,000,000,000
60,000,000,000
70,000,000,000
80,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
US Car VMT VMT Distribution (US) (n=748,918)
VehicleMilesTraveled
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
US Car VMT Buckets VMT BUCKETS (US) (n=748,918)
VehicleMilesTraveled
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
800,000,000,000
900,000,000,000
1,000,000,000,000
1,100,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
1,067,622,603,274
612,861,811,859
425,397,584,867
VMT Distribution (US) (n=748,918)
VehicleMilesTraveled
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
US Car VMT Buckets VMT BUCKETS (US) (n=748,918)
VehicleMilesTraveled
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
800,000,000,000
900,000,000,000
1,000,000,000,000
1,100,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
1,067,622,603,274
1,038,259,396,726
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
1.1
Trillion miles
1.0
Trillion miles
How Much Does a Mile Cost?
PRICING VMT IN NYC
$0.00
$3.00
$6.00
$9.00
$12.00
$15.00
$18.00
TRIP DISTANCE
0.5 1 1.5 2 3
$0.50
IRS DEDUCTION
Taxi
Citibike
MICROMOBILIT Y
$0.00
$0.75
$1.50
$2.25
$3.00
1 2 3 4 5 6 7 8 9 10
US Revenue Buckets Dollar BUCKETS (US) (n=748,918)
PersonDollar-Miles
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
800,000,000,000
900,000,000,000
1,000,000,000,000
1,100,000,000,000
1,200,000,000,000
1,300,000,000,000
1,400,000,000,000
1,500,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
$1,111,051,834,588
$1,408,549,860,197
0
100,000,000,000
200,000,000,000
300,000,000,000
400,000,000,000
500,000,000,000
600,000,000,000
700,000,000,000
800,000,000,000
Trip Distance (miles)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
$1.1
Trillion
$1.4
Trillion
SMALL DISTANCES IN SMALL
VEHICLES
ELECTRIC EARLY,
AUTONOMOUS LATE
AUTONOMOUS EARLY,
ELECTRIC LATE
2026: 40 million units/yr
Micromobility market will grow fastest
LARGE DISTANCES IN
LARGE VEHICLES
The Unbundling is Coming

Contenu connexe

Similaire à When Micromobility Attacks

Webcast 3q17 ing final
Webcast 3q17 ing finalWebcast 3q17 ing final
Webcast 3q17 ing finalLocaliza
 
Local road rehabilitation program charts (1)
Local road rehabilitation program charts (1)Local road rehabilitation program charts (1)
Local road rehabilitation program charts (1)Jeffrey C. Hicks
 
1Q16 Conference Call
1Q16 Conference Call1Q16 Conference Call
1Q16 Conference CallLocaliza
 
Webcast 1 q16 ing(1)
Webcast 1 q16 ing(1)Webcast 1 q16 ing(1)
Webcast 1 q16 ing(1)Localiza
 
3Q14 Results Presentation
3Q14 Results Presentation3Q14 Results Presentation
3Q14 Results PresentationTegmaRI
 
Scott-Macon Aerospace, Defense and Government Industry Update
Scott-Macon Aerospace, Defense and Government Industry UpdateScott-Macon Aerospace, Defense and Government Industry Update
Scott-Macon Aerospace, Defense and Government Industry UpdateMichael Papazis
 
Webcast 2Q17
Webcast 2Q17Webcast 2Q17
Webcast 2Q17Localiza
 
3Q16 Webcast
3Q16 Webcast3Q16 Webcast
3Q16 WebcastLocaliza
 
Webcast 3Q16
Webcast 3Q16Webcast 3Q16
Webcast 3Q16Localiza
 
Webcast - 2Q18
Webcast - 2Q18Webcast - 2Q18
Webcast - 2Q18Localiza
 
Scott-Macon Aerospace, Defense and Government Services (May 2017)
Scott-Macon Aerospace, Defense and Government Services (May 2017)Scott-Macon Aerospace, Defense and Government Services (May 2017)
Scott-Macon Aerospace, Defense and Government Services (May 2017)Michael Papazis
 
AssumptionsAssumptions that can be changed for the caseAs the ins.docx
AssumptionsAssumptions that can be changed for the caseAs the ins.docxAssumptionsAssumptions that can be changed for the caseAs the ins.docx
AssumptionsAssumptions that can be changed for the caseAs the ins.docxrock73
 

Similaire à When Micromobility Attacks (20)

MRM APRIL 2023.pptx
MRM APRIL 2023.pptxMRM APRIL 2023.pptx
MRM APRIL 2023.pptx
 
Webcast 3q17 ing final
Webcast 3q17 ing finalWebcast 3q17 ing final
Webcast 3q17 ing final
 
Call 2 t13_eng
Call 2 t13_engCall 2 t13_eng
Call 2 t13_eng
 
Local road rehabilitation program charts (1)
Local road rehabilitation program charts (1)Local road rehabilitation program charts (1)
Local road rehabilitation program charts (1)
 
Project Selection for Highway Widening: A Systemic Approach
Project Selection for Highway Widening: A Systemic ApproachProject Selection for Highway Widening: A Systemic Approach
Project Selection for Highway Widening: A Systemic Approach
 
1Q16 Conference Call
1Q16 Conference Call1Q16 Conference Call
1Q16 Conference Call
 
Webcast 1 q16 ing(1)
Webcast 1 q16 ing(1)Webcast 1 q16 ing(1)
Webcast 1 q16 ing(1)
 
3Q14 Results Presentation
3Q14 Results Presentation3Q14 Results Presentation
3Q14 Results Presentation
 
Scott-Macon Aerospace, Defense and Government Industry Update
Scott-Macon Aerospace, Defense and Government Industry UpdateScott-Macon Aerospace, Defense and Government Industry Update
Scott-Macon Aerospace, Defense and Government Industry Update
 
P33_Total_Nal.pdf
P33_Total_Nal.pdfP33_Total_Nal.pdf
P33_Total_Nal.pdf
 
Revenues
RevenuesRevenues
Revenues
 
P33_Nal_Comercial.pdf
P33_Nal_Comercial.pdfP33_Nal_Comercial.pdf
P33_Nal_Comercial.pdf
 
Webcast 2Q17
Webcast 2Q17Webcast 2Q17
Webcast 2Q17
 
3Q16 Webcast
3Q16 Webcast3Q16 Webcast
3Q16 Webcast
 
Webcast 3Q16
Webcast 3Q16Webcast 3Q16
Webcast 3Q16
 
Webcast - 2Q18
Webcast - 2Q18Webcast - 2Q18
Webcast - 2Q18
 
Margins
MarginsMargins
Margins
 
Scott-Macon Aerospace, Defense and Government Services (May 2017)
Scott-Macon Aerospace, Defense and Government Services (May 2017)Scott-Macon Aerospace, Defense and Government Services (May 2017)
Scott-Macon Aerospace, Defense and Government Services (May 2017)
 
AssumptionsAssumptions that can be changed for the caseAs the ins.docx
AssumptionsAssumptions that can be changed for the caseAs the ins.docxAssumptionsAssumptions that can be changed for the caseAs the ins.docx
AssumptionsAssumptions that can be changed for the caseAs the ins.docx
 
Vendas por Marca
Vendas por MarcaVendas por Marca
Vendas por Marca
 

Dernier

Clean Mobility Options Program by Sarah Huang
Clean Mobility Options Program by Sarah HuangClean Mobility Options Program by Sarah Huang
Clean Mobility Options Program by Sarah HuangForth
 
Welcome to Auto Know University Orientation
Welcome to Auto Know University OrientationWelcome to Auto Know University Orientation
Welcome to Auto Know University Orientationxlr8sales
 
Increasing Community Impact with Meaningful Engagement by Brytanee Brown
Increasing Community Impact with Meaningful Engagement by Brytanee BrownIncreasing Community Impact with Meaningful Engagement by Brytanee Brown
Increasing Community Impact with Meaningful Engagement by Brytanee BrownForth
 
怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道
怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道
怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道7283h7lh
 
Human Resource Practices TATA MOTORS.pdf
Human Resource Practices TATA MOTORS.pdfHuman Resource Practices TATA MOTORS.pdf
Human Resource Practices TATA MOTORS.pdfAditiMishra247289
 
Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...
Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...
Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...IEABODI2SnVVnGimcEAI
 
ABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILES
ABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILESABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILES
ABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILESsriharshaganjam1
 
Bizwerx Innovation & Mobility Hub by Dr. Cassandra Little
Bizwerx Innovation & Mobility Hub by Dr. Cassandra LittleBizwerx Innovation & Mobility Hub by Dr. Cassandra Little
Bizwerx Innovation & Mobility Hub by Dr. Cassandra LittleForth
 

Dernier (8)

Clean Mobility Options Program by Sarah Huang
Clean Mobility Options Program by Sarah HuangClean Mobility Options Program by Sarah Huang
Clean Mobility Options Program by Sarah Huang
 
Welcome to Auto Know University Orientation
Welcome to Auto Know University OrientationWelcome to Auto Know University Orientation
Welcome to Auto Know University Orientation
 
Increasing Community Impact with Meaningful Engagement by Brytanee Brown
Increasing Community Impact with Meaningful Engagement by Brytanee BrownIncreasing Community Impact with Meaningful Engagement by Brytanee Brown
Increasing Community Impact with Meaningful Engagement by Brytanee Brown
 
怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道
怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道
怎么办理美国UCONN毕业证康涅狄格大学学位证书一手渠道
 
Human Resource Practices TATA MOTORS.pdf
Human Resource Practices TATA MOTORS.pdfHuman Resource Practices TATA MOTORS.pdf
Human Resource Practices TATA MOTORS.pdf
 
Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...
Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...
Infineon-Infineon_DC_EV_Charging_Trends_and_system_solutions-ApplicationPrese...
 
ABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILES
ABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILESABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILES
ABOUT REGENERATIVE BRAKING SYSTEM ON AUTOMOBILES
 
Bizwerx Innovation & Mobility Hub by Dr. Cassandra Little
Bizwerx Innovation & Mobility Hub by Dr. Cassandra LittleBizwerx Innovation & Mobility Hub by Dr. Cassandra Little
Bizwerx Innovation & Mobility Hub by Dr. Cassandra Little
 

When Micromobility Attacks

  • 2. US National Household Travel Survey 2017 VEHICLE TRIPS 220,430,000,000 VEHICLE MILES OF TRAVEL (VMT) 2,105,882,000,000 mi PERSON TRIPS 371,152,000,000 PERSON MILES OF TRAVEL (PMT) 3,970,287,000,000 mi 2.1 Trillion miles 3.9 Trillion miles
  • 3. Car Trip Distance Distribution (US) (n=748,918) OneWayTrips(%) 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% Trip Distance (miles) 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 One-way Trips (%) Lognormal approximation 𝝻 Location parameter 1.65 𝞂 scale parameter 0.95 Arithmetic Mean 8.2 Median 5.2 Mode 2.1 Arithmetic Std. Dev. 7.8 Geometric Mean 5.21 Geometric Std. Dev 2.59 2/3 Min 2.01 2/3 Max 13.46 95% Min 0.78 95% Max 34.81 US Car
  • 4. Miles/trip (MEASURED) TripsProbability 0 5 10 15 20 0 1.5 3 4.5 6 7.5 9 10.5 12 13.5 15 16.5 18 19.5 Trip Distance Probability Log-normal Approximation NYC Taxi
  • 5. New York CITI Bike n = 42.7 million Miles/trip TripsProbability Probability Density Functions 0 0.03 0.06 0.09 0.12 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 Log-normal Approximations 0 0.03 0.06 0.09 0.12 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 Miles/trip (MEASURED, EUCLIDEAN)
  • 6. New York CITI Bike n = 42.7 million (MEASURED, EUCLIDEAN) TripsProbability 0 0.03 0.06 0.09 0.12 Miles 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 0 0.03 0.06 0.09 0.12 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 TripsProbability0 0.024 0.048 0.072 0.096 0.12 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3 0 0.024 0.048 0.072 0.096 0.12 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3 ln(Distance)
  • 7. Boston Hubway n = 3.3 million Miles/trip TripsProbability Miles/trip (MEASURED, EUCLIDEAN) Probability Density Functions 0 0.04 0.08 0.12 0.16 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 Log-normal Fit 0 0.025 0.05 0.075 0.1 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6
  • 8. Chicago Divvy n = 11.5 million Miles/trip TripsProbability Miles/trip (MEASURED, EUCLIDEAN) Probability Density Functions 0 0.025 0.05 0.075 0.1 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 Log-normal Fit 0 0.025 0.05 0.075 0.1 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6
  • 9. DC Capital Bike Share n = 5.7 million Miles/trip TripsProbability Miles/trip (MEASURED, EUCLIDEAN) Probability Density Functions 0 0.023 0.045 0.068 0.09 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6 Log-normal Approximations 0 0.023 0.045 0.068 0.09 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.1 4.6 5.1 5.6 6.1 6.6 7.1 7.6
  • 10. Zürich E-Bike Sharing Miles/trip TripsProbability Miles/trip (MEASURED, EUCLIDEAN) 0 0.018 0.035 0.053 0.07 0.1 0.5 0.9 1.3 1.7 2.1 2.5 2.9 3.3 3.7 4.1 4.5 4.9 5.3 5.7 6.1 6.5 6.9 7.3 7.7 8.1 8.5 8.9 9.3 9.7 PDF 0 0.018 0.035 0.053 0.07 0.1 0.5 0.9 1.3 1.7 2.1 2.5 2.9 3.3 3.7 4.1 4.5 4.9 5.3 5.7 6.1 6.5 6.9 7.3 7.7 8.1 8.5 8.9 9.3 9.7 Log-Normal Approximation Z Bikes
  • 12.
  • 13. Swiss Modal Distributions 0% 8% 15% 23% 30% 0.01.0 3.04.0 6.07.0 9.010.0 12.013.0 15.016.0 18.019.0 21.022.0 24.025.0 27.028.0 30.031.0 33.034.0 36.037.0 39.040.0 42.043.0 45.046.0 48.049.0 51.052.0 54.055.0 57.058.0 60.061.0 63.064.0 66.067.0 69.070.0 72.073.0 75.076.0 78.079.0 81.082.0 84.085.0 87.088.0 90.091.0 93.094.0 96.097.0 99.0100.0 CH 1 CHWalking CH 1 0% 4% 8% 12% 16% 0.01.0 3.04.0 6.07.0 9.010.0 12.013.0 15.016.0 18.019.0 21.022.0 24.025.0 27.028.0 30.031.0 33.034.0 36.037.0 39.040.0 42.043.0 45.046.0 48.049.0 51.052.0 54.055.0 57.058.0 60.061.0 63.064.0 66.067.0 69.070.0 72.073.0 75.076.0 78.079.0 81.082.0 84.085.0 87.088.0 90.091.0 93.094.0 96.097.0 99.0100.0 2 CHCycling 2 0% 1% 3% 4% 5% 0.01.0 3.04.0 6.07.0 9.010.0 12.013.0 15.016.0 18.019.0 21.022.0 24.025.0 27.028.0 30.031.0 33.034.0 36.037.0 39.040.0 42.043.0 45.046.0 48.049.0 51.052.0 54.055.0 57.058.0 60.061.0 63.064.0 66.067.0 69.070.0 72.073.0 75.076.0 78.079.0 81.082.0 84.085.0 87.088.0 90.091.0 93.094.0 96.097.0 99.0100.0 3 CHSmall moped 3 0% 1% 2% 2% 3% 0.01.0 3.04.0 6.07.0 9.010.0 12.013.0 15.016.0 18.019.0 21.022.0 24.025.0 27.028.0 30.031.0 33.034.0 36.037.0 39.040.0 42.043.0 45.046.0 48.049.0 51.052.0 54.055.0 57.058.0 60.061.0 63.064.0 66.067.0 69.070.0 72.073.0 75.076.0 78.079.0 81.082.0 84.085.0 87.088.0 90.091.0 93.094.0 96.097.0 99.0100.0 5 CHMotorcycle driver 5 0% 1% 2% 2% 3% 0.01.0 3.04.0 6.07.0 9.010.0 12.013.0 15.016.0 18.019.0 21.022.0 24.025.0 27.028.0 30.031.0 33.034.0 36.037.0 39.040.0 42.043.0 45.046.0 48.049.0 51.052.0 54.055.0 57.058.0 60.061.0 63.064.0 66.067.0 69.070.0 72.073.0 75.076.0 78.079.0 81.082.0 84.085.0 87.088.0 90.091.0 93.094.0 96.097.0 99.0100.0 7 CHCar driver 7 0% 1% 2% 2% 3% 0.01.0 3.04.0 6.07.0 9.010.0 12.013.0 15.016.0 18.019.0 21.022.0 24.025.0 27.028.0 30.031.0 33.034.0 36.037.0 39.040.0 42.043.0 45.046.0 48.049.0 51.052.0 54.055.0 57.058.0 60.061.0 63.064.0 66.067.0 69.070.0 72.073.0 75.076.0 78.079.0 81.082.0 84.085.0 87.088.0 90.091.0 93.094.0 96.097.0 99.0100.0 8 CHCar passenger 8
  • 14.
  • 15. Addressable Market in Trip Distances for Various Modes 0.1mi. 1mi. 10mi. 100mi. 1000mi. 10000mi. WalkUK ZHWalking ikes(NYCCitiBike) -bike(NereZurich) ZHschoolbus ZHCycling ZHTram/metro NYCTaxi CHWalking CHTaxi PersonalBicycle etransport(Uber?) BusinLondon ZHCardriver ZHCarpassenger rlocalbusEngland Taxi/minicabUK USCar CHMicromobility ZHTrain ublictransportUK vanpassengerUK CardriverUK MotorcycleUK ndonUnderground CHCycling ike(max.25km/h) CHTram/metro CHSmallmoped CHOther CHschoolbus SurfaceRailUK ar/Funicular/skilift otorcycle(<50cc) late(max45km/h) Motorcycledriver CHCardriver torcyclepassenger CHBus(Postauto) CHCarpassenger CHBoat CHTruck Bus(longdistance) CHTrain Non-localbusUK assengerAirTravel CHAircraft 2/3 Min 2/3 Max Median 95% Min 95% Max MICROMOBILITY
  • 16. Car Trip Distance Distribution (US) (n=748,918) 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 Lognormal approximation US Car
  • 17. US Car Trips <31, >30mi. Vehicle Trips Distribution (US) (n=748,918) OneWayTrips(count) 0 10,000,000,000 20,000,000,000 30,000,000,000 40,000,000,000 50,000,000,000 60,000,000,000 70,000,000,000 80,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
  • 18. US Car VMT VMT Distribution (US) (n=748,918) VehicleMilesTraveled 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
  • 19. US Car VMT Buckets VMT BUCKETS (US) (n=748,918) VehicleMilesTraveled 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 800,000,000,000 900,000,000,000 1,000,000,000,000 1,100,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1,067,622,603,274 612,861,811,859 425,397,584,867 VMT Distribution (US) (n=748,918) VehicleMilesTraveled 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
  • 20. US Car VMT Buckets VMT BUCKETS (US) (n=748,918) VehicleMilesTraveled 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 800,000,000,000 900,000,000,000 1,000,000,000,000 1,100,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1,067,622,603,274 1,038,259,396,726 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1.1 Trillion miles 1.0 Trillion miles
  • 21. How Much Does a Mile Cost? PRICING VMT IN NYC $0.00 $3.00 $6.00 $9.00 $12.00 $15.00 $18.00 TRIP DISTANCE 0.5 1 1.5 2 3 $0.50 IRS DEDUCTION Taxi Citibike MICROMOBILIT Y $0.00 $0.75 $1.50 $2.25 $3.00 1 2 3 4 5 6 7 8 9 10
  • 22. US Revenue Buckets Dollar BUCKETS (US) (n=748,918) PersonDollar-Miles 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 800,000,000,000 900,000,000,000 1,000,000,000,000 1,100,000,000,000 1,200,000,000,000 1,300,000,000,000 1,400,000,000,000 1,500,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 $1,111,051,834,588 $1,408,549,860,197 0 100,000,000,000 200,000,000,000 300,000,000,000 400,000,000,000 500,000,000,000 600,000,000,000 700,000,000,000 800,000,000,000 Trip Distance (miles) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 $1.1 Trillion $1.4 Trillion
  • 23. SMALL DISTANCES IN SMALL VEHICLES ELECTRIC EARLY, AUTONOMOUS LATE AUTONOMOUS EARLY, ELECTRIC LATE 2026: 40 million units/yr Micromobility market will grow fastest LARGE DISTANCES IN LARGE VEHICLES The Unbundling is Coming