Lessons learned through automated driving bus operationand efforts using C-ITS solutions
S. Suzuki, K. Shimono, M. Umeda, K. Iwasaki, K. Nakano & Y. Suda
Institute of Industrial Science, The University of Tokyo, Japansuzuki41@iis.u-tokyo.ac.jp

ABSTRACTThis paper reports on the findings obtained from the long-term operation experiment of
automated driving bus being conducted in the Kashiwa-no-ha area of Japan. First, an
overview of the state-level R&D projects for the social implementation of automated driving
services and development of legal systems will be introduced. An overview of the Japanese
government's efforts to date, such as the SIP-adus project, which has been working on the
research and development towards social implementation of automated driving since 2014
under the cooperation of relevant ministries and agencies will be introduced. In addition, it
will be introduced that the requirements necessary in Japan to implement Level 4
autonomous mobility services in society, mainly on the revision of the Road Traffic Act inApril 2022, which paved the way for mobility services to be realized by Level 4 automateddriving. Next, an overview of the long-term operation experiment of automated driving bus
that the authors are working on, and the knowledge and issues obtained from the experimentwill be reported. This project is commenced under the framework of the Kashiwa ITS
Promotion Council. Participants include a variety of companies such as automated driving
vehicle manufacturer, equipment manufacturer, insurance company, leasing company, bus
operator, and developer, as well as university, community development organization, andthe city hall, and are not only engaged in technology development and verification, but also
created an ecosystem for social implementation and are promoting initiatives. The
automated driving operation at SAE level 2 has been continued for about three years.
However, in the operation so far, it has been observed that there are many cases where
drivers manually intervene in the automated driving system in order to prevent the negative
effects on the surrounding road users, such as other vehicles and pedestrians when passing
through intersections, and to avoid obstruction of travel by vehicles parked on the street. In
this paper, it will also be reported that the results of analysis of the factors that hinder
automated driving obtained from the operation so far. Furthermore, in order to eliminate
these impediments to automated driving bus service, it will be reported that efforts havestarted in 2022 in order to realize level 4 automated driving bus service by 2025 byintroducing C-ITS. Finally, we will discuss the challenges and prospects of introducing
Cooperative ITS into automated driving bus services in Kashiwa-no-ha.
1. INTRODUCTION
1.1. Recent initiatives on automated driving in Japan
In Japan, pioneering efforts in research and development of automated driving technology
were seen in the 1990s. However, the full-scale and large-scale efforts were started in 2014,
when the "Public-Private ITS Initiative/Roadmaps" [1] was formulated as a national strategy
for automated driving, and under it, cross-ministerial and public-private collaboration has
been conducted to research and develop automated driving technology and develop aframework for social implementation. This initiative follows the establishment of the Strategic
Innovation Programme (SIP) based on the “Japan Revitalization Strategy”, which wereapproved by the Cabinet in 2013. In the first phase of the SIP, which started in 2014, the[1]

XXVIIth World Road Congress

“SIP Automated Driving System” was implemented with the aim of realizing the expected
timeframe for the market and service realization of automated driving systems, as set out inthe 'Public-Private ITS Concept and Roadmap'. In addition, “SIP-adus (SIP AutomatedDriving for Universal Services)” has been implemented in the second phase of the SIP,
which started in 2018.
In these programs, research and development of automated driving technologies,
particularly in the areas of “Technologies for using the traffic environmental data”, “Safetyassurance technologies”, “Cyber security” and “Creation of an architecture for geographicaldata for automated driving”, which are considered to be collaborative areas, was carried out
under a cross-agency, industry-academia-government collaboration structure. In addition,
field operational tests of automated driving technologies have been conducted in various
regions nationwide.
As a result of these efforts, a Japanese car manufacturer was the first in the world to obtain
Level 3 type approval from the Ministry of Land, Infrastructure Transport and Tourism (MLIT),
Japan in November 2020, and the market launch of Level 3 automated driving system wasachieved in March 2021 [2]. In addition, a driverless automated mobility service using a
remote automated driving system (Level 3) has started operation in Eiheiji-town, Fukui
prefecture, in a limited Operational Design Domain (ODD) [2].
Besides, a company has been established to develop and distribute high-precision 3D maps,
based on the achievements of the SIP projects involving industry -academia-government
collaboration. By the end of 2018, this company have developed and started commercial
distribution of high-precision 3D maps of approximately 30,000 km of expressways andmotorways across the country. In addition, an automated driving evaluation environment incyberspace has been established to enable the evaluation of automated driving systems ina virtual space, similar to real-world conditions [3].
1.2. Initiatives to realise Level 4 automated mobility services in Japan
In Japan, legal and institutional arrangements have also been developed to promoteresearch and development of automated driving technology and to realize social
implementation of automated driving services, as shown in Table 1.

Table 1 - Institutional Arrangements on Automated Driving

Year

Development of legal framework

2016

Formulation of the "Guidelines for Public Road Trials on Automated Driving
Systems"
Amendments to relevant Notices based on "Safety Standards for Road
Transport Vehicles"
Formulation of "Road Use Permission Criteria for Public Road Demonstrationsof Automated Driving"
Amendments to and enforcement of the "Road Transport Vehicle Act" and"Road Traffic Act"

2017
2019
2020
2022

Amendments to the "Road Traffic Act" (entered into force on April 1)

In 2016, the National Police Agency formulated the “Guidelines for Public RoadsideExperiments on Automated Driving Systems” to enable demonstration tests of automateddriving technologies on public roads. These guidelines clarify that demonstration tests of[2]

XXVIIth World Road Congressautomated driving systems can be carried out on public roads without special permission or
notification, for example by ensuring that the safety driver is in the driver's seat of theexperimental vehicle and can perform the necessary operations in an emergency. In addition,
the road-use permission criteria for public road demonstrations have also been improved by
specifying requirements for remote automated driving systems and for automated vehicles
that are operated by a device shaped differently from a conventional steering wheel andbrake during manual operation.
In 2020, amendments to the “Road Transport Vehicle Act” and the “Road Traffic Act” madeit legally possible to realize SAE driving automation level 3. As a result, as mentioned above,
the world's first Level 3 passenger car was put on the market in 2021 and a Level 3
automated driving mobility service was launched in Eiheiji-town, Fukui prefecture.
In 2022, the “Road Traffic Act” was amended again, and the legal system was developed torealise driverless automated driving mobility services, SAE driving automation level 4.
Specifically, a new permit framework was established for those who intend to perform
automated driving without a driver, named “Specified Automated Operation (SAO)”, whichis equivalent to Level 4. Table 2 provides an overview of the permit framework for SAO. It isstipulated that this permit framework will start in April 2023, and it is expected that Level 4
automated driving mobility services will be launched from April onwards in Japan.
Table 2 – Overview of the Specified Automated Operation [4](1) Permission for Specified Automated Operation (SAO)・ Parties seeking to conduct automated driving without a driver ("Specified Automated Operation"), equivalent to Level 4,
require permission from the Prefectural Public Safety Commission
・ Parties who intend to obtain a permission shall submit a "SAO Plan" to the Prefectural Public Safety Commission
・ When the Prefectural Public Safety Commission intends to grant a permission, it shall hear opinions from the mayor of themunicipality whose area includes the route of the SAO(2) Permission Criteria
・ The vehicle must be capable of SAO
・ The SAO must be performed in compliance with the ODD*・ Smooth and reliable implementation is expected for the measures which the SAO implementer or the SAO staff must
implement under the Road Traffic Act
・ The SAO conducted according to the SAO plan is not likely to significantly interfere with other traffic
・ The SAO is for the purpose of transporting people or goods and is recognized as contributing to the convenience or
welfare of local residents* ODD: Operatinal Design Domain(Specific conditions under which an automated driving system is designed to operate (thetraveling route, the time of day, weather, etc.))(3) Obligations of a Permission Holder ("SAO Implementer")・ SAOs must comply with the plan for SAO and the conditions attached to the SAO permission
・ Installation of remote monitoring equipment and assignment of a person ("SAO Supervisor") who perform the remotemonitoring (except when the SAO Supervisor is on board)・ The SAO implementer must provide education to the SAO staff, etc.
(4) Obligations of SAO Supervisors
・ Monitor the state of the operation of the remote monitoring・ In the event of a traffic accident, taking measures to notify the fire department and to send a person responsible for on-sitemeasures to the scene
・ In the event of a traffic accident, reporting the date and time of traffic accidents to police officers, etc.
(5) Administrative Disposition
・ The Prefectural Public Safety Commission may issue instructions, revoke or suspend permission, etc., when a SAO
Implementer, etc., violates laws and regulations
・ The chief of a police station may suspend the validity of a permission provisionally in the event of a traffic accident or otherincident in a SAO[3]

XXVIIth World Road CongressIn addition, research and development under a project of the Ministry of Economy, Tradeand Industry (METI) and Ministry of Land, Infrastructure, Transport and Tourism (MLIT) has
started since 2021 for the social implementation of Level 4 automated driving mobility
services. The project, named “Project on Research, Development, Demonstration and
Deployment (RDD&D) of Autonomous Driving toward the Level 4 and its Enhanced Mobility
Services (RoAD to the L4)” has started including four themes for research, development anddemonstration. The four themes are: “Realisation of Level 4 automated mobility services
under the limited ODD”, “Expansion of ODD and vehicles”, “Practical application ofadvanced logistics systems on expressways” and “Establishment of automated mobility
services in mixed traffic environment.” Furthermore, field operational tests are being actively
conducted in various regions to realize the Government's goal of implementing Level 4
automated mobility services in 50 locations by 2025 and in 100 locations by 2027.
2. OVERVIEW OF AUTOMATED BUS OPERATION IN KASHIWA-NO-HA
2.1. Framework of the initiative
A long-term demonstration experiment for automated driving bus operation in the Kashiwano-ha area of Kashiwa City, Chiba prefecture began in November 2019. This long-term
demonstration experiment is being conducted with two main objectives. The first is todevelop and verify automated driving technologies. The second objective is to verify how
automated mobility can be operated as a sustainable mobility in urban development. For
this reason, the implementation structure of this long-term demonstration of automateddriving bus is being carried out with the participation of a diverse range of stakeholders who
participate in the “Kashiwa ITS Promotion Council”, as shown in Table 3. In other words,
unlike other demonstration experiments conducted over a short period of time, in order toprovide a sustainable automated mobility service, not only companies with technicalresources but also parties with non-technical resources such as Kashiwa City Hall, theUrban Design Centre, which is responsible for promoting urban development in Kashiwano-ha, a property development company, an insurance company, a car leasing company
and others are participating in the project. This has enabled initiatives to improve the social
acceptance of automated mobility by holding test-ride events for residents, as well as
examining how automated mobility should be implemented in urban development.

Table 3 - Contributors to the long-term demonstration experiment of automated driving bus
Participants contributing mainly to technical considerations
Bus operator
Automated bus development company
Remote monitoring system provider
Magnetic positioning system development company
Companies developing Cooperative ITS RSU
Participants contributing mainly to non-technical considerations
Kashiwa City Hall
Urban Design Center Kashiwa-no-ha
Insurance company
Car leasing company
Property development company
Consulting company
Leading Organization
The University of Tokyo[4]

XXVIIth World Road CongressFrom 2021, based on the previous initiatives for the operation of automated driving bus, newR&D activities are carried out under the CooL4 (Cooperative Level 4 Automated Mobility
Service in mixed traffic environment) project, as a part of the project, “RoAD to the L4.” The
CooL4 consortium, which includes The University of Tokyo, Nagoya University, AIST andothers, is developing and verifying technologies under the automated driving bus operationin Kashiwa-no-ha [5].
2.2. Operation of automated bus
Figure 1 shows the route of the automated driving bus service in Kashiwa-no-ha. The
Kashiwa-no-ha area is located approximately 30 km from central Tokyo. The Kashiwa-noha area is served by Kashiwanoha-campus Station on the Tsukuba Express line, whichconnects central Tokyo and Tsukuba City by train. The University of Tokyo, Chiba University
and the National Cancer Centre Hospital East are located near Kashiwanoha-campus
Station.

Source: Geographical Survey Institute map with relevant information added by the author

Figure 1 – Route of automated driving bus operation

Automated driving bus is operated as part of a shuttle bus service between Kashiwanohacampus Station and the Kashiwa campus of the University of Tokyo, carrying actual
passengers and making three round trips a day. The passengers are students, faculty andstaff, as well as people who have business at the Kashiwa campus. In addition to this, one
shuttle bus service is operated daily for trial rides, making a total of four round trip shuttle
bus services a day from Monday to Friday. In addition, extra test-rides are also operated
when there is a particular request.
The trial operation of automated driving bus in Kashiwa-no-ha as long-term demonstration
experiment has continued for more than three years and two months as of January 2023. It
is one of the longest running demonstration tests with passengers on board. No accidents
have reported with the automated driving system during the period of operation.

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XXVIIth World Road Congress2.3. Technologies used in automated driving bus
An automated driving bus converted from a small size bus was used at the beginning ofoperation in 2019. That fleet was replaced by the automated driving bus converted from a
conventional medium-sized bus in January 2021. Both vehicles are equipped with a driving
automation system that automates a part of driving tasks, enabling Level 2 automateddriving with a safety driver in the driver's seat. Specifically, the recognition module of theautomated driving system uses the various sensors shown in Table 4 to localize self-position
and recognize obstacles, while the decision-making module calculates how the vehicle
should be controlled based on the recognition information. Based on the calculation results,
the control module manipulates the steering wheel, accelerator/brake and blinker toimplement automated driving.

Table 4 - Various sensors on automated driving bus
Sensors equipped on automated driving bus
LiDAR (forward, rear, side×2)
Obstacle-detection camera
Signal recognition camera
Stereo camera
Millimeter-wave radar
Magnetic marker detection sensor
Gyro sensor
GNSS antennaCommunication antenna

Gradual improvement has been made to the driving automation system. The RTK-GPS andhigh-precision gyro sensors are used for localisation of self-position of automated drivingbus. However, when the roadside trees along the road are overgrown in summer and whenthe vehicle passes under some buildings, the accuracy of localization using RTK-GPS andhigh-precision gyro sensors alone is not sufficient. Therefore, magnetic markers are installed
in sections where accuracy is insufficient, and improvement of driving automation system
was made to the use of a magnetic positioning system in April 2020. Magnetic markers areused not as target trajectories but as landmarks for self-position estimation, and for research,development and verification purposes, magnetic markers are placed in a grid pattern insome sections in addition to the usual point sequence arrangement [6].
The base fleet upgrade to medium-sized buses in January 2021 included enhanced traffic
signal recognition cameras and object detection sensors on the side. In conjunction with this,other detection and driving functions were also improved. A display has also been added to
the vehicle. This display allows the passengers to see the image of automatic steering andthe sensing status during automated driving. Figure 2 shows the image of the display. In
addition, remote monitoring functions have been installed to detect passengers who stands
up or walking during bus running and to announce warnings based on recognition using
camera images to prevent passengers from falling over [7].
From 2022, initiatives on connection with traffic signals and with cameras and sensors of CITS roadside units on the route have also been started as described in section 4.

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XXVIIth World Road Congress(Photo: S.Suzuki)

Figure 2 - Image of a display installed in the automated driving bus
3. MANUAL OVERRIDE DURING AUTOMATED BUS OPERATION
3.1. Situations where manual overrides take place
When an automated driving bus is in operation, a safety driver belongs to a bus operator
company which is operating a route bus in the Kashiwa-no-ha area is in the driver's seat. In
case the situations cannot be managed by the automated driving system, the safety driver
manually overrides the automated driving system. In this operation at Kashiwa-no-ha, even
within the ODD, manual override is performed whenever the safety driver, based on his/herexperience, deems it necessary. Therefore, locations where manual override occurs are
considered to be where challenges can be identified for automated driving systems. The
authors analyzed the locations where manual override is performed and found that most of
manual overrides occur in the locations shown in Table 5.

Table 5 - Locations where manual overrides are frequently performed

3.2. Factors leading to manual overrides
There are three types of manual override: steering, accelerating and braking. The highest
number of manual overrides per round trip by type, recorded in the period January 2022 toSeptember 2022, was for accelerating, followed by steering and the lowest number ofmanual overrides for braking as shown in Figure 3.

[7]

XXVIIth World Road CongressFigure 3 – Comparison of three types of overrides per round trip [8]The reasons for the high number of manual overrides on accelerator operations may be dueto the following reasons. For example, when passing through an intersection, the drivercommunicates somehow with surrounding vehicles, cyclists and pedestrians and predicts
their behaviour based on experience. Then, after confirming and ensuring safety, the driver
promptly exits the intersection, also taking traffic smoothness into consideration. However,the driving automation system cannot communicate with surrounding vehicles, cyclists andpedestrians, and compared to the driver, the acceleration and deceleration control
performed while confirming and ensuring safety is more discreet on the safety side. Thismay cause a difference between the driver's decision making and the that of the driving
automation system, and the driver is likely to perform manual overrides in accelerator control
in many cases.
The authors also analyzed the surrounding road environment when manual override was
performed, using the images of the drive-recorders [8]. As a result, it was learned that inmany cases, manual overrides in braking occurred in front of the driving path, when apedestrian crossing takes place or a vehicle enters the path, by initiating deceleration inadvance. In these cases, manual overrides in braking control by the driver is considered tobe caused by a difference between the driver's experience-based behaviour prediction andthe decision making of the driving automation system.
4. INSTALLATIONS OF COOPERATIVE ITS
4.1. Outline of additional Cooperative ITS installations
As described in section 3., a number of manual overrides were performed at signalised andnon-signalised intersection in the Kashiwa-no-ha automated driving bus operation, andfurther improvements were required to achieve Level 4 driving automation. Therefore, under
the CooL4 project funded by METI, some roadside units (RSUs) were installed in a test fieldof the University of Tokyo's Kashiwa Campus and functional verification was carried out. In
addition, in 2022, RSUs equipped with sensors and communication devices were installedby parties of Kashiwa ITS Promotion Council for verification of functions to expand thephysical range within which automated driving bus can detect approaching vehicles and soon and to enable them to acquire signal information. Images of RSU are shown in Figure 4.
The locations of the RSUs are shown in Figure 1.

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XXVIIth World Road Congress(Photos: S.Suzuki)
Figure 4 - Images of RSU

Each RSU is equipped with LiDAR and/or cameras and has the capability to detectpedestrians, cyclists, running vehicles and parked vehicles and transmit this information to
the automated driving bus via a common communication device.
4.2. Cooperative ITS services for road users
Table 6 shows the outline of the C-ITS services provided to road users using introduced
RSUs.
At signalized intersections, signal information is transmitted to the automated driving bus via
communication equipment to improve the bus's decision-making on acceleration anddeceleration operations, thereby improving the accuracy of safety confirmation and realizing
efficient deceleration operations. In addition, sensors such as LiDAR, cameras andmillimetre-wave sensors are used to detect vehicles, cyclists and pedestrians inside andoutside intersections, and transmit this information to the automated driving bus, thereby
enhancing the automated driving bus's perception of traffic environment at intersections.
These technologies provide services that ensure efficient fuel consumption in an automateddriving bus and services that prevent passengers from falling over in the cabin. They also
provide safe driving assistance services that include surrounding road users by reducing the
likelihood of collisions between automated buses and pedestrians, cyclists and othervehicles.
RSUs installed beside pedestrian crossings at an unsignalized intersection detects
pedestrians and cyclists in the vicinity of the pedestrian crossing, including those in blind
spots from the approaching automated driving bus, and transmit information to theautomated driving bus to prevent sudden deceleration. RSUs installed at anotherunsignalized intersection at the exits of a narrow street detects running out vehicles andcyclists, and pedestrians crossing the road. And it provides information to the automateddriving bus to prevent sudden deceleration. RSUs installed in areas where there are manyparked vehicles can detect pedestrians and vehicles jumping out of blind spots caused byparked vehicles, as well as the departure of parked vehicles, and transmit the information to
the automated driving bus to prevent sudden deceleration. At bus stops, the system detects
vehicles approaching from behind when the automated driving bus starts and transmits theinformation to the automated bus, thereby improving safety when the bus starts from bus
stop.
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XXVIIth World Road Congress

These technologies also provide services that prevent passengers from falling over in thecabin and safe driving assistance services that include surrounding road users.
The idea is that these C-ITS services by RSUs will be provided not only to buses equippedwith automated driving systems, but also to vehicles equipped with C-ITS on-board units. In
other words, other road users are being considered to be able to enjoy the C-ITS services
using RSUs, mainly on safe driving assistance.
When introducing driving automation system utilizing Cooperative ITS RSUs, after checking
and verifying the functions and communications, the safety driver of the automated driving
bus is given the experience they need to get used to the improved system behaviour using
additional Cooperative ITS’s information. This is because, when implementing Level 2
automated driving, the driver needs to be fully aware of the tendency of decisions andbehavior of the automated driving system, for making appropriate manual overrides toensure safety. As of December 2022, the verification of the transmission of signal
information and of its reflection to the automated driving system has been completed. And
safety drivers’ familiarization experience of improved system is in the process of being
implemented. For other Cooperative ITS RSUs, the functional and communication
verification stage is still in the process, and safety driver familiarization experience will be
conducted as soon as it is completed.

Table 6 - Outline of the installed C-ITS services using RSUs
Type
Signal information provision

Right and left turn support

On-street parking avoidance
supportPedestrian detection support at
unsignalized pedestrian crossing
Support for detection of runningout vehicle from side street

Function
Signal information is provided from RSU to automated driving bus inorder to enable correct recognition of the current status and remaining
signal time without the influence of the dazzling sunset or street trees
To prevent interference with oncoming straight vehicles when turning
right and with crossing pedestrians and cyclists when turning right/left,
vehicles, pedestrians and cyclists are detected by RSU and right/leftturn assistance information or object information is provided to theautomated bus
For on-street parking avoidance support, the RSU detects on-street
parked vehicles and oncoming vehicles and provides information on onstreet parking avoidance suport and object information to the automateddriving bus
To prevent interference with pedestrians and cyclists at unsignalized
pedestrian crossings, pedestrians and cyclists are detected by RSU
and information on pedestrian crossing detection support and/or object
information is provided to the automated driving bus
To prevent interference with vehicles runnig out of the side street, theRSU detects the vehicles and provides object information to theautomated driving bus

5. CONCLUSIONFirstly, this paper provides an overview of the research and development of automateddriving technology in Japan and the efforts made towards its social implementation. In Japan,
research, development and social implementation in the cooperative field, such as
development of high-precision 3D maps and automated driving evaluation environment incyberspace were promoted through cooperation between industry, government andacademia in accordance with the roadmap set by the Government of Japan. In addition,[10]

XXVIIth World Road Congresslegal systems were developed to enable social implementation of SAE driving automationlevel 3 and level 4.
Secondly, the long-term operation experiment of a Level 2 automated driving bus, which has
been continuously conducted in the Kashiwa-no-ha area for more than three years, wasdescribed. This long-term operation has been realized with contributions from a diverse
range of participants, not only to carry out technical verification, but also to verify sustainable
operation and social implementation. It was also reported that improvements are being
made to the driving automation system sequentially in order to resolve issues learned in thecourse of continued operation. Specifically, it is described that introduction of a magnetic
positioning system, improvements to the operation automation system in conjunction withvehicle renewal, and the introduction of Cooperative ITS.
Future challenges include the verification of the use of the Cooperative ITS in the driving
automation system, which has been installed and verified since 2022, in actual operations.
Besides, the improvement of automated driving technology, the establishment of an
operation implementation framework and the evaluation of the impact of automated bus
driving on surrounding traffic environment in order to meet the Permission Criteria forobtaining a permit of Specified Automated Operation with a view to realizing Level 4
automated mobility service within fiscal year 2025.

ACKNOWLEDGEMENT
The authors would like to thank the member of the Kashiwa ITS Promotion Council who
provided invaluable assistance in the long-term experiment of automated driving bus
operation Kashiwa-no-ha, and in the survey and analysis of the results.

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2. Strategic Headquarters for the Promotion of an Advanced Information and Communications Network
Society・Strategic Council for the Promotion of Data Use in the Public and Private Sectors(2021). PublicPrivate ITS Initiative/Roadmaps -Past efforts and basic ideas for the future of the ITS Initiative-.
https://cio.go.jp/sites/default/files/uploads/documents/its_roadmap_20210615.pdf. pp 2-4
3. Cabinet Office(2022).Commercialisation of simulation software for safety assessment using the results of
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4. Hisaaki Ikeuchi (National Police Agency) (2023). The Act for Partial Amendment of the Road Traffic Act,SIP 2nd Phase: Automated Driving for Universal Services - Final Results Report (2018-2022), pp 285-287
5. The University of Tokyo et al.(2022). The FY2021 report of the Project on Research, Development,
Demonstration and Deployment (RDD&D) of Autonomous Driving toward the Level 4 and its Enhanced
Mobility Services (Theme 4), https://www.meti.go.jp/meti_lib/report/2021FY/000305.pdf
6. K. Ishii et al.(2022). Autonomous Vehicle Localization Using Magnetic Markers Placed in Grid-LikePatterns. Transactions of the Society of Automotive Engineers of Japan. Vol 53, No.5, pp 1003-1009
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04/KNH_JidouBus_Panf_HD.pdf
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XXVIIth World Road Congress