Internet DRAFT - draft-zhang-t2trg-accident-blockchain
draft-zhang-t2trg-accident-blockchain
Network Working Group R. Li
Internet-Draft X. Zhang, Ed.
Intended status: Informational J. Fan
Expires: July 2, 2021 Inner Mongolia University
December 29, 2020
Architecture for collecting traffic accident information based on
blockchain
draft-zhang-t2trg-accident-blockchain-00
Abstract
Blockchain is a distributed technology, and it uses cryptography and
hash functions to store data in a chain to ensure that data are
tamper-resistant and traceable. So, this document proposes an
architecture for collecting traffic accident information based on
blockchain. At the same time, this document describes the working
method of collecting traffic accident information under this
architecture.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Relate work . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. System structure . . . . . . . . . . . . . . . . . . . . . . 5
3.1. Perception layer . . . . . . . . . . . . . . . . . . . . 6
3.2. Edge computing layer . . . . . . . . . . . . . . . . . . 6
3.3. Service layer . . . . . . . . . . . . . . . . . . . . . . 6
4. Scheme design . . . . . . . . . . . . . . . . . . . . . . . . 7
4.1. Traffic accident information query . . . . . . . . . . . 7
4.2. Traffic accident information return . . . . . . . . . . . 7
4.2.1. Resource fragmenting method . . . . . . . . . . . . . 7
4.2.2. Resource Naming Method . . . . . . . . . . . . . . . 8
4.3. RSUs consensus . . . . . . . . . . . . . . . . . . . . . 8
4.4. Traffic accident information storage . . . . . . . . . . 9
5. Discuss . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 10
7. Security Considerations . . . . . . . . . . . . . . . . . . . 10
8. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 10
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 11
10. Informative References . . . . . . . . . . . . . . . . . . . 11
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 12
1. Introduction
With the development of society, there are more and more vehicles on
the road, and a problem that follows is that the incidence of traffic
accidents is also increasing. The frequent occurrence of traffic
accidents has brought a serious impact on human life, and has brought
certain pressure on the relevant traffic departments to deal with
traffic accidents. The handling of traffic accidents must be timely,
and the evidence must be obtained correctly, so as to avoid traffic
jams, secondary accidents and legal disputes. Therefore, how to use
the existing technology to quickly, correctly and effectively deal
with traffic accidents has become a very important issue.
The most important thing to deal with traffic accidents is to collect
traffic accident information (also known as "resources"). At
present, the main methods of collecting traffic accident information
are manual and automatic. Among them, manual methods include
measuring tape, witness investigation, and on-site photographing.
The automatic method is to use the camera at the intersection. These
methods require a long time, and cause certain difficulties for rapid
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recording, rapid evacuation of traffic, subsequent accident analysis
and liability determination.
In the past few years, with the development of wireless communication
technology and the automobile industry, the Vehicular Ad Hoc Network
(VANET) has developed significantly [Misra2009]. Based on the VANET
researchers have proposed a large number of related applications,
which are divided into safety-related applications and comfort-
related applications [Eze2014]. These applications mainly use the
cooperation between vehicles to transmit messages. The driving
recorder is an instrument that records the video image and sound of
the vehicle during driving. If a traffic accident occurs in front of
the vehicle, it can provide strong evidence for handling the traffic
accident. Resources can also be collected through cooperation
between vehicles. It can be seen that the use of vehicle-to-vehicle
collaboration in the VANET can transmit driving recorder?s data to
relevant departments, which is beneficial to better handling of
traffic accidents.
Most of the resources transmitted is used as evidence. It is
necessary to ensure that the data transmitted to the relevant
transportation department are true, confidential, and not tampered,
and traceable. However, in the communication process, resources
security is the main concern, including the safety protection issues
in transmission process, the security issues of centralized storage
in the data center, the access control and privacy protection.
Blockchain is a distributed technology. It uses cryptography and
hash functions to store data in a chain to ensure that data are
tamper-resistant and traceable. And the technology uses a consensus
protocol to ensure data consistency. Therefore, blockchain
technology can be applied to the VANET environment to solve the
security problem and remove the dependence on trusted central
entities. However, the process of consensus has to solve the large
computational problem which cannot be done on computing resources
constrained vehicles. As a new type of technology, Mobile Edge
Computing (MEC) can be used not only to offload computationally
intensive tasks from mobile devices to edge networks, but also to
optimize processing before sending data to the core network, and to
provide edge cloud services for mobile users at the edge.
Therefore, this document proposes an architecture for collecting
traffic accident information based on blockchain. It uses blockchain
to ensure that resources are tamper-resistant and traceable, and uses
edge computing to solve the large computational problem of blockchain
consensus process.
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In section 2, some current researches on collecting transaction
accident information are described, and their shortcomings are
analyzed. Section 3 proposes the structure of this document.
Section 4 describes the working method of collecting traffic accident
information in the framework proposed in this document. Section 5
discusses how the architecture guarantees the security of VANET.
Section 6 summarizes the full document.
2. Relate work
With the increase of vehicles on the road, the number of traffic
accidents has also increased. The traditional methods of collecting
traffic accident information are manual methods-pulling a measuring
tape, witnessing investigation, and taking pictures on the spot,
which takes a long time and is not conducive to the rapid evacuation
of traffic and rapid recording of the scene. Therefore, there are a
large number of researchers in collecting traffic accident
information.
Among these studies, one type of research is to use web-based methods
to obtain accident information. Users upload the accident
information to the server of the relevant transportation department
through the browser, and the relevant transportation department
obtains the traffic accident information from the server as the basis
for handling the traffic accident. Lobont et al. collect basic
information of accidents in a web-based traffic accident collection
system, including time and location [Lobont2013]. In a web-based
traffic accident collection system, Williams et al. collect
information on the severity of accidents, vehicle types, casualties,
road conditions, weather conditions, and light conditions
[Williams2015]. Another form of such research is the use of smart
phones. CrashData [Derdus2014] proposed by Derdus et al. is an
application based on mobile smart phones. The application can upload
the basic information of the traffic accident to the server. This
type of research must be connected to the Internet and requires users
to participate in actively uploading information, but users may not
upload resources voluntarily.
Another type of research is to install fixed infrastructure on both
sides of the road to obtain traffic accident information. In the
traffic accident investigation and management system based on GPS
VRS, GIS road database and stereo vision technology proposed by
Qingwu H et al. [Hu2011], the traffic accident information is mainly
obtained through GPS VRS and GIS road database, and then restored
using stereo vision technology. In the system for collecting traffic
accident information based on ultrasound and ZigBee wireless
transmission technology proposed by Song H et al. [Song2014], the
state of the vehicle during a traffic accident is measured by
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ultrasound, including information such as speed and direction. This
type of research is limited by the location of fixed infrastructure,
and traffic accident information cannot be collected where there is
no fixed infrastructure.
Other research is firstly obtaining traffic accident information
through various sensors on the vehicle, and then using the VANET to
transmit the traffic accident information to the relevant traffic
department. In the literature [Abduljalil2012], Abduljalil FM et al.
use on-board angle sensors, airbag sensors, cameras, GPS sensors,
etc. to obtain traffic accident information, and then use Wi-Fi,
GPRS, 3G, WIMAX, 4G-LTE wireless transmission technology to transfer
traffic accident information to the relevant department. In the
VWaas service architecture proposed by Hussain R et al.
[Hussain2013], when a traffic accident occurs, the surrounding
vehicles use the car?s camera to capture the traffic accident
information, and then send the captured content to the centralized
server facility. In this process, the vehicle directly sends traffic
accident information to the server via 3G/4G or transmits the traffic
accident information to the RSUs (Road Side Units) via DSRC, and then
the RSU transmits the information to the RSUs server.
Among the above methods for collecting traffic accident information,
the web-based method requires users to upload traffic accident
information to a server, which must be connected to the Internet, and
the time for collecting information is relatively long. Based on the
way roadside infrastructure collects traffic accident information,
limited by the fixed location of the infrastructure, it is impossible
to collect traffic accident information in areas not covered by the
infrastructure. The method of collecting traffic accident
information based on vehicle sensors and the VANET requires the
participation of RSUs. In the above three methods of collecting
traffic accident information, only the information after the traffic
accident can be collected, and the information before the traffic
accident cannot be obtained. The analysis of the accident and the
determination of responsibility after the accident have certain
difficulties. And there is no guarantee that the collected traffic
accident information is not been tampered with and can be traced to
the source.
3. System structure
This document proposes a security architecture for collecting traffic
accident information based on blockchain. The architecture consists
of three layers, namely perception layer, edge computing layer, and
service layer. The perception layer comprises vehicle and RSU,
together forming blockchain network. The edge computing layer
provides computing resources and edge cloud services for the
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perception layer. The service layer includes cloud services and
blockchain.
3.1. Perception layer
A driving recorder is installed on the vehicle, which can record the
traffic accident information of the vehicle passing position.
Because of the constraint of computing resource and the mobility, the
vehicle cannot perform all blockchain functions, including wallet
(save address and private key), miner (mining), complete blockchain
(save all blockchain data), network routing (validate and propagate
transaction block information, discover and maintain connections to
peer nodes). In this document, vehicle performs the functions of
wallet and network routing.
The RSU connects each other by wired communication, forming stable
blockchain network which can ensure a unique ledger for collecting
traffic accident information. Therefore, all blockchain functions
are performed on the RSU. Even while one vehicle is moving, it can
communicate with RSU directly or through other vehicles.
3.2. Edge computing layer
There are lots of transactions occurred for collecting traffic
accident information. If all the consensus work of the blockchain
transaction is completed in RSU, it will inevitably affect the
network performance and bring high delay. Therefore, this document
offloads the computationally intensive work to MEC, and the result is
returned to the RSU after completion. MEC is also responsible for
handling other computationally intensive work, such as video or image
processing, etc.
3.3. Service layer
The traffic accident information recorded by the driving recorder is
video, which has a large amount of data and is not suitable for
storage in blockchain of RSUs. Because the blockchain is distributed
storage, each blockchain node stores all the data, which consumes
lots of storage resources. So, the document stores the traffic
accident information on the cloud server, which can not only store
the data permanently, but also facilitate the inspection and evidence
collection by the traffic police department.
So, for data stored in the service layer, part of the data which are
tamper-resistant and traceable, such as traffic accident data,
traffic violation data, etc. are stored using blockchain. The other
part of data is stored on the cloud service.
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4. Scheme design
Based on the above architecture, the working method of collecting
traffic accident information includes 4 steps, including traffic
accident information query, traffic accident information return, RSUs
consensus, and traffic accident information storage. The working
methods of collecting traffic accident information are as follows.
4.1. Traffic accident information query
The traffic police department initiates a traffic accident
information inquiry request based on the time and location of the
traffic accident. The query request is sent to the vehicles driving
on the road through the RSUs. Because it is uncertain which vehicles
have captured the traffic accident information, in order to enable
more vehicles within the communication range of the RSU to receive
the traffic accident information query request, the document uses the
flooding method to send the query request. At the same time, delay
tolerant network technology is used to forward query requests to
vehicles that are not within the communication range of RSU by using
moving vehicles.
4.2. Traffic accident information return
The vehicle receives the traffic accident information query request
and checks whether the traffic accident information is recorded
locally. If recording, extract the traffic accident information from
the driving recorder and transmit it to the nearest RSU. If the
vehicle does not directly communicate with the RSUs in a single hop,
it is forwarded through the intermediate vehicle.
The vehicle is in a moving state. If the traffic accident
information recorded by the driving recorder is directly disseminated
on the network, the probability of transmission failure will be very
high, and the network performance will be affected. Therefore, this
document processes the traffic accident information in fragments, and
then transmits the fragmented traffic accident information, and
finally aggregates it through the RSUs.
4.2.1. Resource fragmenting method
The resources need to be transmitted in fragments. However, the size
of the fragments must ensure that a complete resource can be
transmitted within the shortest communication time between vehicles.
Therefore, this document determines the size of resource fragments
according to the shortest communication time of vehicles on urban
roads. First, determine the shortest time for vehicle communication
on urban roads. The movement of vehicles on urban roads can be
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divided into two types: same direction driving and reverse direction
driving. When two vehicles are driving in the same direction and in
the reverse direction on the city road at the same speed, the
communication time for them when driving in the reverse direction is
shorter.
Generally, vehicles on urban roads are not allowed to exceed the
prescribed speed. When the vehicle is traveling at the maximum speed
specified on the city road, the communication time between them is
the shortest. Therefore, the fragment size of the resource is
defined as the data size that can be transmitted in the shortest
communication time between vehicles, which can ensure that any
resource can be transmitted within the vehicle communication time
range.
4.2.2. Resource Naming Method
The traffic accident information after fragmentation is named
according to certain rules, which is convenient to distinguish from
other vehicles and to facilitate aggregation. The naming rules are
as follows:
NodeID_SerialNum_TotalNum_Time_Location
Among them, NodeID represents the ID of the node, that is, the
license plate number of the vehicle; SerialNum represents the serial
number of the traffic accident information fragment; TotalNum
represents the total number of traffic accident information
fragments; Time represents the time when the traffic accident
occurred; Location represents the location of the traffic accident,
that is, the latitude and longitude.
For the same traffic accident resource, the node ID can distinguish
which vehicle provides the resource, and the resource sequence number
and the total number of resource fragments can distinguish each
fragment of the resource provided by the vehicle. For the same car
(same node ID), even if the resources of multiple traffic accidents
are captured, different traffic accidents can be distinguished by the
time and location of the traffic accident. Moreover, each fragment
of the same traffic accident resource can be distinguished by the
resource sequence number and the total number of resource fragments.
4.3. RSUs consensus
The traffic accident information needs to be verified, agreed, and
added to the blockchain. The specific process is as follows:
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a. When RSUs receive traffic accident information, they generate a
transaction based on the basic information and hash value of the
traffic accident information (NodeID, SerialNum, TotalNum, Time,
Location) and forward it to other RSUs.
b. Other RSUs in the blockchain network receive the transaction and
check whether the transaction is valid and the format is correct.
If the inspection meets the requirements, it is placed in the
transaction storage pool and forwarded to other RSUs. The other
RSUs that receive the transaction repeat the process.
c. The RSU that obtains the right to packaging the transactions in
the transaction storage pool into a block, and then mines the
block. The mining process needs to complete a large number of
calculations, and RSUs generally do not have the ability to
complete a large number of calculations, and the calculation
tasks need to be offloaded to edge computing. Edge computing
completes the calculation task and returns the result to the
RSUs. The RSUs sends the block to other RSUs to spread across
the entire network.
d. After receiving the block, other RSUs verify the block. If the
block is verified, the RSUs deletes the completed consensus
transaction from the transaction storage pool and the block being
mined, and at the same time adds it to the blockchain.
4.4. Traffic accident information storage
The RSUs aggregate the traffic accident information fragmented in the
blockchain. The aggregating process involves video processing, so
this process is also offloaded to edge computing to reduce the
workload of RSUs and increase its effectiveness. After the edge
computing completes the aggregation of the traffic accident
information, it sends the complete traffic accident information to
the RSUs.
The blockchain in RSUs cannot store all traffic accident information.
So it is uploaded to the cloud for storage, and the blockchain in the
RSUs only store the digest of traffic accident information. In order
to ensure the security of data in cloud, the data which are tamper-
resistant and traceable are stored using blockchain. While, other
data adopt the original storage method of the cloud, guaranteeing
security by cloud computing architecture.
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5. Discuss
This section focuses on how the architecture guarantees the security
for collecting traffic accident information.
In this security architecture, vehicles and RSUs in the perception
layer together form blockchain network to improve the security for
collecting traffic accident information. However, traffic accident
information generated by the vehicle generally are stored in the
cloud or a centralized platform so as to provide data support for
related department. Considering a large amount of traffic accident
information, the perception layer does not have enough space to
store. Therefore, in this security architecture, the traffic
accident information is still stored in the cloud of the service
layer. In order to ensure the security of data in cloud, the data
which are tamper-resistant and traceable are stored using blockchain.
While, other data adopt the original storage method of the cloud,
guaranteeing security by cloud computing architecture.
At the perception layer, the main challenge is security of traffic
accident information during transmission. So, blockchain in the
perception layer is used to solve the security problem in the
transmission process. And the data solving the security problem in
transmission process need to be stored in perception layer
blockchain. By combining MEC, the perception layer can ensure the
security of traffic accident information in transmission process.
6. IANA Considerations
There are no IANA considerations related to this document.
7. Security Considerations
There are no Security Considerations related to this document.
8. Conclusion
This document proposes an architecture for collecting traffic
accident information based on blockchain. The architecture includes
three layers, namely perception layer, edge computing layer and
service layer. The perception layer ensures the security of VANET
data in the transmission process through the blockchain. The edge
computing layer provides computing resources and edge cloud services
for the perception layer. The service layer uses the combination of
traditional cloud storage and blockchain to ensure the security of
data.
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9. Acknowledgements
This work was supported by the Inner Mongolia Autonomous Region
Science and Technology Achievements Transformation Project (No.
CGZH2018124).
10. Informative References
[Abduljalil2012]
Abduljalil, F., "A framework for vehicular accident
management using wireless networks", 2012 IEEE 13th
International Conference on Information Reuse &
Integration (IRI), 2012.
[Derdus2014]
Derdus, K. and V. Ozianyi, "A mobile solution for road
accident data collection", Proceedings of the 2nd Pan
African International Conference on Science, Computing and
Telecommunications (PACT 2014), 2014.
[Eze2014] Eze, E., Zhang, S., and E. Liu, "Centralized Conferencing
(XCON) Media Models", 2014 20th International Conference
on Automation and Computing, 2014.
[Hu2011] Hu, Q. and H. Wang, "A Framework for Traffic Accident
Scene Investigation with GPS VRS, Road Database and Stereo
Vision Integration", 2011 International Workshop on
Multi-Platform/Multi-Sensor Remote Sensing and Mapping,
2011.
[Hussain2013]
Hussain, R., Abbas, A., Son, S., Kim, K., Kim, K., and O.
Oh, "Vehicle witnesses as a service: Leveraging vehicles
as witnesses on the road in vanet clouds", 2013 IEEE 5th
International Conference on Cloud Computing Technology and
Science, 2013.
[Lobont2013]
Lobont, L., FILICHI, A., and L. POPESCU, "Improving
traffic safety using modern methods for accident data
collection", ANNALS OF THE ORADEA UNIVERSITY Fascicle of
Management and Technological Engineering, 2013.
[Misra2009]
Misra, S., Zhang, I., and S. Misra, "Guide to wireless ad
hoc networks", Springer Science & Business Media, 2009.
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[Song2014]
Song, H., Ming, J., Tang, J., Zeng, D., Duan, w., and Z.
Yin, "Wireless Positioning System for Investigation of
Road Traffic Accidents", Proceedings of the International
Conference on Logistics, Engineering, Management and
Computer Science, 2014.
[Williams2015]
Williams, K., Idowu, P., and E. Olonade, "Online Road
Traffic Accident Monitoring System for
Nigeria", Transactions on Networks and Communications,
2015.
Authors' Addresses
Ru Li
Inner Mongolia University
Hohhot 010021
China
Phone: +86 15804712558
Email: csliru@imu.edu.cn
Xiaodong Zhang (editor)
Inner Mongolia University
Hohhot 010021
China
Phone: +86 15247168840
Email: cszxd@imu.edu.cn
Jun Fan
Inner Mongolia University
Hohhot 010021
China
Phone: +86 18686016307
Email: 250832228@qq.com
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