Group work in MSc Engineering Management, University of Bristol. This report proposes optimized solutions to the challenges of commuter transport in cities in developing countries to promote a low-carbon transformation.

2. 上 兵 伐 谋
其 次 伐 交
其 次 伐 兵
其 下 攻 城
孙 武
《 孙 子 兵 法 》

3. Global Challenge Project Group 06:
Minrui Sun, Peihang An, Pengfei Du, Sen Shang, Yuetai Hou
Executive Summary
This report has designed a solution to the current problems of urban congestion and high carbon
emissions. We call it the Street-Smart project. The city we choose is Harbin, China, a city in north-
eastern China where congestion is a major problem and is often complained about by citizens. To
pinpoint the problem, we sent out a questionnaire to the citizens of Harbin about their commuting
experience, and from the results, we identified the problem and proposed a solution.
Figure 1 City of Harbin. Source: https://steemit.com
The project was designed using tools such as the Questionnaire Method (a quantitative model of
public travel costs), the VDI 2221 Design Model, the Morphological Chart, the IPCC 'bottom-up'
method, the results of the questionnaire, and the above tools. We have designed a commuting software
that allows people to choose the most suitable option for their trip, after confirming their travel time,
departure, and arrival points. The app also offers shared electric scooters and shared six-seater electric
vehicles for commuting. The app will be connected to the government-run public transport system
(buses, metro, etc.) and people who use the low-carbon travel options recommended by the app will
accumulate "green travel points" which can be used to offset the cost of public transport trips, which
in part encourages people to use green and low-carbon travel options and reduces carbon emissions.
This encourages the use of green and low-carbon modes of transport and reduces carbon emissions.
PESTEL, Stakeholder Analysis, SWOT, BMC were used in the development of the project strategy
to analyse the opportunities and challenges of the project from a macro and micro perspective and to
design the operation and profitability of the project. Since the Chinese government has been
promoting the concept of environmental protection in recent years, we can start by seeking
government subsidies to solve the problem of financial constraint in the early stage, and when the
project user scale is expanded, more profitability will become possible.
The project risk analysis process uses the FMECA model to identify the most pressing issues that
need to be addressed, all of which are related to passenger safety. Nothing should take precedence
over life, so several practical risk mitigation measures will greatly improve the safety of the project.

4. City Background:
We choose the city of Harbin to represent Urbanville. (According to the International Monetary
Fund’s World Economic Outlook Database, October 2018, Harbin is a qualified developing city)
Harbin lies in the Northeast China, it serves as a key political, economic, cultural and communications
hub in Northeast China. Harbin has become one of the largest cities in Northeast China nowadays, as
well as an important industrial base. Harbin has a total area of 53100 square kilometres, a municipal
area of 10198 square kilometres and a built-up area of 768 square kilometres. By the end of 2019, the
total number of registered residence population was over 9 million which ranks No.4 in all the
provincial capitals, and the total population of urban area was over 4 million. The city's road mileage
was 25762.5 kilometres, including 877.2 kilometres of highway. The number of civil vehicles was
1.979 million. Among them, the number of private cars reaches 1.787 million, and the number of
individual minibuses was 1.627 million. (www.harbin.gov.cn, n.d.2020)
In 2019, there were 306 bus lines. The total length
of public transport lines reached 6984 km. 7402
buses are in operation, including 1937 new energy
buses. The annual bus passenger volume was 1.06
billion, down 16.5% over the previous year. There
are 17980 taxis, including 2423 dual fuel taxis and
556 million passengers. The length of the metro
line is 30.3 km and the passenger volume is
104million person times. The number of motor
vehicle drivers is 1.825 million, still increasing.
(www.harbin.gov.cn, n.d.2020)
Through simple calculation, Harbin's daily
average travel volume has reached 2.9million
person times for buses and 285thousand person
times for underground. Due to the lack of
transportation facilities, commuter traffic has
become a major problem that citizens complain
about. Moreover, current traffic also poses
environmental challenges to Harbin such as
haze causing a huge cost on environmental
protection.
We thus write this proposal hoping to offer some advice to address the traffic problems as well as the
environmental issues. [For more details about Harbin, please refer to Appendix 1]
Figure 2 Satellite photographs of Harbin.
Source: https://map.baidu.com/
0
500000
1000000
1500000
2000000
2011 2012 2013 2014 2015 2016 2017 2018
Total amount of the vehicles
private vehicles
Figure 3 Trend of vehicles' amount in Harbin

5. Assessment of Potential technology for future commuting:
At the very beginning, we did some research on the technologies which have the potential to play an
important role in the future of commuting transport. [For more details, please refer to Appendix 2]
New energy vehicles have advantages of high
potential for energy saving and emission
mitigation (Ren,2018). Moreover, it can reduce
the cost of travel to a certain extent. However,
the proportion of electric vehicles in the total
vehicles is still low, mainly due to the high
failure rate of new energy vehicles (Liu,
Kokko,2013). What’s more, the new energy
vehicle industry needs mature commercial mode,
which refers to develop new businesses and
business models to provide the infrastructure, component, vehicle, and service necessary to enable a
good ecosystem of new energy vehicle (Cuma, Koroglu,2015). The price of new energy vehicles has
no advantage compared with traditional vehicles, and the price is even higher. Therefore, lowering
the price of new energy vehicles will arouse the interest of buyers (Mehndiratta,2011).
Smart control technology can be used to accurately infer and record the operation of a car through
computer data, which can assist in building more efficient and convenient systems for dealing with
transport violations (Yaqoob, et.al, 2019). Smart control applied to driving can provide more
reasonable driving judgment, better driving operation and improving the macro-efficiency of traffic
management. In the future, autonomous driving technology should be developed mainly at the level,
i.e.it still requires the driver's hands to stay on the steering wheel and the driver's manual
experience. The risk of the smart control is mainly in terms of high retrofitting costs and unstable
performance.
Figure 5 levels of driving automation. Source: https://www.dxc.technology/
The Internet of Things constitutes a world in which physical things, humans and other creatures,
and virtual information and environments collaborate with each other. Since many gadgets are
Figure 4 A typical new energy car.
Source: https://evhome-charge.com/

6. connected to the web, a large amount of information is created. (Gawade.et.at, 2017) Another
application direction of the Internet of Things is the health of transportation, that is, real-time
monitoring of each functional module or even each component through sensors, and viewing them
on mobile phones, PCs and other terminal devices, which can effectively improve the maintenance
efficiency of transportation and maintain High-performance operation improves transportation
efficiency. In view of the large amount of work required to install and update equipment, we believe
that Harbin should first focus on the Internet of Things technology to promote shared travel in the
future and try to find new types of data and develop new types of data collection hardware
equipment. And it is closely integrated with China's emerging 5G technology and cloud computing.
The application of data technology in the transport sector can be divided into macro and micro points.
At the macro level, the government can obtain comprehensive and large amount of traffic data
information to optimise future urban traffic planning and allocate traffic resources more rationally
from a higher perspective. At the micro level, individual users can make better travel plans by
accessing traffic data related to themselves. The risk lies in the high human cost associated with
collecting, maintaining, storing and analysing the data, and the need for excellent technical personnel
to process the data. The future development of data science in the field of transport applications has
a lot of room for growth. There are three main directions of development:
1) Combine with IOT technology
2) Develop data visualisation
3) Develop data analysis-based future preview technology, so as to predict unknown traffic
conditions (Liu,2018).
Based on the data science and big data, the government will build the city into a digital city and
with the addition of the IoT, the city can be further developed into a smart city (Zhang,2015).
Figure 6 WeChat Pay. Source: https://www.scmp.com/
The most successful application of the IOT combining Data Science in mainland China today is
mobile payments. China's mobile payment technology, represented by WeChat Pay, is an area leader
and is well spread in the public transport sector in major Chinese cities like Shanghai and Beijing.

7. Project Proposal:
This article is arranged as:
Figure 7 Catalogue Structure for the proposal
Project Proposal
Perface
Project
Life Cycle
Concept
Defination
Requirement
Specification
Development
Design Process
Environmental
Assessment
Strategic Analysis
Macro
PESTLE Analysis
Stakeholder
Analysis
Micro
Porter 5 Forces
Analysis
SWOT
Project Summary
Business Model
Canvas
Supportive Reasons
Risk
FMECA
Mitigation
Prospects

8. 1．Preface
To start with the project design, we used a questionnaire [For more details, please refer to Appendix
3] to get some key conclusions, then we used the general problem framing methodology [For more
details, please refer to Appendix 4] to analyse the key problems faced by Harbin and drew the
conclusion:
The vicious cycle of road traffic must be broken by the cooperation of new methods of transport and
upgrades to existing public transport for the questionnaire showed that most people in Harbin have
low satisfaction with the existing public transportation.
Figure 8 vicious cycle vs virtuous circle
Data and information are essential realise the goals and to reshape public concepts for the
inaccessibility of real-time transport information causes an imbalance in public transportation. We
should also seize the promotion chance among local college students who are the future commuters.
This project shall focus on new energy like electricity, posing new directions in car manufacturing,
environmental protection, producing side boosts in technologies and employment opportunities.
We have excluded the construction of Bus Rapid Transit system (Institute for Transportation and
Development Policy，2014) and underground transit, which have been implemented in other cities.
The former only by has an effect on the bus system itself, while the latter takes too long to plan and
construct, which cannot improve the existing traffic situation in time.
More
Private
Cars
More
CO2
More
Bus
Inputs
Worse
Congestion
Worse
Experience
Less
Private
Cars
Less
CO2
Balanced
Transport
Allocation
Less
Congestion
Better
Experience

9. 2． Life Cycle
2.1 Concept
The Street-Smart project is an integrated system of transportation modes, aiming to increase the
traffic efficiency through “Information Warfare” and promote a low-carbon commuting life style.
2.2 Definition
(1) The core concept of our project is to
build a platform that aggregate all traffic
information, allowing people to access
data-based travel advice and transport
services.
(2) Besides, we also proposed some
technical and service suggestions to
enhance the customer experience on
existing public transport.
(3) Finally, we shall design a new environmental-friendly way of commuting-sharing transportation
mode to improve efficiency, and this new transport service will also be included in the platform and
will be promoted as a core selling point.
2.2.1 Requirement Specification
From the results of the questionnaire, it can be seen that the existed public transportation is widely
complained by the citizens, the most common ones are the waiting conditions and punctuality. The
“Street Smart” project should focus on solving these problems.
Requirement Solution Description Predicted/ideal Outcome Importance
Avoid
congestion/
smoothness
Information Real-time position of the
vehicle; Congestion
assessment; Estimate
arrival time etc.
People can access the real-time
original data or visualized
information they want through our
App.
High
Recommendations
&comparison of travel
options
People can obtain the whole set of
indicators (estimated time cost,
transfer times, money cost, carbon
emission) of each travel plan as
well as the direct comparison of
them. People can also rank plans by
their own requirements (such as in
High
NEW
MODE
Figure 9 Street Smart Definition

10. ascending order of time cost)
Better
Punctuality
Prediction based on data To provide a more precise estimate
arrival time of each bus in advance.
High
Higher service
level
Services More convenient method
of ticket purchasing.
After people choose or combine
their own travel plan, they can
order an “e-ticket” covering all the
different transport service during
the plan and finish the online
payment on the same platform
without changing apps.
High
Better waiting
condition
Auxiliary technologies
for current public
transport service
To provide a mini traffic tool to
save the “home-station” time cost.
To enhance the physical conditions
of station.
Low
Better vehicle
facilities/ Better
Punctuality
To equip the public vehicle with
possible driving-supportive
technology and vehicle health
monitoring system.
High
Environmental
concept/ Better
interior
environment
New transportation
service
Use green-energy to replace
traditional energy in order to reduce
carbon emissions.
Use formula to calculate and
compare the outcomes.
Provide a new public transportation
mode with better vehicle facility
and more comfortable experience.
Medium
Table 1 Requirement Specification table

11. 2.3 Development
2.3.1 Design Process
Since we did not really have the full details of the project, we applied a simplified version of the VDI
2221 Model to illustrate our design process.
Figure 10 Design Process for the Project
2.3.1.1 Task
To draft a general design plan for a virtual System mentioned in 3.2 Definition.
2. 3.1.2 Specification
(1) Provide visualized traffic data.
(2) Provide a new environmental-friendly travel services, especially for commuting.
(3) Provide technological ideas to enhance existing public transport services.
(4) Promote awareness of environmentally friendly travel.
(5) Generate preliminary plans for basic operation and management of the system.
Task Specification Function Srtucture
Principle Solutpion System Architeture Key Moudules
Layout

12. 2. 3.1.3 Function Structure
After the functional analysis [For more details, please refer to Appendix 5], we designed the
functional structure as shown in the following diagram
Data Processing
System Boundary
Main Flow
Physical Elements Flow
Information Flow
Auxiliary Flow
2. 3.1.4 Principal Solution:
We can see three core ideas as the design principle for solving the public transport problem:
1 Stop adding more vehicle numbers to the roads.
2 Attract more commuters to public transport without increasing public transport facilities.
3 Shape people's perception of green travel.
Choose plan On ride Arrive Pay and Review
Traffic Data Visualization & Recommendation
Vehicle
s
Control info Provide Control Auxiliary Technology
Map Apps/ Traffic Companies
Passengers &
requirements
End
of
travel
Status info
Figure 11 Function Structure

13. 2. 3.1.5 System Architecture [For more details, please refer to Appendix 6]
2. 3.1.6 Key Modules
Information Module:
First thing is to decide what new data can be taken into account: e.g., carriage congestion, vehicle
health, etc. and how to visualise it. To fulfil the functions of this module, we envisage the Street-
Smart project working in depth with mapping apps and public transport system to share basic traffic
information such as real-time road vehicle locations and punctuality, etc. Moreover, we hope to
INPUT (RESOURCE)
Information
Service
Road situation
Vehicle condition
Satellite
Sensor in vehicle
GPS (through smart phone and app)
Sensor in vehicle
Bus Fare authority
Metro Fare authority
Shared transport facilities and tolling authority
Facilities for new low-carbon mode and fare authority
Taxi fare authority
Travel requirement
Passenger
Departure / Destination
Time requirements
Money cost Requirement
Transfer requirements STREET SMART
OUTPUT（FUNCTION）
Information
Service
Visual road data
Comparison of travel options
Customised travel plan
Bus ticket-purchasing
Underground ticket-purchasing
Auxiliary technology for public
transport
Taxi payment (online)
New transportation service Key
Key
Estimation of Carbon emission
Condition of each Vehicle (Sanitary, congestion，facility etc.)
Real-time location, Estimated arrival time of public transport etc.
General
Personal
Free of charge
Membership
Single charge / membership
STREET SMART
Figure 12 System Architecture

14. explore new data entry points to enrich our customers' information requirements.
The next important thing require detailed design is the program and key algorithms to customise
travel solutions based on user input on personal requirements and traffic conditions and to provide
processed data to the City Council for traffic planning (Zhao, J. et al 2019). Through the user's input
of travel demand indicators, such as time requirements, fatigue cost (normally represented by transfer
times), combined with the considerable traffic data integrated by the Street-Smart system, we provide
the user with customed solutions that meet the demand showing a comparison of different solutions
as well. Customers thus can make more effective travel decisions improving the operation efficiency
of transport resources.
As the system is a platform integrated with information and service, the customer can place an order
directly on the app after selecting a travel plan, pay for the fare with mobile payment technology. At
the end of each journey, the app automatically calculates and records the estimated carbon footprint
of each journey for passengers. [For more details please refer to Appendix 7]
Auxiliary technology for public transport:
Based on our previous Assessment of the potential for different technologies, we have proposed the
following feasible scenarios for the application of Auxiliary technology:
(1) L2 level autonomous driving system
We envisage the application of this system on the Bus, whose main function is to improve driving
performance, i.e. to help the driver make faster and more accurate driving judgements or to assist in
providing more stable driving manoeuvres (e.g. maintaining a constant speed), thus optimising
stopping spacing and starting speeds and thus reducing traffic congestion (Li, Z. et al 2017).
(2) Vehicle health monitoring system
By monitoring the health of the vehicle in real time,
drivers can carry out maintenance on problematic
modules or parts in a timely manner, reducing the
probability of breakdowns (Anon, 2015). Customers
can access the operating status of public vehicles
via the app client and select the more stable
performance under the same conditions.
Figure 13 Concept of Vehicle Health Monitoring
Source: https://uk5g.org/

15. (3) Shared Scooter
Based on our research, we found that commuters spend a lot of time in the 'home- station' section and
that the time spent in this section also tends to result in longer waiting times for trains. We therefore
wanted to help commuters solve this problem by offering a shared Scooter [See more details, please
refer to Appendix 8].
New Transport Service:
To generate the draft design of the new transport service, we used the Morphological Chart method
[See more details, please refer to Appendix 9] to support our design.
Function: Solution:
Mobility Rail Road Air
Power Electricity Gasoline Hybrid
Carrying Two-seat Four-seat Six-seat Over ten
Location Self-seeking Reservation Station
Driving Chauffeur Passenger Combination Full-auto
Navigation Free route Fixed route Customed route
Parking Free parking Fixed area parking
Payment Card Mobile-Pay Cash
Final Combination:
Six-seater，electricity-powered, shared commuter vehicle.
Figure 14 A typical six-seater vehicle. Source: https://autokult.pl/
Considering that the vehicle is used for shared transport between passengers, six seats are used instead
of seven to ensure sufficient private space. As for different private experience between different rows,

16. we balance it by different seat-price.
2. 3.1.7 Layout
This section focuses on the two major sub-modules that have been added to the “Street Smart”
project
Shared Scooter:
It is mainly provided to commuters from residential or working areas to underground stations or bus
stop.
Figure 15 Shared Scooter. Source: https://www.wantedinrome.com/
First of all, we will set up a batch of battery-powered scooters in urban area waiting for order.
Secondly, this service is only for regular users with fixed commuting route and time. Commuters
should apply for the membership through app registering location, time and route information.
And we shall allocate the scooter to each member’s request location (near their house) at the request
time (before they leave their house for work) every morning for member to use.
A member only has the permission to ride the specific scooter we assigned to him and only for the
“home-station” route he registered in the app only because this service is only for enhancing the

17. experience of public commuting. We shall use the IOT technology to ensure the scooter shall only
be used by the right member and in the right area.
Figure 16 Operational Processes of the Scooter
Note: Staffs are not necessary to ride on the Scooter, they could use Pickup Truck to gather and convey the Scooters.
Car-sharing:
User inputs basic commuting requirements (necessary requirements: departure point, destination.
Willingness to drive. Willingness to share; other requirements: time requirements, fellow passenger
requirements, etc.) through the App. System matches users with similar routes according to their real-
time travel requirements, and starts allocating vehicles after the matching is completed. When the
Before you wake up: Staff rides the Scooter to your house from Distribution Point
When you get out: Ride the Scooter to your registered Bus stop
After arriving: Wait for the Bus
After you get on bus: Staff rides the Scooter to Distribution Point

18. system has finished matching, each passenger will be told the pick-up point where the shared electric
vehicles are. Passengers must arrive at the designated pick-up point by the designated time, get on
board and click the “Journey-start button” on the app to begin the journey. Once the passengers get
off at their destinations, they must click the “Journey-end button” to end the trip billing. If any
problems occur during the journey, passengers will be able to contact customer service asking for
help.
Figure 17 Operational Processes of the Car-Sharing

19. We also used a Q&A form [for more details, please refer to Appendix 10] to help us to think about
the possible operation details
2.3.2 Environmental Assessment
An electricity-powered six-seater car on the street eliminates the opportunity cost of at least one
private car on the street, as the driver must have a licence. A successful car-sharing trip often includes
4-5 passengers, which means that this one new energy six-seater successfully eliminates the potential
for 4-5 private cars on the street. There will, of course, be some cases of unlicensed passengers, in
which case we can measure the number of customers with a driver license, and then making a survey
about the customer’s private car brand and the usual driving commute mileage, the reduction of
carbon emissions can be calculated according to the IPCC “bottom-up” method (Yuan,
Tao,Yang,2019) [see more details, please refer to Appendix 11].
Beside the car-sharing service, the street-smart project encourages more people to use public transport
by providing well-processed public transport information and better public transport experience.
3 Strategic Analysis
3.1 Macro
3.1.1 PESTLE Analysis:
This table below shows our PESTLE conclusions based on case study analysis [For more details,
please refer to Appendix 12].
P • Price of public transport
• Price of electricity
• Government subsidy
• Low
• High
• High
• UnLikely
• Unlikely
• Likely
E • Time cost
• Unemployment rate
• Pollution prevention costs
• Car manufacture
• High
• Medium
• Low
• High
• Extremely likely
• Unlikely
• Unlikely
• Extremely likely
S • Environmental Concept
• Traffic Congestion
• High
• Medium
• Likely
• Likely
T • Electricity energy
• Electricity facility
• Data Base/analysis
• High
• High
• High
• Extremely likely
• Extremely likely
• Extremely likely
L • Road law
• Personal Information
• Low
• Low
• Unlikely
• Unlikely

20. E • CO2
• Fossil Fuel consuming
• Medium
• Low
• Likely
• Unlikely
Table 2 PESTLE analysis table
3.1.2 Stakeholders Analysis
We have categorised Stakeholders as follows, with notes to the key sections.
Figure 18 Stakeholders’ Catalogue
Examples: Note:
Partners: Map apps;
Mobile payments
apps.
Street Smart app supports Alipay and WeChat payment and other payment
methods, while the map application provides data support for the project
app.
Supplier: Server;
Car manufacture.
Harbin local new energy vehicle manufacturers such as Tonglian Bus
Manufacturing and Longjiang Bus Manufacturing Co.
Customer: College students;
Commuters.
Competitor: Map apps;
Car-hiring companies;
Taxi companies.
Street Smart is an integrated mobility platform that includes taxis as a
daily mode of travel, but the project is still mainly focused on fuel-
efficient travel. The same applies to Map Apps, which is used to provide
road traffic data services and is both a partner and a competitor with
taxis and Map Apps because of the overlap between the project's app
functionality and Map Apps. we do not rule out the possibility of
recommending taxis as the primary travel option to customers
concerning the macro traffic situation.
Investor: Shareholder. Under the premise of government-led projects, the government can
provide funding for the project, and can also attract funding from other
individual investors, investment companies, and partners of the project
such as Maps Apps and Mobile Payment Apps to share the profits.
Government: Staff;
Driver;
Equipment
The government provides start-up funding for the project and coordinates
with various government departments such as traffic management, public
security bureaus and legislative and judicial authorities to issue
Stakeholder
Partners
Supplier
Customer
Competitor
Investor
Employees
Government

21. maintenance;
Customer service.
regulations and emergency plans to provide safety and legal protection for
the project.
Table 3 Key notes on Stakeholders’Analysis
3.2 Micro
3.2.1 Porter 5 Forces:
The following conclusions were reached after we conducted the Porter 5 Forces analysis [For more
details, please refer to Appendix 13].
Supplier power:
(1) The bargaining power of vehicle suppliers is poor. There are many companies that can provide
reliable electric vehicles, On the premise of ensuring the quality, we can invite tenders to choose
the lowest price electric vehicles as our resources
(2) The bargaining power of power
supplier is strong. China's power grid is a
state-owned enterprise (State Grid
Corporation of China). So, the power grid
companies have full pricing power for
electricity prices, and we have no alternative
choices. On the other hand, because the State
Grid is controlled by the government, we can get government subsidies to get lower price
electricity.
(3) The bargaining power of parking area supplier is strong. Land in mainland China is state-owned,
if we want to get a better location as a parking lot, we often have to pay a very high price. On
the other hand, because the land use right is controlled by the government is controlled by the
government, we can get government subsidies to get lower price parking lands.
Buyer power: Buyers have strong bargaining power. When the difference between commuting
experience and time spent is not big, customers will prefer the cheapest commuting method.
Threat of New Entry: Car sharing service needs to provide a wide range of products and services,
and the threshold for new entrants to enter the market is relatively high. For the new entrants, because
the main customers of car sharing service are scattered individual customers, only relying on the low-
price advantage is not enough to seize a large market share. So, the threat of new entry is not high.
Figure 19 Logo of State Grid Corporation of China.
Source: http://www.sgcc.com.cn/

22. Threat of Substitution: The substitutions include
taxis, DIDI, Ubers, private cars, etc. Combined
with the current market situation, online car hailing
and private car have a great alternative advantage. .
The convenience of private cars is incomparable to
shared cars.
Competitive Rivalry: At present, the competitive
rivalries are online car hiring, taxi and traditional car rental enterprises. They have a high degree of
overlap with shared car customers. These competitors are highly competitive.
3.2.2 SWOT:
Here we retain the key points of the strategy implementation based on SWOT analysis [For more
details, please refer to Appendix 14].
S:
1. Information and one-stop
service
2. Algorithm
3. Technical team
4. Accurately customer-matching
W:
1. Lack of cash flow
2. Lack of Data
O:
1. Poor public transport
experience;
2. High cost of taxi and self-
driving
3. Low service homogenisation
4. Government’s support
SO：
1. Cooperate with the government
2. Cooperate with public
transportation
WO:
1. Start the project within a small
area
2. Focus on data processing and
marketing
T:
1. Competitive Rivalry from
other companies
2. Price-oriented trend
3. High cost of power and land
resources.
ST:
1. Seize the market as soon as
possible.
2. Pay as we earn to provide lower
price
3. Policy subsidies
WT:
1. Obtain information resources from
software companies.
2. Promotion activities for college
students.
Table 4 SWOT analysis table
SO (Strength and Opportunities)
2016-2019, the country's fiscal spending on energy conservation and environmental protection is
RMB 2.4 trillion, and these financial investments have guided and leveraged a large amount of social
capital to participate in ecological and environmental protection work around the country. (Sun. X,
2020)
Figure 20 Logo of DIDI.
Source: https://www.didiglobal.com/

23. In the early stage, we can fight for government subsidies in the name of green travel. We can also
cooperate with the government operated bus and subway companies to share the data of public
transportations, and provide a public interface, so that users can choose to take public transport or use
shared cars.
WO (Weakness and Opportunities)
In the early stage, we should invest the project in a small area where the flow of people is relatively
large, so as to avoid the occupation of a large amount of funds. Communities with a large number of
employees and CBDs with a large number of companies are our preferred locations
At the same time, we need to do a good job of market research, use the existing data, with our
powerful algorithm to provide customers with the best travel advice service.
ST (Strength and Threats)
We should cooperate with the government to obtain financial support from the government, including
low electricity price, low land price and other resources. Technical experts and legal experts to
participate in the relevant legislative work to promote the perfection of the legal provisions of car
sharing.
WT (Weakness and Threats)
The famous mapping software on the market today, such as Baidu Maps and Gaode Maps can be our
partners to provide the map information. On the basis of the existing preferential policies, more
preferential policies should be given to college students to cultivate the concept of shared travel for
young people. (lbs.amap.com. 2020).
4 Project Summary
4.1 Business Model Canvas
This table below illustrates the business model for our Project. [see more details, please refer to
Appendix 15]

24. Table 5 Business Model Canvas for Street-Smart

25. 4.2 Supportive Reasons
There are several advantages of our project will be the reasons why our flagship project will be
selected. The following will analyze it from a technical and commercial perspective.
First of all, our project will focus on the concept of sharing. In the previous way of commuting,
most people traveled alone and did not interfere with each other, and their own way of travel would
not affect others. However, the idea of street-smart allows people with overlapping commuting
schedules to commute together, this way of commuting can reduce private car traveling. For
example, four people with the similar living area and workplace used to drive to work using four
cars every day, now with the sharing travel provided by our project, they are able to finish the travel
with only one electrical vehicle, making the total travel cost is about 1/4 of the previous. Moreover,
every time someone uses shared travel, the road congestion during commuting will get better
because the number of private cars on road is decreases.
Secondly, all shared cars we provide are new energy vehicles. Such technology will reduce carbon
emissions caused by automobile exhaust and can appropriately alleviate environmental problems in
Harbin. Because in winters, cities in northern China are severely affected by smog and have to
adopt car-restrictions by car number.
Finally, people who live far away from subways and bus stations are unwilling to choose public
transportation. With scooter, public transportation can re-enter their choice of commuting methods.
For commuters who have tolerated long walking time before, the reduction in commuting time is also
a saving of travel costs. [See more details, please refer to Appendix 16]
5 Risk
5.1 FMECA
This is the FMECA table we used to analyse the risks.

26. Table 6 FMECA Table for Car-sharing Service

27. 5.2 Mitigations
These four problems related to safe driving fall into the undesirable range. These four problems need
to be solved urgently. [See more details please refer to appendix 17]
5.2.1 The traffic violations/accidents caused by inexperienced drivers.
In order to avoid this kind of situation, we need to set strict scoring system for shared car drivers so
that both we and passengers can evaluate the driver's skills and behaviours. For users with lower
scores due to bad behaviours, the system will limit their chance to drive.
5.2.2 The failures of the vehicle’s safety system/ important parts (engine, brake, etc)
The failures of important parts/safety system shall cause serious dangers on customers. These
problems are mainly caused by inadequate vehicle maintenance. In order to avoid these problems,
besides the introduction of Vehicle health monitoring system that we mentioned before, we also need
to hire more maintenance personnel, increase vehicle maintenance efforts, and ensure that every
vehicle is completely safe before it is put into use.
5.2.3 Violate crimes
These problems are often due to the fact that the system does not recognize the passengers with
dangerous motives. To avoid such situation, we have to design a more reasonable algorithm to
evaluate customers’behaviour, the customers with too low behaviour scores will be banned to use the
car sharing app. We also need to cooperate with the police department to enhance the design of
emergency-calling button in vehicles and maybe introduce the facial-recognition system.
For the problem in the tolerable range, most of them are the problem of driving experience. We are
confident to solve these problems with a reasonable scoring system.
6 Prospects
As the project continues to run and the number of users grows, we will be able to provide the City
Council with vast amounts of traffic data for their macro-level traffic planning in exchange for longer-
term policy support.
As the user group increases, the amount of data increases. Two six-seater electric vehicles with similar
routes can be combined into one twelve-seater minibus. Further easing road congestion and reducing
carbon emissions. Once the twelve-seater minibus is realised, a dedicated driver can be dispatched to
fully reduce the cost of driving fatigue. This initiative is similar to shuttle bus, but more flexible. A
more autonomous, customised match based on real travel data of people in urban areas.

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