Explanation of terms■Description of driving automation Levels

Level 1The system continuously performs subtasks of vehicle motion control,
either longitudinally or laterally in the dynamic driving task, at a particular ODD.

Level 2The system continuously performs both longitudinal andlateral vehicle motion control subtasks of the dynamic driving task, at a particular ODD.

Level 3The system continuously performs all dynamic driving tasks at a particular ODD.
Users are expected to accept and respond appropriately to requests for intervention
issued by the system.

Level 4The system continuously performs all dynamic driving tasks andresponses to cases where it is diﬃcult to continue operation, at a particular ODD.

Level 5The system performs continuously all dynamic driving tasks andresponses to diﬃcult operation continuity cases without limitation(i.e. not only at a particular ODD).

■ Kashiwa ITS Promotion Council（Chairman: Prof. Yoshihiro Suda, Institute of Industrial Science,
The University of Tokyo）
The purpose of this project is to promote various research and development activities and to conduct activities
that contribute to the social implementation of ITS in Kashiwa City, as well as to realize a"low-carbon
transportation city" and "next-generation environmental city" by its use.
It was established in December 2009 as a platform for cooperation and coordination among administrative
agencies, private companies, various groups, and individuals, and The University of Tokyo.

Implementing body : Kashiwa ITS Promotion Council
Participating organizations : The following 16 organizations● Mobility Innovation Collaborative Research Organization, The University of Tokyo

Long-term operation experiment of a automateddriving bus on public roads between Kashiwanoha
Campus Station and the University of Tokyo,
Kashiwa Campus.
■ Purpose of the experiment
As technology development related to automated driving progresses, many short-term demonstration experiments
are being conducted, but there are few that are conducting veriﬁcations of operations, inspections, and maintenancefor practical commercial operation over a long period of time.
The purpose of this long-term operation experiment is to understand operation issues and verify countermeasures when
operating the automated driving bus.
The automated driving bus operates on a 2.6km section that consists of approximately 2.3km of public roads and 0.3kmof roads in the University of Tokyo, Kashiwa Campus.
The vehicle is licensed for commercial transportation equipped with an automatic driving system developed by
Advanced Smart Mobility Co., Ltd., and operated by Tobu Bus Central Co., Ltd.
The level of driving automation for this bus is Level 2 and the system performs subtasks of vehicle motion control in both
longitudinal and lateral directions under the deﬁned ODD.
This experiment is a part of the smart city model project,“Kashiwanoha Smart City Consortium”and anAdvanced Model Project selected by the Ministry of Land, Infrastructure, Transport and Tourism.
The results of the experiment will be used to evaluate driving performance and safety performance for operation with Level 4
or higher automated driving. Development of a new automated bus vehicle based on the veriﬁcation results is also envisioned.
Therefore, even after this veriﬁcation experiment is completed, we plan to introduce a new vehicle and continue the operation of
the veriﬁcation experiment.
In the future, we will aim to create safe, comfortable, and convenient services for residents in collaboration with
Kashiwanoha urban developments.

■ Routes & Vehicles●The City of Kashiwa●Advanced Smart Mobility Co., Ltd.

●Tobu Bus Central Co., Ltd.

●Mitsui Fudosan Co., Ltd.

●BOLDLY Inc.

●Sompo Japan Insurance Inc.

●Mitsubishi Auto Leasing Corporation●Aichi Steel Corporation●IHI Corporation●Koito Electric Industries, Ltd.

●Kashiwanoha Urban Design Center（ＵＤＣＫ）●Paciﬁc Consultants Co., Ltd.

● Nippon Signal Co., Ltd.

■ Regarding the automated bus and its operationInquiries

The secretariat of Mobility Innovation Collaborative ResearchOrganization, The University of Tokyo℡:04-7136-6960 E-mail:utmobi-sec@its.iis.u-tokyo.ac.jp■ Regarding the experiment in general

The secretariat of Kashiwa ITS Promotion Council（Kashiwa City Civil Engineering Department Transportation Policy Division）℡:04-7167-1219

E-mail：kotsuseisaku@city.kashiwa.chiba.jp

Regarding
Test-ride■ Only participants of the Kashiwanoha Smart City
Tour [Gate Square Course] at the Kashiwanoha
Urban Design Center (UDCK) can use the test-ride
operation.
■ If you are interested, please check the details
at the following site.

https://www.kashiwanoha-smartcity.com/tour/pc/Dates

University of Tokyo
Kashiwa Campus
National Cancer Center
Hospital East

Kashiwanoha Park

● Institute of Industrial Science, The University of Tokyo●Graduate School of Frontier Science, The University of Tokyo■ Overview of the experimentKashiwanohaCampus Station©N T T イ ン フ ラ ネッ ト

Operation route：November 1, 2019 to March 31, 2024
5

Operating Hours ：Between 11:00am-3:00pm(3 shuttle operations and 1 operation for test-rideon every week day)

Route：Tsukuba Express Kashiwanoha Campus Station～
University of Tokyo, Kashiwa Campus

Distance：Approximately 2.6km

Vehicle Info：Isuzu Motors ELGAMIO, with automated driving
system（Licensed for commercial transportation）（Public roads：2.3km、Campus area：0.3km）

Passenger Capacity ：28 persons (seated)※ Bus will not operate if passenger capacity is exceeded.
Drivingautomation level：Level２

Eligiblepassengers：Students, staﬀs, and visitors of
the University of Tokyo Kashiwa Campus※participants of the Kashiwanoha Smart City Tour
[Gate Square Course] held at the Kashiwanoha Urban Design Center(UDCK)
can use the test-ride operation.
※To apply for a test-ride on the automated driving bus, please contact
the following website.
https://www.kashiwanoha-smartcity.com/tour/pc/

Technical characteristics of automated driving bus
Driving automation system

Automated control items

The automated bus in operation is equipped with a driving automation system that combines several
advanced sensors and control technologies to achieve automated driving.

● Localization of self-position using RTK-GPS + magnetic positioning system + high-precision gyro sensors

The recognition part of the driving automation system uses GPS, magnetic sensors, gyro sensors, etc.
to recognize the position of the vehicle, and recognizes the surrounding environment with obstacle sensors.

● Arrival/departure function at bus stop

Based on the recognition information, the judgment section calculates how the vehicle should move.

Using the judgment information, the control unit electrically or electronically maneuvers the steering wheel(steering wheel), accelerator/brake, and blinkers to enable automated driving.

● Collision avoidance control with obstacle recognition and lane change or automated braking

Start● In environments where GPS reception is
insuﬃcient, the system use magnetic markers
embedded in the road for localization.

Lane keeping controls● Steering control using target trajectory● Localization of self-position (RTK-GPS)Pause

In this way, we are fully utilizing cutting-edge and existing technologies and functions to enhance control andsafety performance, but it is not yet perfect.
We will continue to develop and aim to realize more advanced automated driving bus operations in the future.
● Forward LiDAR● Obstacle detection camera● Signal color recognition camera

Speed control● GNSS antenna● Speed control within the speed limit ／ following the car in front (ACC function)

Goal● Stopping/starting at particular points (Driver judgment: button operation)● Rear LiDAR●Communicationantenna

Obstacle recognition function● Obstacle recognition function (vehicle ahead) with improved detection stability by combining deep learning(AI technology) using camera images, LiDAR (laser radar), and millimeter-wave radar sensing technology.

● Stereo camera● Function to determine whether obstacles are located inside or outside the lane using the concept of a digital map.

Object detection by LiDAR

Recognition using Deep Learning

In/out-side-lane judgment● Lateral LiDAR● Magnetic marker sensor● Gyro sensor● Millimeterwave radar

Recognition(sensors)

Judgment+Outsidethe lane

Control

In the lane

Localization

RTK-GPS

Accelerator

Magnetic sensor
IMU（Gyro sensor）
Obstacle recognition

LiDAR（Laser radar）
Millimeter wave radar
Deep Learning（Camera）
Stereo camera

Driving
automation
systemBrake
Steering
Blinker

Fleet management platform for automated driving bus operation : DISPATCHER■ Built-in functions that can be remotely managed● Driving record function● Condition monitoring function● Error recording function● Emergency response function● Driving instruction function ● Driving feasibility judgment function