Recent International Activity in 

Cooperative Vehicle–Highway 

Automation Systems

The Exploratory Advanced Research Program
This report has been prepared with the support of the Federal Highway Administration’s (FHWA’s) 

Exploratory Advanced Research Program under the technical supervision of the FHWA Turner–

Fairbank Highway Research Program’s Office of Operations Research and Development. This work 

was initiated to provide the U.S. transportation research community with a better understanding of 

the current state of research and development and to encourage broader thinking about cooperative 

vehicle–highway automation systems based on developments in other countries. This topic has 

received increased attention in the industrialized world, even while interest in the United States has 

been at a relatively low level in recent years. It is now time that the United States take a fresh look at 

the technical and institutional issues associated with vehicle automation and its implications for the 

future of the surface transportation system, particularly when interest in the topic has been growing 

within the automotive and information technology industries.

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for the use of 

the information contained in this document. The U.S. Government does not endorse products or 

manufacturers. Trademarks or manufacturers’ names appear in this report only because they are 

considered essential to the objective of the document. 

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high quality information to serve Government, 

industry, and the public in a manner that promotes public understanding. Standards and policies are 

used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA 

periodically reviews quality issues and adjusts its programs and processes to ensure continuous 

quality improvement.

Joseph I. Peters

Director, Office of Operations Research

and Development

Debra S. Elston

Director, Office of Corporate Research, 

Technology, and Innovation Management 

Foreword
i
ii

Technical Report Documentation Page 

1. Report No.

FHWA-HRT-12-033

2. Government Accession No. 3. Recipient’s Catalog No.

4. Title and Subtitle

Recent International Activity in Cooperative Vehicle–Highway 

Automation Systems 

5. Report Date

December 2012

6. Performing Organization Code: 

7. Author(s)

S.E. Shladover

8. Performing Organization Report No. 

9. Performing Organization Name and Address

University of California PATH Program

1357 S.46th Street, Bldg. 452

Richmond, CA 94804-4648

Cambridge Systematics, Inc.

100 Cambridge Park Drive, Suite 400

Cambridge, MA 02140-2322

10. Work Unit No.

11. Contract or Grant No.

Contract DTFH61-06-D-00004, Task Order CA04-070

12. Sponsoring Agency Name and Address

Office of Corporate Research, Technology, and Innovation 

Management

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report, January 2011 – December 2012

14. Sponsoring Agency Code

HRTM-30

15. Supplementary Notes

FHWA’s Contracting Officer’s Task Manager (COTM): Robert Ferlis, HRDO-2

16. Abstract

This report summarizes the current state of the art in cooperative vehicle–highway automation systems in Europe and Asia 

based on a series of meetings, demonstrations, and site visits, combined with the results of literature review. This review covers 

systems that provide drivers with a range of automation capabilities, from driver assistance to fully automated driving, with an 

emphasis on cooperative systems that involve active exchanges of information between the vehicles and the roadside and 

among separate vehicles. The trends in development and deployment of these systems are examined by country, and the 

similarities and differences relative to the U.S. situation are noted, leading toward recommendations for future U.S. action.

The Literature Review on Recent International Activity in Cooperative Vehicle-Highway Automation Systems is published 

separately as FHWA-HRT-13-025. 

17. Key Words

Automated Vehicles, Autonomous Systems, 

Autonomous Vehicles, Cooperative Automation 

Systems, Intelligent Transportation Systems, Personal 

Rapid Transit Vehicles, Public Transport Systems, 

Vehicle Automation Systems, Vehicle-to Infrastructure 

Cooperation, Vehicle-to-Vehicle Communications.

18. Distribution Statement

No restrictions. This document is available to the public through the 

National Technical Information Service, Springfield, VA 22161.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

81

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
iii
iv

SI* (MODERN METRIC) CONVERSION FACTORS

APPROXIMATE CONVERSIONS TO SI UNITS

SYMBOL WHEN YOU KNOW MULTIPLY BY TO FIND SYMBOL

LENGTH

in inches 25.4 millimeters mm

ft feet 0.305 meters m

yd yards 0.914 meters m

mi miles 1.61 kilometers km

AREA

in2 square inches 645.2 square millimeters mm2

ft2 square feet 0.093 square meters m2

yd2 square yard 0.836 square meters m2

ac acres 0.405 hectares ha

mi2 square miles 2.59 square kilometers km2

VOLUME

fl oz fluid ounces 29.57 milliliters mL

gal gallons 3.785 liters L

ft3 cubic feet 0.028 cubic meters m3

yd3 cubic yards 0.765 cubic meters m3

NOTE: volumes greater than 1000 L shall be shown in m3

MASS oz ounces 28.35 grams g

lb pounds 0.454 kilograms kg

T short tons (2000 lb) 0.907 megagrams (or "metric ton") Mg (or "t")

TEMPERATURE (exact degrees) o

F Fahrenheit 5 (F-32)/9 Celsius oC

or (F-32)/1.8

ILLUMINATION

fc foot-candles 10.76 lux lx

fl foot-Lamberts 3.426 candela/m2 cd/m2

FORCE and PRESSURE or STRESS

lbf poundforce 4.45 newtons N

lbf/in2 poundforce per square inch 6.89 kilopascals kPa

APPROXIMATE CONVERSIONS FROM SI UNITS

SYMBOL WHEN YOU KNOW MULTIPLY BY TO FIND SYMBOL

LENGTH mm millimeters 0.039 inches in

m meters 3.28 feet ft

m meters 1.09 yards yd

km kilometers 0.621 miles mi

AREA mm2 square millimeters 0.0016 square inches in2

m2 square meters 10.764 square feet ft2

m2 square meters 1.195 square yards yd2

ha hectares 2.47 acres ac

km2 square kilometers 0.386 square miles mi2

VOLUME

mL milliliters 0.034 fluid ounces fl oz

L liters 0.264 gallons gal

m3 cubic meters 35.314 cubic feet ft3

m3 cubic meters 1.307 cubic yards yd3

MASS

g grams 0.035 ounces oz

kg kilograms 2.202 pounds lb

Mg (or "t") megagrams (or "metric ton") 1.103 short tons (2000 lb) T

TEMPERATURE (exact degrees) o

C Celsius 1.8C+32 Fahrenheit oF

ILLUMINATION

lx lux 0.0929 foot-candles fc

cd/m2 candela/m2 0.2919 foot-Lamberts fl

FORCE and PRESSURE or STRESS

N newtons 0.225 poundforce lbf

kPa kilopascals 0.145 poundforce per square inch lbf/in2

*SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380.

(Revised March 2003)
v

Table of Contents

Introduction 1

Europe 2

Germany 2

The Netherlands 2

France 2

Japan 2

Background 3

Japan 5

Germany 6

France 6

Parallel Historical Activities in the United States 7

Institutional and Political Environment for Cooperative Vehicle–Highway Automation 9

Europe in General and European Commission Activities 10

 National Activities in Europe 12

 France 12

 Germany 13

 The Netherlands 14

 Spain 14

 Other European Countries 14

Japan 15

Korea 16

China 16

Summary of Key Factors Overseas 16

Current European Projects in Cooperative Vehicle–Highway Automation 18

SARTRE 20

HAVEit 22

 Volkswagen’s Temporary AutoPilot 27

 Automated Queue Assistance (AQuA) 27

 Automated Assistance in Roadworks and Congestion 28
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CityMobil 30

 CityMobil La Rochelle Cyber Car Demonstration (May 2011) 30

 CityMobil La Rochelle Conference (May 2011) 33

2010 SMART-64 38

Dutch Programs 44

 Strategic Platform for Intelligent Transport Systems 44

 Advisory Acceleration Control Field Test 44

 Dutch Integrated Testsite for Cooperative Mobility 45

 Connected Cruise Control 45

 Connect and Drive 45

 Grand Cooperative Driving Challenge 46

 Shock Wave Mitigation with Mixed Equipped and Unequipped Vehicles 46

French Programs 49

German Programs 50

 KONVOI Project 50

 German Study on Legal Aspects of Road Transport Automation 54

Private Automotive Industry Activities 57

European Commission Workshop on Automation in Road Transport 57

Current Asian Activities in Cooperative Vehicle–Highway Automation 62

Japan’s Energy ITS Project 63

Toyota’s Platooning Development Work 69

Comparison with Current U.S. Status 71

U.S. Activities 72

Similarities and Differences Between Overseas and U.S. Situations 72

 Similarities 73

 Differences 73

Implications of These Contrasts for Future U.S. Actions 74

References 77
vii

List of Figures

Figure 1. Diagram. SARTRE operating concept. 20

Figure 2. Photo. SARTRE demonstration of three automated cars and one automated truck following 

the lead truck in a platoon (May 2012). 21

Figure 3. Photo. Reading a newspaper while being driven automatically in the platoon behind the lead

truck (December 2010). 21

Figure 4. Diagram. SARTRE vehicle-maneuvering use cases. NOTE: FV = following vehicle,

LV = lead vehicle, PFV/PLV = potential following vehicle/potential lead vehicle, OV = other vehicle

(not part of the platoon). 22

Figure 5. Diagram. Basic philosophy of multiple levels of driving automation in HAVEit. 23

Figure 6. Diagram. Multiple automation levels through one driver–vehicle interface. 24

Figure 7. Photo. Example of a human–machine interface, showing different control mode choices. 25

Figure 8. Diagram. Complexity of HAVEit implementation. 25

Figure 9. Diagram. HAVEit concept of driver monitoring to ensure driver engagement, from

Continental Automotive France. 26

Figure 10. Photo. Volkswagen’s Temporary Autopilot display, showing three levels of automation

choices in lower right corner. 27

Figure 11. Photo. Steering wheel controls for Volvo Automated Queue Assistance (AQuA) for heavy trucks. 27

Figure 12. Photo. Automated Queue Assistance (AQuA) driver interface for heavy trucks. 28

Figure 13. Photo. Automated Queue Assistance system demonstrationfor low–speed automation in a truck. 28

Figure 14. Photo. An Automated Roadworks Assistant vehicle follows a lead vehicle between pylons

and maintains separation from a truck. 29

Figure 15. Photo. Roadworks Assistant driver–vehicle interface, showing three levels of automation

on left side of screen. 29

Figure 16. Photo. La Rochelle CyberCar demonstration site features a park sidewalk shared with pedestrians. 31

Figure 17. Photo. A CyberCar at the station in La Rochelle, France, with an attendant who is required

for passenger loading and unloading during the demonstration. 32

Figure 18. Photo. Rome Exhibition Center vehicle. 33

Figure 19. Photo. Soft bumper of the Rome Exhibition Center vehicle. 34

Figure 20. Photo. ULTra Personal Rapid Transit (PRT) track at Heathrow Airport. 34

Figure 21. Photo. ULTra Personal Rapid Transit (PRT) vehicles and station at Heathrow Airport. 35

Figure 22. Chart. Automation concepts considered in the SMART-64 project. NOTE: CACC = cooperative

adaptive cruise control. 39

Figure 23. Chart. Automation applications and their deployment timescales assumed in SMART-64 project. 40
viii

Figure 24. Photo. Distance–versus–time plot comparing a stream of 48 Advisory Acceleration Control

vehicles (right photo) with 48 unequipped vehicles (left photo). 45

Figure 25. Photo. Cooperative adaptive cruise control platoon of Toyota Prius vehicles developed as

part of the Connect and Drive Project. 45

Figure 26. Photo. Touch-screen control panel for adjusting parameters of a cooperative adaptive cruise

control (CACC) test. Note: RSU = roadside units, CC = cruise control, ACC = adaptive cruise control. 46

Figure 27. Diagram. Urban scenario of the Grand Cooperative Driving Challenge. 47

Figure 28. Diagram. Highway scenario of the Grand Cooperative Driving Challenge. 47

Figure 29. Photo. Aerial view of A270 test site with vehicle locations superimposed. 48

Figure 30. Photo. Real–time plots of distance-versus-time diagrams during an attempt to mitigate

congestion shock waves. 48

Figure 31. Chart. Relevant current projects at France’s LIVIC laboratory. NOTE: ABV = Automatisation

Basse Vitesse. 49

Figure 32. Photo. Four–truck KONVOI platoon driving at 10-m (33-ft) gaps between trucks on a

German autobahn. 52

Figure 33. Chart. BASt definitions of levels of automation. 55

Figure 34. Chart. BASt mapping of automation levels into operating speeds for safety. NOTE: Assist = assistance,

ACC = adaptive cruise control. 56

Figure 35. Diagram. Venn diagram of automation safety benefits and non-benefits, inspired by the BASt

study. Existing crashes that cannot be avoided by automation are represented by the blue circle, new

crashes created by automation are represented by the red circle, and existing crashes that could be

avoided by use of automation are represented by the overlap areas. 56

Figure 36. Presentation slide. Energy ITS truck platoon definition of capabilities. NOTE: V2V = vehicle-to-vehicle 

communication, ACC = adaptive cruise control, CACC = cooperative adaptive cruise control. 64

Figure 37. Diagram. Automation equipment installed on Energy ITS trucks. NOTE: GPS = global positioning 

system, IMU = inertial measurement unit, V2V = vehicle-to-vehicle communication, 

HMI = human–machine interface 65

Figure 38. Presentation slide. Performance requirements for Energy ITS truck platoon system. 66

Figure 39. Diagram. Maneuver scenarios for Energy ITS project truck platoon. NOTE: 80 km/h = 50 mi/h. 66

Figure 40. Presentation slide. First predictions of aerodynamic drag effects of Energy ITS project truck

platooning, compared with experimental results on full–scale trucks. NOTE: 80 km/h = 50 mi/h, 

4 m–12 m = 13 ft–40 ft, Cd = drag coefficient, Cp = pressure coefficient. 67

Figure 41. Photo. In-vehicle display screen of a following truck in the Energy ITS platoon. 68

Figure 42. Photo. Rear view of Energy ITS truck with three information displays. NOTE: LED = light–emitting diode. 69
ix

List of Abbreviations

AAC Advisory acceleration control

ACC Adaptive cruise control

ADAS Advanced driver assistance system

AHSRA Advanced Cruise–Assist Highway Systems Research Association

AIST Agency for Industrial Science and Technology

BASt Bundesanstalt für Strassenwesen (Federal Highway Research Institute in Germany)

BMBF Bundesministerium für Bildung und Forschung (Federal Ministry of Education and 

Research in Germany)

BMFT Bundesministerium für Forschung und Technologie (Federal Ministry of Research and 

Technology in Germany)

CACC Cooperative adaptive cruise control

CHAUFFEUR European Commission–funded truck–platooning research project

CVHAS Cooperative vehicle–highway automation systems

CVS Computer–controlled vehicle system

DARPA Defense Advanced Research Projects Agency

DG Directorate General within the European Commission

DG-CONNECT Directorate General for Communications Networks, Content and Technology

DG-ENTR Directorate General for Enterprise and Industry

DG-INFSO Directorate General for Information Society and Media (obsolete)

DG-MOVE Directorate General for Mobility and Transport

DG-RTD Directorate General for Research and Innovation

DLR Deutschen Zentrum für Luft– und Raumfahrt (German Aerospace Center)

DriveC2X European project on communication between cars and other cars/infrastructure/

nomadic devices

DSRC Dedicated short–range communication 

DVI Driver–vehicle interface

EC European Commission 

EU European Union

GM General Motors

GPS Global positioning system

HAVEit Highly Automated Vehicles for Intelligent Transport

HIDO Highway Industry Development Organization

HMI Human–machine interface
x

I2V Infrastructure–to–vehicle

ICT Information and Communication Technology

IFSTTAR Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux 

(French Institute of Science and Technology for Transportation, Development and Networks)

IMTS Intelligent Multimode Transit System

INRETS Institut National de Recherche sur les Transports et leurs Sécurité (National Institute for Research on 

Transportation Systems and Their Safety in France)

INRIA Institut National de Recherche en Informatique et Automatique (National Institute for Research in 

Computer Science and Control in France)

ITS Intelligent transportation systems

LCPC Laboratoire Centrale des Ponts et Chaussées (Central laboratory of bridges and roads in France)

LIVIC Laboratoire sur les Interactions Véhicule-Infrastructure- Conducteur (Laboratory on the interactions 

among vehicles, infrastructure, and drivers in France)

METI Ministry of Economy, Trade and Industry 

MITI Ministry of International Trade and Industry (obsolete)

MLIT Ministry of Land, Infrastructure and Transport

NAHSC National Automated Highway Systems Consortium

NPA National Police Agency

NSF National Science Foundation

OEM Original equipment manufacturer

PARTAGE French project on driver assistance systems

PATH Partners for Advanced Transit and Highways

PROMETHEUS PROgraMme for European Traffic with Highest Efficiency and Unprecedented Safety

PRT Personal rapid transit

PSA French auto manufacturer (maker of Peugeot and Citroën)

RCA Radio Corporation of America

RWTH Rheinisch–Westfälische Technische Hochschule (Rhine–Westfalian Technical University in Aachen, 

Germany)

SARTRE SAfe Road TRains for the Environment

SCORE@F Système COopératif Routier Expérimental Français (French Experimental Cooperative Road System 

field operational test)

SPITS Strategic Platform for Intelligent Traffic Systems

TMC Transportation management center

TNO Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek (Netherlands 

Organization for Applied Scientific Research)

TRL Technology readiness level

V2I Vehicle–to–infrastructure

V2V Vehicle–to–vehicle

VITA II VIsion Technology Application (second generation test vehicle in PROMETHEUS by Daimler–Benz)
xi
» The primary motivation for this work, as 

with intelligent transportation systems 

(ITS) in general, is to improve the energy 

efficiency of road transportation to help 

countries meet their Kyoto targets for 

reducing carbon dioxide (CO2) emissions.

» Most of the development work is 

supported by public agencies with primary 

missions in technology development and 

economic competitiveness rather than in 

transportation. This means that Japan and 

Europe see significant export potential 

in automation technologies, rather than 

viewing these technologies solely in terms 

of domestic road transport applications.

» In Europe, there are significantly different 

perspectives between the organizations 

that approach CVHAS as automotive 

products and those that approach it as a 

means of improving public transportation. 

The former tend to emphasize partial 

automation systems operating in mixed 

traffic, whereas the latter tend to 

emphasize fully automated (driverless) 

vehicles in dedicated rights of way.

» Truck platooning and light passenger 

vehicle platooning have become popular 

Introduction

applications for study and development. 

The former are very much a highway 

application, whereas the latter could be 

either highway–oriented or applied to 

low-speed urban vehicles (e.g., shuttling 

empty shared vehicles to where they are 

most needed).

» Automobiles and trucks currently on 

the market in Japan and Europe tend 

to be better equipped with advanced 

technologies than are the vehicles in 

the United States, and indeed most of 

the well-equipped vehicles in the U.S. 

market are imported from Japan or 

Europe. The sensors used for collision 

warning and avoidance systems and the 

electronic actuation systems used for 

electric and hybrid vehicles are important 

enabling technologies for the automation 

systems; thus, the automation system 

developers are trying to build on the use 

of the components and subsystems that 

are already in series production. The 

relative roles of the automotive original 

equipment manufacturers (OEMs) 

and their first–tier system suppliers in 

developing components and subsystems 

are sometimes difficult to discern, but 

During the past decade, the level of activity in cooperative vehicle–highway 

automation systems (CVHAS) has increased significantly in Japan and Europe, 

whereas it has remained at a relatively low level in the United States. This research 

project was initiated to create a summary of the current state of CVHAS development 

and thinking about these systems in other countries and to help inform decisions about 

future related activities in the United States. This review has identified the following salient 

points associated with international activities:

1
in general, the automotive industry is 

becoming more internationalized, with 

less variation from region to region as 

both OEMs and major suppliers become 

truly global corporations.

The following section addresses the current 

CVHAS highlights by region.

Europe

Two different Directorates General (DGs) of 

the European Commission (EC) are currently 

sponsoring the primary automation projects 

in Europe. Their approaches are quite 

different, but they held a joint workshop 

in October 2011 to review current progress 

and to define the needs for future work with 

the hope that such automation projects 

can be better coordinated. DG-CONNECT 

(Communications Networks, Content and 

Technology, formerly DG-INFSO (Information 

Society and Media)) is tightly coupled to 

the automobile industry; thus, their current 

projects (i.e., HAVEit and SMART-64) have 

emphasized partial automation systems 

that operate in mixed traffic, building on the 

sensor technologies that are already being 

used for collision warning and adaptive cruise 

control (ACC) systems. DG-RTD (Research 

and Innovation) is more multi-modal in 

perspective, and its current projects, 

CityMobil and SARTRE (SAfe Road TRains 

for the Environment), have emphasized 

urban transit and trucking applications. 

CityMobil in particular has considered how 

to separate automated vehicles from other 

traffic (including vulnerable road users) to 

ensure safety.

Germany

Germany sponsored the KONVOI project to 

investigate the benefits and deployment issues associated with truck platooning, with 

truck platoons assumed to be operating in 

mixed traffic on autobahns. More recently, 

Germany has been studying the legal aspects 

of vehicle automation systems to determine 

what legal changes may be needed and how 

these relate to different levels of vehicle automation (which they defined very carefully 

and precisely).

The Netherlands

The Netherlands has emphasized cooperative 

system applications in their national programs, 

with work on cooperative ACC (CACC) and 

precursor systems that seek to smooth 

out traffic dynamics by advising drivers 

when to accelerate and decelerate. The 

Netherlands has invested heavily in a testbed 

environment on a 5-km (3-mi) section of road 

between Eindhoven and Helmond, where 

they have already held several high–profile 

demonstrations and which they are offering 

as a general European testbed.

France

The automation work in France has been 

concentrated in its research institutes, which 

have a substantial heritage of relevant work 

on both enabling technologies and systems. 

France is studying partial automation 

systems, as well as systems for shuttling 

vehicles among nearby sites at low speeds 

and without drivers.

Japan

Japan has one of the most ambitious 

automation projects, with the Energy ITS 

Project of its Ministry of Economy, Trade and 

Industry developing and testing an automated 

platoon of three heavy trucks designed to 

operate at short enough gaps to produce 

significant savings in aerodynamic drag. In 

addition, the Japanese automotive OEMs are 

experimenting with ACC system interactions 

and exploring CACC to smooth out traffic 

disturbances and also to save energy and 

CO2 emissions.

2
3

Background
4

This report covers current international 

activities for developing, testing, 

and deploying CVHAS, augmenting 

the literature review that was prepared 

separately for this project. The focus of this 

report is on activities outside of the United 

States, because U.S. CVHAS activities are 

already familiar. In this report, there will be 

occasional references to activities in the 

United States to help set the context for the 

overseas activities and to offer points of 

comparison. Cooperative vehicle–highway 

automation means that the systems 

involve some form of vehicle–to–vehicle 

(V2V), vehicle–to–infrastructure (V2I), or 

infrastructure–to–vehicle (I2V) cooperation 

(and/or interactions with the driver in 

partially automated systems), but this 

report generally avoids addressing the fully 

autonomous systems that do not involve 

active cooperation. The term automation

covers multiple degrees of automation of 

the driving function, ranging from driver 

warning and control assistance to partial 

automation and full automation. 

The dominant international activities in 

CVHAS, as indeed in all of ITS, are sponsored 

by the Japanese government and the EC. 

Although they have the largest budgets and 

are most inclined to publicize their work in 

international technical forums, they are not 

the only sponsors active in this research 

area. There are also substantial national 

programs of research and development 

(R&D) in individual European countries and 

in other Asian countries, particularly Korea 

and China. 

There has been considerable heritage of 

prior work on cooperative automation 

systems in several countries, although none 

has previously had as much activity as 

the United States; however, several of the 

current international automation activities 

are substantially larger and more ambitious 

than any current U.S. activities.
5

Japan has the most extensive heritage of 

relevant prior work. The pioneering work 

on vehicle automation by Dr. Sadayuki 

Tsugawa, working for the Ministry of 

International Trade and Industry beginning 

in the 1970s, was based on autonomous 

vehicle concepts.(1) The same ministry, 

however, also supported the development 

of one of the earliest and most ambitious 

automated personal rapid transit (PRT) 

system concepts—the Computer–Controlled 

Vehicle System (CVS)—in the 1970s.(2) This 

included special-purpose passenger and 

freight vehicles captive to a guideway, as 

well as “dual mode” vehicles that could 

operate automatically on the guideway 

and manually on normal roads. CVS had 

an extensive test track, with multiple 

test vehicles, and performed elaborate 

simulation studies of how large networks 

of automated vehicles would operate, but it 

never advanced beyond the test track stage.

When the ITS program became active 

throughout the world, Japan was one of 

the most ambitious participants. As soon 

as the United States formed the National 

Automated Highway Systems Consortium 

(NAHSC) in 1994, Japan’s Minister of Land, 

Infrastructure and Transport visited to 

learn more about it and immediately formed 

a counterpart government–industry, public–

private partnership organization in Japan, 

known as AHSRA. In the first few years, 

AHSRA concentrated on fully automated 

vehicle–infrastructure cooperative systems, 

as the NAHSC had been doing; however, 

by 1997 it had renamed itself the Advanced 

Cruise–Assist Highway Systems Research 

Association, and changed its emphasis 

to much nearer term systems for driver 

warning and control assistance. AHSRA 

continued with this emphasis through 

its dissolution in 2010, when its research 

mission was declared accomplished and 

the results of the research were handed off 

for deployment by the Highway Industry 

Development Organization (HIDO).

Vehicle automation work shifted in different 

directions in Japan in the meantime. 

Toyota concentrated its attention on fully 

automated driving of passenger cars and 

small buses by using magnetic guidance 

based on the Partners for Advanced 

Transit and Highways (PATH) technology 

from the United States and very strong 

infrastructure-based intelligence for 

controlling vehicles longitudinally (moving 

block control analogous to rail and 

automated guideway transit technology). 

Toyota conducted public demonstrations 

of its automated cars at its MegaWeb 

amusement complex in Tokyo and of its 

three-bus Intelligent Multimode Transit 

System (IMTS) at several amusement 

parks and the 2005 Aiichi Expo (World’s 

Fair) near Nagoya, obtaining valuable 

practical experience with automated 

vehicle operations.

Japan’s Ministry of Economy, Trade and 

Industry (METI; the new name for the 

former Ministry of International Trade and 

Industry) initiated the Energy ITS Program 

in 2008, with a 5-year plan to develop 

an automated truck platoon to reduce 

aerodynamic drag, thereby saving energy 

and CO2 emissions. This important project 

will be described in more depth in the 

section on Japan in the next chapter of 

this report.

Japan
not trust their infrastructure agencies to be 

able to provide any cooperative infrastructure, 

so they have tended to insist that their vehicles 

be able to operate without infrastructure 

assistance.

Subsequent to PROMETHEUS, Mercedes 

was the leader of the CHAUFFEUR 

projects, in which platoons of two and three 

trucks were developed and tested. The 

first truck in the platoon would be driven 

manually, but the following truck(s) would 

use automatic steering and speed control 

to follow the trajectory of the first. This 

system was highly cooperative: There was 

close communication between the leading 

and following trucks and a distinctive 

pattern of infrared lamps mounted on 

the rear of the truck trailers that could be 

recognized by sensors on the trucks that 

followed behind them.

Volkswagen has been more receptive 

to vehicle automation than its German 

competitors have been. It demonstrated an 

advanced automated platoon system in 

the late 1980s, in which a heterogeneous 

platoon of vehicles was driven at short 

gaps on a test track with no drivers in the 

vehicles. V2V cooperation and sensing 

systems supported effective platoon 

control. More recently, Volkswagen 

supported the Stanford team’s testing 

of autonomous automated vehicles for 

the Defense Advanced Research Projects 

Agency (DARPA) Challenges, and they 

are now key participants in the HAVEit 

(Highly Automated Vehicles for Intelligent 

Transport) project, which is described 

in more detail in the chapter, “Current 

European Projects in Cooperative Vehicle–

Highway Automation” within this report. 6

Germany

Germany’s history of cooperative vehicle 

automation system work is not quite as 

long and deep as Japan’s history, but it is 

nevertheless substantial. In the 1970s, a 

German consortium developed an advanced 

PRT concept called the Cabinentaxi under 

the sponsorship of the Ministry of Research 

and Technology and tested it extensively 

on a test track; however, like the Japanese 

CVS, it never advanced beyond the test 

track to public deployment.(3)

The German auto industry, with its 

emphasis on high-end vehicles, has had 

a significant involvement with advanced 

technology for automotive vehicles. 

The emphasis on automated driving has 

been somewhat muted because of the 

prevailing ideology about the “fun” of 

driving oneself, particularly at BMW and 

Mercedes; however, Mercedes was the 

founder of the PROMETHEUS project 

in 1986, the seminal European program 

that began ITS with a strong theme of 

automated driving.(4) Mercedes developed 

an extremely sophisticated and advanced 

test car, called VITA II, under PROMETHEUS, 

which they demonstrated performing fully 

automated driving in 1994.(5) The philosophy 

behind this vehicle development was to 

make the car fully autonomous, basing its 

driving decisions entirely on data about 

the driving environment collected by its 

sensors (mainly video cameras), without 

any cooperation with the infrastructure 

or other vehicles. This was influenced to a 

considerable extent by the pioneering work 

of Ernst Dickmanns of the University of the 

Bundeswehr, who demonstrated a vision–

guided car in 1987.(6) German car makers do 
France

In France, the interest in automated 

vehicles has originated within the research 

community rather than within the vehicle 

industry. Following the NAHSC work 

in the United States, a group of French 

researchers from several national research 

institutes developed a plan for an analogous 

program in France that is based on a very 

similar operating concept with cooperative 

automated vehicles driving in protected 

lanes. These researchers wrote a book 

about this work (La Route Automatisée) and 

formed a research consortium, LARA, to 

take it forward. The funding support for this 

work has been somewhat limited, focused 

on nearer term applications and narrower 

developments of enabling technologies.

The two French automobile companies, PSA 

and Renault, have been relatively negative 

about vehicle automation until very recently, 

in large part because of some adverse 

experiences with early versions of partially 

automated vehicle control assist systems 

that were brought to market prematurely; 

however, as explained in the section on 

France in the next chapter, this situation is 

now changing significantly.

The more substantial research activity in 

France has been in the area of “CyberCars,” 

small automated vehicles designed for 

use at low speed in urban areas. Several 

generations of these vehicles have been 

developed and tested under a variety of 

operating conditions, either physically 

segregated from other vehicles and 

pedestrians or else operating in locations 

with a very low density of other vehicles 

and pedestrians. 7

Parallel Historical Activities 

in the United States

In many ways, the United States pioneered the 

concepts and technologies of cooperative 

vehicle–highway automation and had the 

field to itself until the 1970s.(7) The original 

concepts were defined at General Motors 

(GM) in the 1930s and were presented to the 

public in the Futurama exhibits of the 1939–

40 and 1964–65 World’s Fairs in New York, 

NY.(8) GM and RCA pursued development of 

automated highway technologies throughout 

the 1950s and into the 1960s.(9) In the mid1960s, this line of research was picked up at 

Ohio State University, where it continued until 

1980.(10) In the 1970s, there was considerable 

parallel research on cooperative automation 

systems for PRT, with heavy funding 

support from the Urban Mass Transportation 

Administration, the precursor to today’s 

Federal Transit Administration.(11) This led 

to the implementation of the Morgantown, 

WV, people–mover system and several other 

urban people movers, as well as many of 

the airport people movers now in operation 

around the world. These systems are captive 

to their specialized guideways, and their 

longitudinal control is based on moving 

block point–follower control systems 

derived from railroad technology, rather 

than performing active vehicle–following.

There was a hiatus in vehicle automation 

research in the United States for most of 

the 1980s,(12) even while this type of research 

became active in other countries, until the 

California Department of Transportation 

(Caltrans) began to sponsor a new 

generation of this kind of research via the 

California PATH Program in the late 1980s.(13)
The PATH research on automated highways 

was State-funded until it started to receive 

Federal Highway Administration (FHWA) 

funding in 1993 and was then integrated 

into the NAHSC research from 1995 onward. 

Following the demise of the NAHSC in 1998, 

Caltrans continued to support PATH research 

on automated trucks and buses through 

2003. The Federal Transit Administration 

provided some support for automatic 

steering control of buses through its Vehicle 

Assist and Automation Program, and 

FHWA’s Exploratory Advanced Research 

Program supported additional research 

on automated truck platoons and CACC 

beginning in 2007. For the past decade, 

these efforts have been funded at much 

lower levels than the analogous research 

overseas, which will be described in 

subsequent sections of this report.

8
Institutional and Political 

Environment for Cooperative 

Vehicle–Highway Automation
10

Europe in General

and European

Commission Activities 

The institutional environment associated 

with ITS in Europe is very complicated and 

substantially different from that of the 

United States. It is sufficiently complicated 

that most of the people who work in the 

field in Europe claim to not understand it 

themselves, including those who work at the 

major public and private sector organizations 

in the field. With the establishment of the 

European Union (EU), there is some broad 

analogy to the United States if one thinks of 

the EU being like the Federal Government 

and the individual national governments 

being like the State governments. In this 

comparison, the EC would be analogous 

to the executive branch of the Federal 

Government; however, the analogy between 

the EU and U.S. Government is imperfect, 

because the division of responsibilities and 

the flow of funding between the EU and its 

member states does not match the division 

between the Federal and State governments 

in the United States.

One of the most important contrasts 

between Europe and the United States is that 

European countries have ratified the Kyoto 

Accords on greenhouse gas reductions and 

take very seriously its mandate to reduce 

CO2 emissions from transportation. This 

means that saving energy and reducing CO2 

emissions has become the most important 

motivating factor behind ITS as a whole 

and automation in particular, ahead of both 

safety and mobility–enhancement goals. 

The EU’s Transport Policy, as defined in a 

March 2011 White Paper, includes cutting 

in half the use of conventionally fueled road 

vehicles by 2030 and eliminating cars from 

Europe’s cities by 2050. National taxation in 

most European countries has put the price of 

gasoline in the range of $8 to $9 per gallon 

in recent times, providing strong incentives 

for the vehicle industry and consumers to 

save energy.

At the EC, several different DGs, analogous 

to cabinet–level Departments in the United 

States, are involved in ITS:

» DG–MOVE (Mobility and Transport) 

establishes transport policy for 

Europe and addresses how to facilitate 

deployment of ITS technologies in 

support of that policy. The ITS deployment 

program EasyMove is centered here, but 

the only research appears to be policy–

oriented rather than technology–related.

» DG–CONNECT (Communications Networks, 

Content and Technology) is the agency 

responsible for encouraging more use 

of information technology throughout 

Europe and for improving the international 

competitiveness of Europe’s information 

technology (IT) industry. Its Unit 

H.5 (Smart Cities and Sustainability, 

formerly Information and Communication 

Technology (ICT) for Transport) sponsors 

the most visible of the EC’s ITS research 

projects, especially on cooperative 

systems, and is the group that has 

established a research agreement 

with RITA’s (Research and Innovative 

Technology Administration’s) ITS Joint 

Program Office.

» DG–RTD (Research and Innovation) 

sponsors more general enabling 
11

technology research and more 

theoretical research, but it is also the 

agency that has been supporting most of 

the CyberCars research and promoting 

the use of special-purpose automated 

vehicles for urban transit applications in 

its Unit H2 on Surface Transport. 

» DG–ENTR (Enterprise and Industry) 

is responsible for strengthening the 

international competitiveness of 

European industry and promoting job 

growth through innovation.

The level of coordination among these 

DGs is not particularly close, and they 

are not always aware of the activities 

in the other DGs. It is also significant 

that the technical research on ITS is 

supported in the agencies that are 

responsible for general research and 

industrial competitiveness in IT (analogous 

to National Science Foundation and 

Department of Commerce in the United 

States) rather than in transportation.

Each agency has its own processes for 

project selection and procurement, but 

in general, their procurements are less 

prescriptive than in the United States, 

because their rules are considerably 

different from the Federal Acquisition 

Regulations in the United States. There is 

much more opportunity for the industry 

and research community to influence the 

selection of research topics at the start of the 

process. The EC staff role is more of process 

facilitation rather than strategic direction 

setting; thus, the strategic direction comes 

more from the stakeholder community. In 

DG–CONNECT in particular, the project 

development and selection process appears 

to be much closer to the National Science 

Foundation process in the United States, 

with extensive bottom–up input on topics 

and peer review of proposals, than it is to 

the U.S. Department of Transportation 

process. The scope statement for a multi–

million dollar project could be defined in one 

or two pages, leaving significant freedom 

to the teams competing for the funding to 

propose different technical approaches.

The EC funding is intended to encourage 

better integration and cooperation among 

the member states, so the funding always 

requires that proposals come from multinational teams. In recent years, there has 

also been a strong emphasis on the funding 

of “integrated projects,” which are very large 

projects composed of multiple subprojects, 

with teams that can be comprised of 40–50 

different organizations and funding levels 

of tens of millions of dollars. These large 

projects require their own management 

structures and decisionmaking processes, 

which are created by the project partners 

rather than the EC. This helps keep the EC 

staff small and its influence over project 

direction limited.

These aspects of the EC research funding 

process give it more flexibility to respond 

to the interests of its industrial and 

research stakeholders as those interests 

change, but they also mean that the 

EC cannot get too far out in front of its 

stakeholders either. When senior EC staff 

members make public statements about 

automation being the inevitable future 

of road transportation, there can be 

some confidence that this is more than a 

personal opinion, rather that it reflects the 

broader evolution of thinking in Europe.
12

National Activities

in Europe 

Despite the presence and influence of 

the EU, the individual member states 

maintain their own diverse perspectives 

on transportation and technology issues. 

Their differences in geography, economy, 

and history have produced significant 

differences in their transportation needs 

and institutional structures. The major 

European countries all have their own 

transportation and technology strategies, 

as well as different (and competing) 

industrial interests; thus, Europe cannot be 

viewed as a monolithic entity.

France

France has a strongly centralized government 

structure, with heavy national investments 

in both transportation and research through 

its government ministries; however, in recent 

years, the funding for public transit system 

development and operation has been 

decentralized to the cities. Economic and 

political decisions are dominated by Paris, one 

of Europe’s largest urban agglomerations, and 

all other parts of the country have a different 

stature (as well as significantly different 

problems and needs). The intercity high-speed 

rail network is the most highly developed one 

on the continent, and the intercity limited–

access highways are privately operated toll 

ways (with high tolls). The highway operating 

companies have been international leaders in 

the adoption of ITS services.

France has two major automotive OEMs, 

Renault and PSA (which produces Peugeot 

and Citroën cars), neither of which has 

been exporting to the United States for 

a long time. They are not as large and do 

not have as much capability as the major 

German or Italian carmakers, and they have 

been relatively cautious about introducing 

ITS applications. Some years ago, they had 

a negative experience with the premature 

introduction of driver assistance systems, 

which led to a long period in which they were 

hostile to such systems and more advanced 

automation systems. Their position is now 

changing, in large part because of the 

growing emphasis on reducing energy use 

and greenhouse gas production. The French 

carmakers have been supporting new 

models of car ownership, such as carsharing 

systems, and have also become more multi–

modal in orientation. Because PSA makes 

bicycles and motor scooters as well as cars, 

they have been creating integrated mobility 

solutions that combine these different 

modes. (Volkswagen has a somewhat 

different combination of electric bicycles 

and scooters available in Germany.)

France has a strong and well–funded 

national research establishment, with many 

national laboratories of international repute. 

The two major national research institutes 

that have been most important in the ITS 

field, the national institute for research on 

transportation systems and their safety 

(INRETS) and the national laboratory for 

roads and bridges (LCPC) were merged into 

a single entity, IFSTTAR, at the start of 2011, 

under the joint sponsorship of the ministries 

for research and industry and transportation. 

France had already created a jointly operated 

research laboratory to explore vehicle 

automation and interactions with drivers, 

called LIVIC, about 10 years earlier. The 

French research on CyberCars has been 

led by France’s national research institute 
13

for information technology and automation 

(INRIA), which is more generally oriented 

toward basic research.

France is also trying to encourage the 

international industrial competitiveness of 

its regions through the creation of regional 

clusters of industry, research laboratories, 

and academic institutions. The large 

national technology initiatives are now only 

accepting proposals from such regional 

clusters to maximize the likelihood that the 

research results can be commercialized. 

The goals of producing a marketable 

product or a new startup company are now 

among the specific targets of some of the 

national projects.

The French research institutes are also 

networking heavily with researchers in other 

countries for ITS work. The research and 

industry ministry sponsors a broad-based 

cooperative program with the German research 

and technology ministry called Deufrako

(based on the contraction of the German 

words for German–French Cooperation), and 

there are other active research collaborations 

with Canada, Australia, and California.

Germany

Germany’s government is much more 

decentralized than France’s, with more of the 

funding and power residing at the state level 

compared with the federal level. The major 

intercity highways (autobahns) are free rather 

than tolled, and the only significant growth 

in that highway network in recent years has 

been in the eastern part of the country, where 

heavy investments were needed to bring the 

infrastructure up closer to western levels after 

the reunification 20 years ago.

Germany does not have the kind of national 

research institutes that France has, but it does 

have extremely strong research universities 

and technical universities. Because these 

universities are considerably more applied in 

their research than are the French universities 

and have substantial professional staff, 

faculty, and students, they are more nearly 

comparable with the national research 

institutes in France. 

Germany also has three major automotive 

OEMs (i.e., Daimler–Benz, Volkswagen, and 

BMW) and tier–one suppliers, Bosch and 

Continental, which are international leaders 

in technology and sophistication. Because 

they all sell high–end cars, they also have 

the customer base to purchase the latest 

driver assistance innovations. They have 

strong corporate research laboratories, 

which have taken the leadership role in 

many of the EC projects, giving them a 

disproportionate influence on the direction 

of that research. 

Germany’s research and technology 

ministry, Bundesministerium für Forschung 

und Technologie (BMFT), has been 

sponsoring national research programs in 

ITS for many years, complementing the EC 

research projects. These programs have had 

very strong involvement from the German 

carmakers and their major suppliers, which 

has led to a stronger emphasis on vehicle 

systems than on infrastructure systems. 

The current program, called Aktiv, is ending 

and will be followed by a new program. 

Germany’s equivalent of FHWA’s Turner–

Fairbank Highway Research Center, BASt, 

has recently become active in automation 

issues, sponsoring important research 

on the legal issues associated with road–

vehicle automation.
14

The Netherlands

The Netherlands is the most densely 

populated country in Europe and is a 

transportation crossroads because of its 

location and its major air and seaports. This 

means that goods movement is a particularly 

strong concern here. The Rijkswaterstaat, the 

agency responsible for the national highway 

network, has been an international leader 

in ITS from the start and has been active 

in many projects. They want to be a leader 

in implementation of cooperative systems, 

from traffic management to vehicle-based 

systems, and have sponsored ambitious 

field tests of ACC and lane–departure 

warning systems in the past.

The Netherlands has strong research 

universities and a national research institute, 

TNO, which was formerly public but is now 

a private entity. They have been active 

participants in European–wide projects 

and are well networked internationally. 

The Netherlands does not have a domestic 

automobile industry, although they 

have smaller specialty truck and bus 

manufacturers and many suppliers. The 

region of North Brabant around Eindhoven 

is the technology hub for the country and 

has been investing heavily to establish 

itself as one of the European centers for 

automotive technology. The Netherlands is 

trying to capitalize on its lack of a home–

based automotive OEM to market itself as 

unbiased suppliers to the entire international 

vehicle industry. Both government and 

industry have created projects and 

demonstrations to showcase their interest in 

V2I and I2V cooperative systems, including 

various levels of vehicle automation. These 

have involved the regional development 

agencies as well as the national ministry for 

economic development in projects such as 

the recently completed Strategic Platform 

for Intelligent Traffic Systems (SPITS), 

intended to spur deployment of ITS.

Spain

In Spain, the research ministry has been 

providing support to researchers who are 

working on several projects that involve 

vehicle automation at the national scientific 

research council’s automation and robotics 

center. These projects have mainly been 

focused on autonomous vehicles but more 

recently have involved more cooperative 

systems. The institutional framework, 

however, continues to focus on basic research 

rather than transportation applications, 

and it is not connected to transportation 

operations or deployment.

Other European Countries

Although there are important activities on 

automation in other European countries, 

these activities have been associated 

with specific industry and research 

organizations rather than with the national 

governments in those countries. Both 

the Volvo car and truck companies in 

Sweden have been active in several of the 

prominent EC projects on automation in 

the hope of continuing to enhance their 

reputation for leadership on safety issues. 

Ricardo, an automotive consultancy in the 

United Kingdom, is leading the SARTRE 

truck platooning project for the EC. In Italy, 

the University of Parma and its spinoff 

company, VisLab, have been international 

leaders in research on computer vision 

technology for vehicle automation.
15

Japan 

Japan’s government is considerably more 

centralized than the governments in Europe 

or the United States; thus, the national 

government has the authority to make 

decisions about infrastructure technology 

and deployment for the entire country. They 

also have a heavy regulatory hand on the 

vehicle industry, which they can force to move 

in a variety of directions. There is also a strong 

history of cooperation between government 

and large corporations, with the government 

promoting the interests of its large corporate 

citizens. This means that adoption of new 

cooperative ITS technologies can be pushed 

faster than in other countries.

Japan has four government ministries with 

interests in ITS, all with somewhat different 

areas of focus. The Ministry of Internal Affairs 

and Communications oversees wireless 

communication technologies and spectrum 

allocations. The Ministry of Land, Infrastructure, 

Transport, and Tourism is responsible for 

the intercity highway network and for safety 

regulations on the vehicle industry. The 

National Police Agency manages traffic within 

the urban areas (except for the highways), and 

METI is responsible for the country’s economic 

health and for generating jobs through 

improving international competitiveness. It 

has a long–standing role as the protector of 

the automotive industry and has taken the 

lead role in the recent Energy ITS Program that 

is developing an automated truck platoon to 

save energy and greenhouse gas emissions.

Japan does not generally have the strong 

national research institutes or universities 

of the European countries, but its vehicle 

and electronics industries have very strong 

technical capabilities in their own research 

and development laboratories. This is 

typically from where the major technological 

advances come. The domestic Japanese 

consumer market is favorably inclined toward 

new gadgetry, even before it is mature 

enough to provide real value. This means 

that the Japanese companies can generate 

revenue by selling immature systems to their 

customers and then gradually improve the 

systems until they are robust enough for 

export to other less tolerant markets.

Japan is not a fertile ground for applying 

automation to transit buses, because the 

high-priority and high–demand transit 

services are all on rails rather than on rubber 

tires, and the buses only provide supporting 

feeder services or relatively low–volume 

services. Because the majority of Japan’s 

freight travels by highway, however, the 

trucking applications look considerably more 

promising. The automobile applications are 

more uncertain because of the peculiarities 

of automobile usage in Japan. Automobiles 

serve only limited fractions of the trips in 

the urban areas, because the densities are 

generally too high for efficient use and 

parking, and the urban expressways are very 

narrow (only two lanes each way). On the 

intercity highways, the congestion problems 

are associated with grade changes (known 

as sags) and with delays at the access points, 

where vehicle automation is not a particularly 

efficient or cost–effective solution compared 

with other alternatives. 

The government and automobile companies 

are very interested in methods of smoothing 

out the speed variations at the sags and have 

consequently created the Smart Traffic Flow 

Research Consortium to develop strategies for 

speed harmonization. This consortium, which 
16

includes the major automotive OEMs and 

university researchers, focuses on strategies 

that are much less ambitious than vehicle 

automation, including the introduction of pace 

cars to regularize the traffic speeds, roadside 

variable message signs to advise drivers to 

maintain their speeds, V2V communications 

and in-vehicle displays advising drivers about 

the speeds they should drive, I2V speed 

advisories, and V2V speed controls along the 

lines of cooperative ACC. The consortium is 

also working on achieving string stability of 

conventional ACC vehicles, including when 

vehicles from different makers need to 

coexist in sequence. These activities were 

first unveiled to an international audience in 

Special Session 52 of the ITS World Congress 

in Orlando, FL, but there were no published 

papers or other enduring documentation 

provided in English.

Korea

The institutional structure in Korea is 

similar to the Japanese model, with a 

strong central government and strong 

automotive industry. Because its economy 

has developed somewhat more slowly than 

has Japan’s, the situation in Korea often 

gives the impression of being similar to 

Japan a few decades earlier.

The Korea Highway Corporation is 

responsible for the extensive toll road system 

in Korea and is very well–funded as a result. 

It has initiated a “Smart Highway” project to 

apply the latest ITS technologies, including 

cooperative systems, to its highways. After 

multiple contacts and inquiries, however, it 

appears that this project is not extending its 

scope beyond driver assistance systems and 

into full automation within the foreseeable 

future, so it is not directly relevant to the 

current project.

Some Korean universities are participating 

in projects and contests that involve 

autonomous automated road vehicles, 

which are somewhat outside the scope of 

this review, but it has not been possible to 

identify any cooperative automation work 

in Korea.

China

China has a centralized government 

structure, more so than any of the other 

countries considered in this report. Inquiries 

about work on cooperative automation 

systems have not yielded any leads until now. 

Multiple universities have been conducting 

research on autonomous automated vehicles 

and holding competitions, but there have 

not yet been any indications of V2V or I2V 

cooperation in support of automated driving.

Summary of Key Factors 

Overseas

Several aspects of the environments in 

other countries are notable, particularly for 

the ways in which they contrast with the 

U.S. environment:

» The motivation and funding support 

for the development of ITS, and vehicle 

automation systems in particular, 

generally come from public agencies that 

are responsible for improving technology 

and economic competitiveness, rather 

than transportation.
17

» The primary public sector goals associated 

with ITS and vehicle automation in 

particular have shifted in recent years 

to energy savings and CO2 emission 

reductions, based on the need to meet 

the targets in the Kyoto Accord (this 

is now prioritized ahead of safety and 

mobility issues). Achievement of these 

goals is already encouraged by high 

fuel taxation, producing gasoline retail 

prices at more than twice the U.S. levels.

» The governments of other countries 

tend to have more centralized 

decisionmaking and deployment 

authority than in the United States, 

making it easier to implement new 

infrastructure–based systems. At the 

same time, vehicle manufacturers 

remain leery of being dependent on 

deployment of roadway infrastructure 

elements for their systems to work 

effectively.

» Vehicle manufacturers and vehicle 

buyers are willing to pay more for 

innovative high–technology features in 

their vehicles.
18

Current European Projects

in Cooperative Vehicle–

Highway Automation
19

The European projects that are 

currently developing CVHAS, or their 

subsystems or precursors, are reviewed 

in this chapter. These reviews are based 

on in–person visits with the leaders of the 

projects and, where possible, participation 

in demonstrations of the target systems. 

The information reported here augments 

the information in the literature review that 

was prepared for this project and developed 

as a separate report. It also includes more 

subjective and unofficial information than the 

more formal published information cited in 

the literature review.

This review of the current and recent 

European CVHAS projects begins with the 

major integrated projects sponsored by 

the EC and then covers the most important 

national projects. The section concludes 

with a discussion of the major workshop 

that the EC sponsored in October 2011 

to synthesize the results of the work 

performed until that time and to identify 

the next steps that need to be taken. The 

following sections in this chapter provide 

descriptions of the different CVHAS 

projects reviewed. 

19
20

the information reported here was based 

on meetings with the primary project 

participants and their presentations at recent 

international meetings rather than on any 

direct experience of vehicle demonstrations.

Figure 1 shows the basic SARTRE operating 

concept in schematic form.(14) A truck driven 

by a specially trained driver would lead the 

platoon, and other trucks and cars could then 

perform fully automated vehicle–following 

behind the lead truck. The driver of the lead 

truck would be provided with technologies 

that would assist him to drive as safely, 

smoothly, and efficiently as possible. The 

steering systems of the following vehicles 

would be designed to follow the same 

trajectory as the leading truck, but this raises 

concerns about the safety of the followers if 

the lead truck runs off the road or is involved 

in another kind of unsafe scenario. The drivers 

of the following vehicles would be able to do 

whatever they want while following in the 

platoon and would not have any vehiclecontrol responsibilities, thus freeing up the 

drivers to perform other duties during their 

travel time. 

The SARTRE project team has been trying 

to use available sensor technologies as 

SARTRE

The SARTRE project (SAfe Road TRains 

for the Environment) is the most recent 

of the major EC–sponsored projects on 

vehicle automation, and its vision is the 

most ambitious in the level of automation 

to be implemented in a public mixed–

traffic environment involving automated 

close–formation vehicle platoons. As 

the name implies, the main motivations 

are both environmental and safety–

related, but the project is also interested 

in reducing congestion and enhancing 

driver convenience. SARTRE is led by the 

automotive consultants Ricardo from the 

United Kingdom and the major vehicle 

industry partners at Volvo, both automobile 

and trucking companies. The SARTRE 

project team is developing and testing a 

concept of a platoon led by a manually driven 

truck, with a mixture of fully automated trucks 

and cars following close behind to save fuel 

and emissions. The SARTRE project team 

plans to eventually operate these “road trains” 

on public highways in mixed traffic, with the 

shortest feasible gaps between vehicles. 

SARTRE began in September 2009 

and ended in September 2012 with a 

demonstration in Sweden. It is funded at 

a total level of €6.4 million ($8.2 million), 

with the EC funding 60 percent of the total 

and the seven project partners from four 

European countries funding the rest as cost 

share. The project sponsors held a media 

demonstration in December 2010 and a 

workshop and demonstration in September 

2012, but no demonstrations were scheduled 

during the information–gathering stage 

of this international review project; thus, 

Figure 1. Diagram. SARTRE operating concept. 

© Volvo Car Corporation

20
21

vehicles of different types entering and 

leaving the platoon, to make sure that all cases 

are covered by the technological capabilities 

of the system. Information from the following 

vehicles will be communicated to the driver 

of the lead vehicle so that he can judge, for 

example, when there is enough space in 

an adjacent lane to accommodate a lane 

change by the entire platoon (relying on the 

blind spot sensor systems on those following 

vehicles). Vehicles entering and leaving the 

platoon would be steered manually by their 

drivers, but their longitudinal control would 

be automated.

The SARTRE operating concept assumes 

that no infrastructure cooperation will be 

needed and that the SARTRE platoons 

much as possible in their test vehicles, 

because the Volvo production cars are 

now equipped with very comprehensive 

suites of sensors for collision warning and 

avoidance. SARTRE is using one 5.9 GHz 

dedicated short-range communication 

(DSRC) radio per vehicle for the V2V 

coordination, with 40–Hz updates of the 

vehicle data on these radios based on the 

control update cycles of the other elements 

of the system, but this is a faster update 

rate than what other DSRC applications 

have been assuming. The development 

work has been paying close attention to 

radio wave propagation challenges in 

this frequency band, particularly to avoid 

having cars shadowed by much taller 

trucks. The first test track experiments 

were conducted in late 2010, culminating 

in a high-profile media event that 

drew considerable attention. A second 

demonstration on a public motorway in 

Spain in May 2012 showed three passenger 

cars and a truck following the lead truck, as 

illustrated in figure 2.(14) A view from inside 

a car automatically following behind the 

lead truck from the first demonstration is 

shown in figure 3.(14)

SARTRE project members have been 

considering a variety of use cases for 

maneuvering, as shown in figure 4,(14) with 

Figure 2. Photo. SARTRE demonstration of three automated cars and one automated truck following

the lead truck in a platoon (May 2012).

© Volvo Car Corporation

Figure 3. Photo. Reading a newspaper while being 

driven automatically in the platoon behind the lead 

truck (December 2010).

© Volvo Car Corporation
22

would be able to operate in any highway 

lane, without segregation from other 

vehicle traffic. The project team has not 

worked through the implications of all the 

hazard scenarios that could arise in this 

type of mixed traffic automation, but they 

are aware that there are serious challenges 

here. One of the project partners, ika 

Aachen, already had experience with cut–

ins within their truck platoon in the KONVOI 

project several years ago (discussed later 

in this report), and cut–ins were also tested 

in SARTRE. 

The lateral control of the following vehicles 

in a SARTRE platoon is performed by 

following the trajectory of the lead vehicle, 

more or less like tracking a sequence of 

“breadcrumbs” from that vehicle, without 

reference to any roadway markings. This 

Confidentiality: Public 10/11 Oct 2011, SARTRE Workshop SARTRE_6_014_PU © Ricardo plc 2011 1

SARTRE Overview

Use Cases

Other Vehicle Tries to Enter Platoon

Truck Joins Platoon

Car Joins Platoon

Car Joins Platoon From Rear Truck Joins Platoon From Front

Car Leaves Platoon

Truck Leaves Platoon

Car Leaves Platoon From Rear Truck Leaves Platoon From Front

FV/LV

PFV/PLV

FV

PFV

OV

Figure 4. Diagram. SARTRE vehicle-maneuvering use cases. 

NOTE: FV = following vehicle, LV= lead vehicle, PFV/PLV = potential following vehicle/potential lead vehicle,

OV = other vehicle (not part of the platoon).

© Volvo Car Corporation

was justified on the basis of avoiding the 

need to add more sensors to the vehicles, 

but it increases the risk to all of the 

followers when the lead vehicle driver does 

something wrong.

HAVEit

The HAVEit project is another major 

Integrated Project of the EC, in this case 

sponsored by DG–CONNECT. The name 

HAVEit stands for Highly Automated 

Vehicles for Intelligent Transport, but in 

this context highly automated does not 

mean fully automated. Rather, this project 

concentrates on partially automated 

vehicles and has conducted some important 

experiments and prototype developments 

to explore how drivers interact with vehicles 
23

Reiner Hoeger / 2009 Continental 1

Root Cause and the HAVEit Approach:

Automation to Assist and Not Replacing the Driver

at different levels of automation, trying to 

avoid both underloading and overloading 

of drivers, as illustrated in figure 5.(15)

HAVEit began in February 2008 and ended 

in June 2011, with a final event held at a 

Volvo test track in Sweden. It was funded 

at a level of €27.5 million ($35 million), 

with €17 million ($22 million) funded by 

the EC and the rest funded in cost share 

from the 17 partner organizations led 

by the automotive supplier company 

Continental. The primary vehicle industry 

partners were Volkswagen for cars and 

Volvo Technology for trucks.

The central principle in the HAVEit project 

is the provision of four different modes of 

driver–vehicle interaction, with varying levels 

of automation, which can be engaged by 

the driver through a “mode selection and 

arbitration unit” as follows:

» Driver only—full manual control.

» Driver is assisted by using a single existing 

driver assistance (warning) system, such 

as a lane-departure warning or a forward–

collision warning.

» Semi-automated, combining warning 

systems with a longitudinal control 

Figure 5. Diagram. Basic philosophy of multiple levels of driving automation in HAVEit.

© Continental Automotive GmbH

activation
24

function, such as ACC or full–speed 

range ACC.

» Highly automated, combining lateral 

and longitudinal control (ACC plus lane–

keeping assistance).

These different modes have been 

implemented on test vehicles primarily 

by using existing commercially available 

sensors and driving assistance systems, 

minimizing the amount of new purpose–

built equipment and associated costs. An 

integrated driver–vehicle interface (DVI) was 

developed so that the driver could look in 

one place to determine which level of driving 

automation or assistance was being provided 

and to choose a different level. This concept 

is indicated schematically in figure 6,(15) and 

an example implementation on one of the 

test vehicles is shown in figure 7.(15) Despite 

the emphasis on re-use of existing sensors 

and systems, the overall system is still quite 

complex, as shown in figure 8.(15)

The HAVEit project team is well–supplied with 

human factors expertise and tools to develop 

a better understanding of driver limitations 

and drivers’ ability to interact safely with 

the different levels of automated driving 

assistance. They used driving simulators in the 

development, including a “theater technique,” 

in which an expert driver acted as the virtual 

copilot that the test subjects did not see at a 

second driving station, by which they could 

assess which of the copilot’s driving strategies 

© Continental Automotive GmbH

Figure 6. Diagram. Multiple automation levels through one driver–vehicle interface. 
25

worked well with the naive test subjects and 

which did not so that they could choose which 

to implement in the system software.

At the HAVEit final event, Dr. Juergen Leohold, 

the head of research for Volkswagen, confirmed 

that driving automation had been part of their 

corporate vision for a long time, motivated 

primarily by safety considerations. He identified 

the main challenges to deployment of these 

partially automated systems to be:

» Affordable sensors with “high enough” 

performance capabilities.

» Sensor fusion to achieve higher reliability 

and safety.

» Legal restrictions associated with the 

Vienna Convention on Road Traffic, 

liability uncertainties, and the need for 

consistent regulations.

» Development of a human–machine 

interface (HMI) approach to maintain 

the driver’s attention in the control loop 

without being annoying.

The current prototype vehicle implementation 

relies on a video camera mounted inside the 

instrument cluster, observing the driver’s face, 

as explained in figure 9.(15) If the driver’s head 

or eyes are turned away from the forward view 

of the road, a video image processing system 

detects this as inattention and issues an 

increasingly urgent audio alert to the driver. If 

the driver does not return eyes to the forward 

Figure 7. Photo. Example of a human–machine 

interface, showing different control mode choices.

© Continental Automotive GmbH

Figure 8. Diagram. Complexity of HAVEit implementation.

© Continental Automotive GmbH
26

driving scene, the system then decelerates the 

vehicle to a stop. This is a very conservative 

system design approach, intended to deter the 

driver from non–driving tasks, such as texting, 

but at the same time it denies the driver one 

of the primary benefits of automated driving, 

which is the ability to do other things. Some 

of the European automotive marketing people 

believe that this is a lost opportunity, and that 

the real attraction to the public of automated 

driving will be the ability to do something 

else during the driving time. Of course, to be 

able to do this safely, the performance of the 

automated system will need to be much more 

advanced than the current state of the art.

The HAVEit operational concept was 

described as a “joint system,” with the driver 

assuming supervisory control responsibilities. 

An analogy was drawn to commercial aircraft 

automation, in which 95 percent of the time 

the airliner is flown by the autopilot under 

the pilot’s supervision, but the pilot remains 

responsible for strategic decisions and 

must be prepared to take full control at any 

time. The other metaphor that was used to 

describe the system was the horse and rider, 

with “dynamic task repartition” between the 

elements of a joint cognitive system. In this 

case, the vehicle system needs to maintain 

a continuous real–time understanding of 

both the driver’s capabilities (watching 

the road or not) and its own capabilities 

(uncertainties or conflicts in its sensors’ 

perceptions of the environment).

The highlights of the HAVEit final event 

were the demonstrations of the vehicles on 

the test track, which are discussed in the 

following sections.

Volkswagen’s Temporary 

AutoPilot 

Volkswagen’s Temporary AutoPilot received 

the strongest media attention, because it 

Figure 9. Diagram. HAVEit concept of driver monitoring to ensure driver engagement, 

from Continental Automotive France (CAF).

© Continental Automotive GmbH
27

left the impression of a close approach to 

truly automated driving, but some of the 

media coverage overlooked the fundamental 

requirement for the driver to continue watching 

the forward driving scene as a prerequisite 

for the system to continue to operate. The 

AutoPilot demonstration proceeded through 

the different levels of driver assistance up to 

the combination of lateral and longitudinal 

control. The different control levels were visible 

on the DVI display, as shown in figure 10.(16)

The vehicle demonstrated the ability to 

track a slower vehicle in the left adjacent 

lane and avoid overtaking it on the right, 

which is illegal in many European countries. 

The vehicle also performed an emergency 

braking maneuver behind a stopped 

fake vehicle in its lane (fake for safety, to 

avoid danger in event of a failure). After 

engaging the “highly automated” mode 

with automatic steering and speed control, 

the driver turned his head to look out the 

side window for an extended time. That 

caused the system to beep with increasing 

urgency to try to draw his attention back 

to the road. When he failed to respond 

to the system’s beeping, it brought the 

vehicle to a gradual stop, representing a 

risk-averse strategy in case the driver was 

incapacitated or asleep. This strategy also 

prevented drivers from abusing the system 

by trying to do something completely 

different while driving.

Automated Queue Assistance 

(AQuA)

The Automated Queue Assistance (AQuA) 

system for trucks by Volvo Technology 

provided a somewhat different view 

of highly automated driving aimed 

specifically at low–speed driving in heavily 

congested traffic, which could become 

monotonous for the driver. This system 

was demonstrated by following a lead car 

that went through a series of stop–and–

go maneuvers, maintaining the truck at 

an appropriate following distance behind 

the car. Its driver interface is shown 

more closely in figures 11(16) and 12,(16) and 

figure 13(16) shows the view from the visitor 

seat in the back of the cab during the 

demonstration. The AQuA function can be 

engaged only at speeds below 30 km/h (19 

mi/h) and when there is a target vehicle 

within a reasonably short forward range.

Figure 10. Photo. Volkswagen’s Temporary Auto Pilot 

display, showing three levels of automation choices in 

lower right corner.

© Shladover, S. (2012)

Figure 11. Photo. Steering wheel controls for Volvo 

Automated Queue Assistance (AQuA) for heavy trucks.

© Shladover, S. (2012)
28

Figure 12. Photo. Automated Queue Assistance (AQuA) 

driver interface for heavy trucks.

© Shladover, S. (2012)

Figure 13. Photo. Automated Queue Assistance (AQuA) system demonstration for low-speed automation in a truck. 

© Shladover, S. (2012)

Automated Assistance in 

Roadworks and Congestion

Automated Assistance in Roadworks and 

Congestion was a demonstration intended to 

address assistance for drivers in a very high–

workload–driving environment, in which the 

automation could help reduce the workload. 

This demonstration was implemented by the 

first-tier automotive supplier Continental on 

a passenger car, which had to drive through a 

road section where temporary pylons defined 

a path different from that represented by 

the normal lane markings. The vehicle had 

to stay within the pylons while following a 

lead vehicle that went through a variety 

of speed changes of the type one would 

expect when going through a work zone 

where traffic flow is impeded.

Figure 14(16) shows the additional complication 

introduced into this scenario, where a truck 

in the adjacent lane drove very close to the 

equipped car, actually straying over the 

lane boundary (this happened toward the 

right end of the scene in figure 14, after the 

pylons). In this case, the car’s side–mounted 

laser scanners detected the truck impinging 

on its lane so that it could adjust its 

trajectory off the lane center to avoid being 

hit by the truck. Figure 15(16) shows the DVI 

on this test vehicle when it was in manual 

control, using only its collision–warning 

functions (indicated by the stick figure icon 

illuminated in white). The touch–screen 

display could be used to choose the semiautomated mode or the “highly automated” 

mode, represented by the rectangles that 

are shown in blue in figure 15,(16) because 

they were not active when this photo was 

taken. Although the display in this vehicle 

and the other cars in the demonstrations 
29

were in the center console of the vehicle, it 

was noted that production systems would 

be more likely to have their displays located 

directly in front of the driver, in the primary 

instrument cluster, where they will be easier 

to see without diverting the driver’s eyes 

from the forward driving scene.

In figure 15,(16) rain can be seen on the 

car windshield. The day of the HAVEit 

demonstration had extremely variable 

weather, with conditions ranging from bright 

sun to heavy rain. The vehicle systems worked 

well under this full range of conditions, and 

none of the demonstrations had to be aborted 

Figure 14. Photo. An Automated Roadworks Assistant vehicle follows a lead vehicle

between pylons and maintains separation from a truck.

© Shladover, S. (2012)

Figure 15. Photo. Roadworks Assistant driver–vehicle interface, showing three levels

of automation on left side of screen.

© Shladover, S. (2012)

because of adverse weather; however, at 

various times, phantom vehicle icons were 

observed on the display screens, indicating 

cases in which sensors were detecting other 

objects, such as guardrails, and not filtering 

all of them out.

Although the HAVEit systems that were 

developed and tested under the current 

project were entirely sensor–based rather than 

relying on communication for cooperation, the 

EC project officer for the project noted that in 

the follow–on work, cooperative capabilities 

will be added to provide additional data 

sources for the vehicle systems. 
30

CityMobil

The CityMobil project was sponsored by the 

EC, DG-RTD, from May 2006 through the 

end of 2011, at a total funding level of €40 

million ($52 million), of which €11 million ($14 

million) was provided by the EC (29 partner 

organizations provided the remaining funds, 

mainly to support their field demonstrations). 

This is the one project that has emphasized 

public transit applications of automated 

vehicles rather than automobile or trucking 

applications. It is the latest in a sequence of 

projects that have addressed the “CyberCar” 

concept, including CyberCars I and II, 

CyberMove, and City NetMobil.

CityMobil is promoting the development 

of new forms of public transportation to 

help reduce automobile usage in cities 

in support of environmental goals. It is 

based on the assumption that about 

one–third of the households in European 

cities cannot afford a car and one–third 

of households must have a car based on 

their housing and workplace situations, 

but one–third have a choice and can be 

influenced by the availability of better 

transit alternatives. CityMobil is targeting 

diverse niche markets for improved transit 

services, depending on urban area sizes, 

patterns of development, and existing 

transportation infrastructure. CityMobil is 

considering four classes of vehicles:

» CyberCars—Driverless low–speed vehicles 

that operate within somewhat restricted 

environments (low–density pedestrian 

zones).

» Advanced buses that use guidance and 

control technologies in busways.

» PRT—Small vehicles that operate between 

stations on a special dedicated guideway.

» Advanced city vehicles—Cars with 

driver assistance systems for partial 

automation and the ability to operate 

under automatic control under 

some specialized conditions, such as 

platooning of empty vehicles without 

drivers behind a lead vehicle driven by a 

specially trained person.

The definitions of CyberCars and advanced 

city vehicles remain somewhat imprecise at 

this stage of development, with considerable 

uncertainty about what levels of automation 

would be achievable in what kinds of operating 

environments (how much separation from 

pedestrians and other vehicular traffic). This 

is an important issue that became apparent 

with some of the other CVHAS projects as 

well and was indeed among the main areas 

of controversy during the NAHSC research in 

the United States in the 1990s.

Most of the information to be reported here 

was obtained during the CityMobil project’s 

final event in La Rochelle, France, in May 2011, 

which included a small public demonstration 

of a CyberCar and a 2–day technical 

conference with over a hundred attendees.

CityMobil La Rochelle Cyber 

Car Demonstration (May 2011)

The CyberCar demonstration used a single 

driverless vehicle with space for four 

passengers to stand while it drove at low 

speed (approximately a fast walking pace). 

It was operated in a low–density residential 

and light commercial area near the harbor in 

La Rochelle, mainly on a sidewalk adjoining a 
31

park and on an alley beside a row of buildings 

(figure 16).(16) This is a very low-density area, 

so interactions with other vehicles and 

pedestrians were infrequent. An attendant 

was required for passenger loading and 

unloading at the stations, and he walked 

or jogged alongside the vehicle while it 

was driving (figure 17).(16) When the driverless 

vehicle approached slower pedestrians, it 

slowed down behind them and then beeped 

at them to encourage them to get out of the 

way (which they generally did); however, 

if the pedestrians did not move, the vehicle 

would stop. In the aforementioned alley, the 

Figure 16. Photo. La Rochelle CyberCar demonstration site features a park sidewalk shared with pedestrians.

© Shladover, S. (2012)

vehicle shared the space with the occasional 

automobile and had to cross a few other 

alleys where cars could be operated. In these 

locations, the driverless vehicle had to wait 

for the other vehicles to pass before it could 

proceed.

The demonstration vehicle identified its 

location based on a Simultaneous Localization 

and Mapping (SLAM) approach, using laser 

scanners at both ends of the vehicle to 

recognize the surrounding built–environment 

landmarks. The conference attendees 

were informed that when a large group of 
32

Figure 17. Photo. A CyberCar at the station in

La Rochelle, France, with an attendant who was required for passenger loading and unloading

during the demonstration.

© Shladover, S. (2012)

reporters and photographers surrounded the 

vehicle at the time of its media event, they 

occluded the surrounding buildings from the 

view of the laser scanners, and as a result, the 

vehicle lost its bearings (not unlikely in any 

reasonably dense pedestrian environment). 

The vehicle was not equipped with a global 

positioning system (GPS) for positioning 

because of concerns about interruption of 

satellite coverage in the alley, which was 

considered to be an “urban canyon” for 

GPS coverage. The vehicle was equipped 

with WiFi communication so that the 

demonstration operators could keep 

track of its location and status.

The vehicle demonstration was continued 

after the end of the CityMobil conference 

for 10 weeks, during which time it 

operated 3 hours per day, carrying a 

total of 900 passengers (an average of 

about 4.5 passengers per hour). Of these 

passengers, 200 were surveyed for their 

opinions about the system.

Even this limited demonstration required 

considerable political and institutional 

arrangements. Because the vehicle was 

driverless, the mayor of the city had to issue 

a special exemption from normal rules (an 

arrêté), taking on special responsibility 

for anything that may have gone wrong. 

The low density of vehicle and pedestrian 

traffic in the area, as well as the low building 

density, raised questions about whether 

the sites that would be technically feasible 

to use such a vehicle would actually have 

enough travel demand to produce benefits 

that exceed the costs. Would these vehicles 

be able to operate in locations where they 

are really needed (such as the much more 

crowded main marina of La Rochelle, only 

a few hundred meters away from the site 

that was used)?
33

CityMobil La Rochelle 

Conference (May 2011)

The CityMobil conference was considerably 

more informative than was the vehicle 

demonstration, with a wide variety of 

presentations and discussions. Some of the 

key information brought forward during the 

conference is discussed below.

Low–Speed Urban CyberCar Plan,

Rome, Italy

Although the CyberCar demonstration in 

La Rochelle was the most visible example 

of vehicle automation technology, the main 

field test implementations—where most of 

the resources were spent in the project—

were conducted elsewhere. In the case 

of low–speed urban CyberCars, the main 

implementation was planned for Rome, 

Italy, where the demonstration site would 

have connected a remote parking lot with a 

large convention center. The vehicle that was 

intended to be tested in Rome is shown in 

figure 18.(16) A close–up view of the soft bumper 

that is designed to protect pedestrians who 

could be hit by the vehicle if its sensors did 

not detect them or if the vehicle did not stop 

in time is shown in figure 19.(16)

The intended CyberCar implementation 

in Rome is notable for the difficulties 

encountered when attempting to obtain 

the necessary certification for vehicle 

operation from government authorities. 

These authorities required that the vehicle 

only be operated on a right–of–way that was 

entirely fenced in to preclude interactions 

with other vehicles or pedestrians (obviating 

the need for the soft bumper). This obstacle 

showcased one of the institutional challenges 

in trying to implement a driverless vehicle in 

a public environment and raises questions 

about how it will be possible to put these 

vehicles into less-protected environments, 

where they would be easier and cheaper to 

place into service and would be accessible to 

more potential users.

Vision–Guided Bus Technology

The advanced bus application in CityMobil is 

the use of the vision–guided bus technology 

developed by Siemens (originally Matra) 

for use on the CiViS BRT bus, in this case 

applied to a more conventional bus in 

Castellon, Spain.

This bus–guidance technology has been in 

commercial use in Rouen, France, for many 

years but was tested unsuccessfully in Las 

Vegas, NV, several years ago. It has not been 

made clear what was sufficiently special 

about the Castellon application that it should 

become the subject of study in a major 

research program.

For example, the Castellon operation has 

much less automation than does the Phileas 

bus that was developed in Eindhoven in the 

Netherlands several years ago. Phileas was 

a publicly funded project that developed a 

Figure 18. Photo. Rome Exhibition Center vehicle. 

© Shladover, S. (2012)
34

new automated bus rapid transit system that 

could be viewed as the equivalent of a rubbertired tram. Phileas was funded by local and 

regional governments in the North Brabant 

region of the Netherlands, with the intention 

of strengthening the local industrial base and 

encouraging job growth through export sales 

of buses to other countries. (See reference 17 

for more information about Phileas.)

The Phileas system was tested on a public 

busway in Eindhoven under fully automatic 

control (both speed and steering control with 

driver supervision), but the control system 

was removed from the buses before regular 

revenue service began. Although the complete 

story of the Phileas system has not been 

documented, unofficial information suggests 

that the safety certification of the automation 

system was not included in the planning or 

budget for the original development of the 

system. When it came time to obtain the 

safety certification, there was no budget to 

pay for it, and thus it was not obtained.

Personal Rapid Transit

The most ambitious project incorporated in 

CityMobil was the deployment of the ULTra PRT 

(Personal Rapid Transit) system at Heathrow 

Airport in London. This system is quite 

complicated—with extensive infrastructure 

development—but also has limited passenger 

capacity in this initial implementation.

The Heathrow PRT has entered public service 

recently, carrying passengers between 

Terminal 5 and a remote parking area. Its 

development and deployment has largely 

been funded by British Airports Authority, 

which bought a controlling interest in the 

company that developed the system and 

expects to expand it significantly at Heathrow 

and other airports if the initial experience is 

favorable. The PRT vehicles are captive to 

their special guideway, but their driving is 

automated, with automatic steering control 

to choose the correct route to follow at 

diverge points and when entering station 

loading docks (figures 20 and 21).(18) Their 

speed control is based on a moving block 

system comparable with most automated 

people movers and some advanced rail 

control systems. This system went through 

an extensive certification process, analogous 

to that for railroad control systems, before it 

could be put into public use.

PRT systems are less like the road vehicles 

featured in the rest of the project than they 

are like rail vehicles, even though they do not 

run on steel wheels. They are confined to a 

Figure 20. Photo. ULTra Personal Rapid Transit 

(PRT) track at Heathrow Airport.

© Ultra Global

Figure 19. Photo. Soft bumper of the

Rome Exhibition Center vehicle.

© Shladover, S. (2012)
35

special guideway rather than being able to use 

the same road space as other vehicles, and 

they lack a manual driving mode for access to 

unequipped locations. Their control systems 

have strong infrastructure involvement and 

are also much more like moving block railroad 

signal control systems than like vehicle 

follower systems.

Advanced City Cars

The final category of vehicles in the CityMobil 

project, the advanced city cars, are less 

precisely specified than the other vehicle 

categories. These could be vehicles equipped 

with driver assistance systems for partial 

driving automation or vehicles that could 

be operated without drivers if they were 

being led in a platoon by a lead vehicle with 

a driver (e.g., for repositioning of vehicles in 

a carsharing operation). Another application 

that was discussed during the conference was 

vehicles that could provide enhanced mobility 

for elderly people who are no longer able to 

drive themselves. The most ambitious part of 

the presentation about this element of the 

project by Gianfranco Burzio of FIAT was the 

introduction of the FIAT Mio concept vehicle. 

This concept vehicle, developed for the 2010 

Torino motor show, was based on inputs 

suggested from many online participants 

around the world. The features that they 

requested, and that were incorporated in 

the vehicle, included fully automated driving 

on dedicated highway lanes and in-motion 

recharging of the electric vehicle propulsion 

batteries. The Web site for this concept 

vehicle includes an elaborately staged 

video of the vehicle in operation (the video 

is in Portugese, because it was targeted 

to a Brazilian audience, but it has English 

subtitles). The video can be viewed by 

accessing the following link:

http://www.youtube.com/watch?v=aCPrg2

TQui0&playnext=1&list=PL5FED4D80C03

D0EA0.

Automated Vehicle Certification

One of the most challenging issues that 

CityMobil encountered was the certification 

process for obtaining approval for operation 

of the automated vehicles in a public 

environment. The CityMobil team is concerned 

that it will be necessary to have a common 

legal and certification framework for gaining 

approvals for deployment throughout Europe 

in order for the automated vehicle market to 

pose acceptable business risks to suppliers. 

As previously mentioned, certification issues 

forced the application planned for Rome 

to be changed significantly to eliminate all 

possible interactions between the automated 

vehicle and other vehicles and pedestrians. 

If these types of restrictions were to be 

encountered everywhere, the CyberCar 

concept would not be deployable. At the 

other end of the spectrum, the Heathrow PRT 

went through a railroad-level certification 

process, which is a well-established process 

but also extremely conservative in its 

assumptions and expensive to satisfy. TNO, 

the prime contractor for CityMobil, has a lot of 

experience with safety certification, and they 

Figure 21. Photo. ULTra Personal Rapid Transit (PRT) 

vehicles and station at Heathrow Airport.

© Ultra Global
36

use a rather traditional risk-based approach, 

in which the stakeholders determine what 

level of hazard they can accept, by analogy 

with comparable existing systems, and then 

design to that level. 

For CityMobil, they assumed that the safety 

numbers for automated vehicles should be 

twice as high as that of existing road traffic 

based on road traffic safety statistics. In the 

TNO process, the severity of outcomes and 

their frequency of occurrence were treated 

as two dimensions of a matrix, and hazard 

level values were assigned to each cell of 

that matrix. The combinations of severity 

and frequency that exceeded an acceptable 

threshold level of hazard were highlighted 

as unacceptable.

Questions were raised at the conference 

about how the TNO process can account 

for the complexity of software–intensive 

control systems for automated vehicles, 

with their multitude of possible outcomes. 

The answers to these questions were not 

satisfying, because they were based on 

assuming a process of documenting each 

stage of the development process, with 

failure mode effects and criticality analyses. 

Offline discussions with automotive 

industry participants who were attending 

the conference indicated that they 

recognized that this process is inadequate 

for addressing the safety of software 

systems, which remains an important 

unresolved problem.

Non-Technical Risks

Public agencies perceive significant non–

technical risks associated with automated 

vehicle deployment, in addition to the 

technical risks. For example, the PRT 

systems have uniquely designed vehicles 

that must operate on uniquely designed 

guideways, so that once a locality commits 

to deploying a specific system, they are 

locked into a proprietary technology with 

only one supplier. This leaves the locality 

vulnerable to monopoly pricing for future 

expansions, as well as to the risk of premature 

obsolescence if that supplier goes out of 

business. Because the developers of most of 

the systems (not just the special guideway 

systems) are small companies, the risk of 

a supplier going out of business and not 

being able to provide future maintenance 

and support is very real.

Operating Costs

A discussion of operating costs of driverless 

vehicles revealed that the existing, relatively 

small fleets of driverless vehicles (e.g., the 

Rivium people-mover near Rotterdam) have 

operating costs comparable with those of 

conventional bus systems. This seemed 

surprising, because the dominant element 

of conventional bus operating costs is the 

driver labor, and no drivers are needed for 

driverless vehicles. The answer was that 

the maintenance labor costs compensated 

for the lack of driver labor costs. A certain 

minimum number of maintenance people 

are needed full time to handle any problems 

that may arise, and with a complicated 

system, one person cannot be expected 

to know how to fix all possible problems. 

When the number of vehicles is small, this 

fixed labor cost per vehicle can be high, 

but the cost will be reduced when it can be 

spread across a larger fleet of vehicles.
37

Challenges

There was considerable discussion of the 

challenges to widespread deployment of 

automated urban transit vehicles, and there 

seemed to be general agreement that there 

are multiple challenges, as follows:

» No established legal framework for 

allocating risks and responsibilities.

» Lack of an EC directive to define 

which regulatory framework should 

be applied, thus leaving each country 

on its own to establish its own 

framework (leading to unmanageable 

complexity for system developers 

and suppliers who need to deal with 

inconsistent requirements).

» Diverse safety certification approaches 

and requirements, which lead to the 

conclusion that this is likely to be a slow 

and expensive process.

» Larger up–front capital costs when 

compared with the cost of other 

alternatives, without a convincing way 

to demonstrate net life–cycle cost–

benefit advantages.

» Risk to system deployers and operators 

that small company suppliers of new 

systems may not survive to provide 

needed product support for the full life 

of the product.

» Challenges in physically retrofitting a new 

system into an existing built environment.

» Need for a well thought–out concept of 

operations of how driverless vehicles 

should interact with pedestrians and 

other vehicles.

» Need to overcome public anxieties about 

witnessing driverless vehicles operating in 

people’s immediate vicinity.

» Opposition by labor unions who fear loss 

of bus driver jobs if driverless vehicles are 

used instead of conventional buses.

» Limitations of system capabilities that 

restrict their application to low–density or 

fully controlled environments to provide 

acceptable safety levels.

» Perceived to be high–risk alternatives by 

risk–averse public authorities.

These problems were identified, and 

strategies were suggested for finding 

solutions for some of them, but solutions do 

not appear to be imminent.

Public Attitudes

On the positive side, many people attending 

the conference thought that public attitudes 

in Europe were shifting in favor of innovative 

transit services and away from automobile 

use. The impression is that the public 

values mobility rather than car ownership. 

Marketing approaches were suggested to 

make transit options emotionally appealing 

to people. One person even noted that a 

recent opinion poll found that young people 

were more inclined to perceive cars as 

“ViagraTM in chrome.”

Public Operational Test 

The EC is preparing to sponsor a public 

operational test of an automated transit 

system, representing a follow–on project 

to CityMobil. Several cities that would like 
38

to compete for the operational test made 

their pitches at the conference.

eLanes

One of the most important concepts 

developed in CityMobil is the “eLane,” 

which signifies a special subset of the 

roadway infrastructure in which the vehicle 

automation functions can be used. The 

publications on the subject of eLanes have 

been somewhat vague about the definition, 

leaving considerable uncertainty about how 

much physical separation would be needed 

between eLanes and other traffic. This 

uncertainty is real and continues to persist: 

Participants in this research confirmed in 

offline discussions that substantially more 

research is needed to determine what levels of 

vehicle automation can be applied with what 

degrees of physical protection from intrusion. 

This corresponds to the situation that the 

NAHSC researchers encountered in the United 

States in the 1990s, in which the question of 

dedicated and protected lanes was one of 

the most controversial issues. Despite more 

than a decade of effort since then, the issue 

remains unresolved, but there at least appears 

to be general agreement within CityMobil on 

the principle that fully automated vehicles 

cannot mix entirely with conventional traffic 

unless they are operated at very low (i.e., 

walking) speeds. Some degree of separation 

and protection is required.

2010 SMART-64

The EC, through DG–CONNECT, sponsored 

a small study in 2011 to investigate the 

impediments to deployment of vehicle 

automation systems and to determine 

what steps need to be taken to overcome 

them. This project, labeled SMART–64, was 

intended to define the framework for the 

next generation of EC work on automation. 

The project team was led by TNO from the 

Netherlands, with major subcontracts with 

the University of Southampton in the United 

Kingdom (UK), DLR (German Aerospace 

Research Laboratory), Frost and Sullivan 

and Tecnalia. Their final report summarizes 

the findings from their study, including 

stakeholder interactions in a European 

workshop.(19) The emphasis in this study was 

very heavily focused on private automobile 

applications, with limited attention paid to 

trucking and virtually no attention paid to 

public transport systems, reflecting the focus 

of the larger DG–CONNECT projects.

Figure 22(20) depicts the types of automation 

concepts that were considered in each of 

three different road environments in the 

SMART-64 study, and figure 23(20) shows 

estimates of the deployment time frames for 

applications clustered in functional groups. 

The blocks in gray in figure 22(20) were 

considered to be “pre automation” systems 

that could support automation rather than 

automation systems that take on vehicle 

control responsibilities. The applications that 

were assumed for the highway environment 

were largely partial automation rather than 

full automation, with the exception of a 

“safety pull over,” which is a system that would 

automatically take over full control of the 

vehicle and move it to the highway shoulder, 

where it would be automatically stopped 

if the driver were to become disabled. This 

appears to be an exceptionally challenging 

application. The applications selected for the 
39

urban environment were generally providing 

low levels of driver assistance, comparable 

with systems that are already commercially 

available on some cars. The applications 

defined for the dedicated lane environment 

are closer to an automated highway system, 

but in this scenario there is no reference to 

providing any physical protection against 

intrusion of debris or unauthorized vehicles, 

only a legal prohibition against use of the lane 

by unauthorized vehicles.

The SMART-64 project report created its 

own definitions of automated driving, 

cooperative driving, and autonomous 

driving, but these definitions are rather 

awkward and misleading. The project 

defined automated driving as a driver 

assistance system with partial automation 

of the driving functions and the driver 

being either in control or able to quickly 

resume manual control. The project 

defined cooperative driving as the use of 

ICT in conjunction with automated or nonautomated driving vehicles, overlooking the 

fact that any level of automation or driving 

assistance will of course have to depend 

on ICT (e.g., sensors, computers, software, 

and communications). The definition then 

mentioned V2V and V2I communications, 

with the implication that somehow these 

represent the totality of ICT, even though 

there are many other elements of ICT. 

SMART-64 defined autonomous driving 

as fully automated driving, with no human 

intervention in the driving process, and 

Complexity in automation

Environment

CACC

Automated 

lane 

keeping

Emergency 

braking

Safety

pull over

Mixed traffic 

+ highway

Mixed traffic 

+ urban

Dedicated 

lane

CACC

Automated 

Steering

Assist

Forward 

Collision 

Warning

Lane merge

Assist

Drowsiness 

warning

Contextual 

speed limit

Automated 

parking

Road 

pricing

Fuel Use

Lane

keeping

Figure 22. Chart. Automation concepts considered in the SMART-64 

project. NOTE: CACC = cooperative adaptive cruise control. © European Union
40

» Technical involvement (e.g., providing test 

facilities and a deployment roadmap and 

stimulating standards).

» Roadside infrastructure enhancements.

The authors of the SMART-64 project report 

then concluded that public benefits would be 

limited compared with the benefits of cooperative 

systems, creating an artificial dichotomy 

between automation and cooperation.

The private–sector–focused scenario assumed 

that the vehicle industry would build on 

current products, with government playing 

only a passive role (although the report 

acknowledged in passing that ideally both 

public and private sectors would take active 

roles). The private sector was assumed to be 

involved in:

» Defining and adapting to new legislation 

(including standardization).

» Aligning with societal and political needs.

» Quantifying economic benefits from 

diverse stakeholder perspectives.

» Accelerating technological developments.

The main focus of the private-sector–focused 

scenario would be on making automated 

declared this to be outside the scope of the 

project, which addresses a time horizon up to 

the year 2025 for private automotive vehicles.

SMART-64 also defined three institutional 

scenarios for the stimulation of automated 

driving, one led by government, one led 

by industry, and one based on “disruptive 

developments.” It is curious to note that 

there was no scenario involving coordination 

of government and industry activities, 

which would probably be the most likely to 

succeed. Subsequent discussion with one of 

the project leaders revealed that the absence 

of this scenario was intended to steer readers 

to draw that conclusion themselves by seeing 

the limitations of the strictly government–

centered and industry–centered scenarios.

The focus of the government–led scenario 

was on gaining societal benefits, stimulated 

by infrastructure investments. Suggested 

government actions included:

» Funding (e.g., direct investment or 

tax incentives).

» Facilitation (e.g., addressing liability, legal, 

and political challenges, promoting user 

acceptance, and developing evidence 

of benefits).

Figure 23. Chart. Automation applications and their deployment timescales assumed in SMART-64 project.

© European Union
41

driving systems both reliable and affordable. 

The authors expressed their doubts that the 

private sector would develop automated 

driving systems that depend on road 

infrastructure changes.

The disruptive developments scenario was 

based on the dream that artificial intelligence 

technology would somehow provide the 

ability to drive fully automated vehicles in 

mixed traffic, most likely motivated by the 

publicity generated from Google’s “selfdriving” car.

SMART-64 included a summary of driver 

assistance products that are already on the 

market, categorized as warning systems, 

assisting systems, and “toward CACC,” 

which is a rather odd classification scheme 

because this third category contains both 

warning and assisting systems. The review of 

the current state of the art made optimistic 

assumptions about the capabilities of these 

current systems relative to automated driving, 

which colored some of the conclusions and 

recommendations in the study. The review 

tabulated these in terms of the well-known 

“technology readiness level” (TRL) measure 

of technology maturity, without accounting 

for the higher levels of maturity and 

robustness that are needed when the driver’s 

role is reduced. The authors even claimed that 

“current technology is ready for autonomous 

(sic) driving on separate segregated lanes in a 

controlled environment,” citing the examples 

of automated people movers and the first 

generation PRT systems that are already in 

use, without recognizing the differences in 

costs and complexity when trying to apply 

this on a wider scale. They also assumed, 

erroneously, that these exclusive guideway 

systems use the same obstacle detection and 

sensor systems as advanced driver assistance 

systems for cars.

The authors of the SMART-64 report 

contended that dedicated lanes are not 

feasible on cost grounds and that “automated 

vehicles will have to be mixed with manually 

driven vehicles, at least in the early days.” 

They then introduced the eLanes concept 

from the CityMobil project but interpreted 

it to involve coexistence of fully automated 

and manually driven vehicles rather than the 

separation envisioned by the creators of 

the concept. This perspective appears to 

ignore the extreme technical challenges 

that would have to be solved to enable 

safe coexistence of fully automated and 

manually driven vehicles.

The authors of the SMART-64 project report 

explored several aspects of automated 

driving in more detail, as presented in the 

following sections.

Vienna Convention on Road Traffic

This set of rules, adopted by most European 

countries, includes several provisions 

regarding drivers’ control of vehicles that 

weigh against full automation of driving, 

unless the driver can maintain control by 

overriding the automation system. The 

researchers for the study noted that 

there are loopholes and opportunities to 

amend the Vienna Convention rules so 

that they need not serve as a permanent 

obstacle to automation. The authors of the 

report concluded that there is no need to 

adopt a strategy for handling the Vienna 

Convention rules on road traffic until there 

is an agreed-upon deployment staging 

strategy for road vehicle automation.
42

» Experiences from rail and aviation 

systems are not expected to be 

especially applicable because of the 

large differences in training of vehicle 

operators and constraints on the 

operating environments.

» Standards and New Car Assessment 

Program ratings could be used to ensure 

minimum performance and quality levels 

so that unsafe systems are not introduced.

Reliability

Automated system reliability was explored in 

the context of the ability of the driver to recover 

control quickly enough to avoid a crash. This will 

require clear definition of the responsibilities of 

the driver versus the vehicle provider. It was also 

recognized that additional work will be needed 

on developing fail-safe mechanisms, in-vehicle 

and I2V health checks, HMI systems to alert 

drivers about problems and to manage the 

control transitions, and infrastructure features 

to augment system safety.

Recommendations in the report for EC 

actions included:

» Technology R&D (e.g., fail-safe 

technologies, sensor fusion, and 

redundancy).

» Legislation.

» Driver interactions—how to keep the 

driver in the loop and transfer control.

» Stimulate standards and certification.

Controller Development

The report recognized the important 

challenges in software complexity and cost 

Liability

It was noted that different countries in 

Europe still have substantially different 

legal systems; thus, there is no consistency 

in how liability is handled across the 

continent. A substantial in-depth study will 

be needed to sort out these differences in 

legal systems and the diverse operational 

concepts of vehicle automation systems 

to determine how such liability would be 

handled. This is an important issue for 

vehicle manufacturers because they 

need to be able to market their vehicles 

throughout the continent and would 

be reluctant to proceed with market 

introduction until they knew that there 

would be a consistent and predictable 

legal environment for handling liability. 

This might require European legislation. 

Some additional issues to consider in terms 

of liability are as follows:

» It was suggested in the report that 

the easiest way to develop strategies 

for providing liability insurance for 

automated vehicles would be to start 

with fleet vehicle operations, in which 

there would be a business–to–business 

relationship between the vehicle owner 

and insurer. There was also a suggestion 

of a government-supported insurance 

pool to encourage initial adoption of 

automation technologies before there 

is a substantial body of actuarial data 

about the safety of the systems.

» Once automated systems are 

demonstrated to improve safety, vehicle 

OEMs could eventually be found liable 

for not implementing automation.
43

reduction before automation systems can be 

widely deployed, but it made unrealistically 

severe assumptions about the computational 

update rate that would be needed (assuming 

1 millisecond).

Drive-by-Wire Technology

The authors of the report devoted 

disproportionate attention to the technical 

issues associated with “by wire” actuation, 

without recognizing that the required actuation 

for vehicle automation can be accomplished by 

using less risky technologies that are already 

widely used on electric and hybrid vehicles.

Sensor Systems

The authors of the report enumerated the 

types of sensor technologies that would be 

required in vehicles and the infrastructure 

to implement automated driving; wireless 

communication was included as one of the 

sensor technologies. The authors adopted an 

optimistic view of the maturity of the current 

sensor technologies, without considering 

the challenges associated with adverse 

environmental conditions.

Positioning Technology

The authors of the report also reviewed the 

types of positioning system performance that 

might be needed for automated driving but 

underestimated the update rates that would be 

needed for good vehicle control performance.

Cross–Border Driving

Because European countries have so 

many borders that road vehicles would be 

expected to cross frequently, a section of 

the report was devoted to the issues that 

need to be resolved to ensure smooth and 

safe cross–border operations of automated 

vehicles. These issues include the need 

to establish well–defined standards to 

ensure interoperability of vehicles and 

the cooperating infrastructure where that 

is needed.

Interactions with Human Drivers

The authors of the SMART-64 project 

report focused on scenarios with partial 

automation—rather than full automation 

of driving—and included the statement, 

“The driver is and must stay in control; 

responsibility remains with the driver.” Yet 

parts of the report also addressed issues 

that arise with fully automated vehicles. 

The driver interaction research questions 

were identified as:

» What effect does higher automation in 

the vehicle have on the driver?

» How can the driver interface be 

improved without overloading the driver 

with information?

» How can standardization for automated 

vehicle control and interface design be 

achieved without legislation?

» How can driver training for automated 

systems be improved? 

» Should a gradual migration of skill be 

allowed or should some form of universal 

training be introduced?

» How should automated vehicles be 

integrated with other road users?

» Will other road users also require 

training about how to interact with 

automated vehicles?
44

trajectories of all the vehicles traversing the 

section of roadway. This site provides an 

outstanding data recording capability that 

can be used in experiments that investigate 

traffic flow stability and countermeasures 

for improving stability. This same stretch 

has continuous coverage by 5.9 GHz DSRC, 

based on 11 DSRC transceivers installed along 

the roadside, providing an environment for 

testing V2I and I2V cooperative strategies.

Advisory Acceleration Control 

Field Test

The Advisory Acceleration Control (AAC) field 

test was an innovative experiment conducted 

by TNO under SPITS auspices in which drivers 

of 48 vehicles were provided with a display 

(implemented using TomTom hand–held 

navigators reprogrammed for the purpose) to 

advise them whether to accelerate, decelerate, 

or maintain their current speed, based on use 

of an algorithm designed to dampen traffic 

shock waves. 

During a weekend period in February 2010 

when the A270 highway was closed to the 

public, these drivers were lined up in one lane 

of the highway, while another 48 vehicles 

in an adjacent lane were unequipped with 

driving aids. The vehicles at the head of the 

two streams of vehicles followed a prescribed 

speed profile, with speed variations intended 

to promote shock waves among the followers. 

The dynamics of the two traffic streams 

were compared by using the trajectory data 

extracted from the roadside video systems, 

and the advisory display was shown to reduce 

the severity of the shock wave. An example 

of these results is shown in the distance–

versus–time plots of figure 24.(21) in which the 

lighter color and higher slope of the plots on 

Dutch Programs

The Netherlands has several relevant 

current activities that address partial vehicle 

automation and some potential precursors, all 

with a very strong emphasis on cooperative 

systems. These activities were all showcased 

during the “automotive week” activities in 

Eindhoven in mid–May 2011. It is notable that 

these activities are most strongly driven by 

regional economic development interests 

centered in the North Brabant province 

around Eindhoven, which sees itself as the 

“Brain Port” for the country and the center of 

automotive industry activity. The multitude 

of projects in the Netherlands is confusing 

to sort out, particularly because some of 

the names are quite similar even when the 

projects and their participants are different. 

Strategic Platform for 

Intelligent Transport Systems 

The Strategic Platform for Intelligent 

Transport Systems (SPITS) was a consortium 

of 13 companies and universities funded 

by the Dutch Ministry of Economic Affairs, 

from July 2009 to June 2011, to position 

the Netherlands for a strong role in future 

European projects and to encourage 

commercialization of the results of prior 

projects. The work of SPITS includes the 

development of a unique test site along 

the A270 highway between Eindhoven and 

Helmond. Along a 5-km (3-mi) stretch of this 

highway, 48 video cameras were mounted on 

poles, providing continuous and overlapping 

coverage of all vehicle movements. The 

real-time video images were fed back to 

a control center where image processing 

software produced continuous traces of the 
45

the right (representing higher traffic speeds) 

indicate how the shock wave was attenuated 

by use of the AAC guidance system. This was 

meant to demonstrate a potentially near-term 

application that could smooth out traffic flow 

in the same way that CACC would, but without 

requiring that vehicles be equipped with the 

relatively expensive ACC control system.

Dutch Integrated Testsite for

Cooperative Mobility 

The Dutch Integrated Testsite for Cooperative 

Mobility is a new initiative, created in May 2011, 

to bring together diverse Dutch interests as a 

successor to SPITS, with a particular emphasis 

on becoming the European test site of choice 

for all future cooperative ITS services. It will, of 

course, need to compete with other sites for 

specific project opportunities.

Connected Cruise Control 

Connected Cruise Control is a project of the 

Ministry of Economic Affairs for providing 

individualized speed, lane selection, and 

gap advice to drivers to deter the formation 

of shock waves in traffic by smoothing 

out speed variations. This project is under 

development by a consortium of universities 

and companies, beginning in 2010 and aiming 

for commercialization of a product by 2013.

Connect and Drive

This project of TNO Mobility and Transport 

and the Technical Universities of Eindhoven 

and Twente has developed and tested a 

prototype cooperative ACC system, aimed 

at longer term implementation when there 

is a high market penetration of cooperative 

vehicles. Although it is expected that the 

first practical application will be for heavy 

truck platoons, Toyota Prius vehicles served 

as the demonstration platforms (figure 25)(22)

Figure 24. Photo. Distance–versus–time plot comparing a stream of 48 Advisory 

Acceleration Control vehicles (right photo) with 48 unequipped vehicles (left photo). © Netten, et al 

Figure 25. Photo. Cooperative adaptive cruise control 

platoon of Toyota Prius vehicles developed as part of 

the Connect and Drive Project.

© TNO Mobility and Transport (Bart, 

Scheepers), the Netherlands 
46

Shock Wave Mitigation 

with Mixed Equipped and 

Unequipped Vehicles

During the same period as the Grand 

Cooperative Driving Challenge, the SPITS 

A270 test site was used for another 

experiment, attempting to mitigate 

congestion shock waves by two alternative 

means: (a) giving some drivers detailed 

real-time in-vehicle advisories about their 

driving speeds; and (b) providing the same 

drivers with CACC speed control, with the set 

speeds commanded from the roadside. The 

advisory speeds for both of these strategies 

were determined in the same way, making 

use of the detailed real-time traffic data from 

the video monitoring of the 5–km (3–mi) test 

section of highway to identify potential shock 

waves being formed and then instructing the 

equipped vehicles what speed to travel for 

breaking up the shock waves. The people 

working on this project recognized that the 

intensive video monitoring infrastructure 

of this highway test section would not be 

replicable on normal roads, however this was 

being used to emulate the kind of data that 

could be available with widespread market 

penetration of probe vehicle monitoring.

and showed very good performance in the 

low-speed demonstration of four vehicles 

that was performed for visitors in May 2011. 

The parameters of the CACC system could 

be adjusted by using the vehicle’s touch–

screen display, which was reprogrammed 

for this purpose (figure 26).(16) These vehicles 

accomplished their cooperation by using WiFi 

communication, because DSRC radios were 

not available to the project team at the time 

they integrated the vehicle systems, but they 

recognized the need to migrate to DSRC and 

did so in subsequent work, using IEEE 802.11p 

and the ETSI (European Telecommunications 

Standards Institute) protocol stack.

Grand Cooperative Driving 

Challenge 

The Grand Cooperative Driving Challenge was 

an international competition that was inspired 

by the DARPA Challenges and organized by 

TNO and the High–Tech Automotive Systems 

program, with sponsorship from the local and 

regional governments around the competition 

site in Helmond, a suburb of Eindhoven. 

In contrast to the DARPA Challenges, this 

challenge depended heavily on V2V and I2V 

cooperation, requiring that the competing 

teams not only control their own vehicles 

well but also communicate good information 

to the vehicles from the other teams. This 

significantly raised the awareness of the 

competing research teams—11 university 

groups from throughout Europe—to the 

importance of cooperative systems and their 

advantages over autonomous systems.

The vehicles were staged through two 

scenarios, one representing urban traffic 

conditions (figure 27)(23) and the other 

representing highway traffic (figure 28).(23) 

The final competition was held in May 2011, in 

combination with several other cooperative 

system events, and was won by a team from the 

Karlsruhe Institute of Technology in Germany.

Figure 26. Photo. Touch-screen control panel for 

adjusting parameters of a cooperative adaptive cruise 

control (CACC) test vehicle. NOTE: RSU = roadside units, 

CC = cruise control, ACC = adaptive cruise control.

 © Shladover, S. (2012)
47

The experiment was performed with a string 

of 70 vehicles, 8 of which were equipped 

for infrastructure-cooperative ACC and 12 of 

which had driver advisory displays, scattered 

at fairly uniform intervals along the string of 

vehicles. The shock waves were deliberately 

induced by the lead vehicle in the string, 

which slowed down so that the driver could 

look at a roadside incident (which also made 

it more likely that the other drivers would be 

tempted to slow down to take a look). The 

trajectories of all the vehicles were recorded 

to see what effects could be achieved with 

the advisory system (with specially trained 

drivers instructed about following the advice 

so that they would be more likely to follow 

1 3 December 2012

Finish

Urban

Scenario

1

2

3

4

5

5

Start

Finish

Lane A

Lane B

GCDC

Participant n

Participant 1

Participant n+1

Participant n+2

Participant n+m

Start

End urban scenario

Disturbances

Shockwave

1 2 3

Highway Scenario

Figure 28. Diagram. Highway scenario of the Grand Cooperative Driving Challenge.

 © TNO Mobility and Transport, the Netherlands

1 3 December 2012

3 4

Finish

Accelerate

First vehicle

passing line

triggers green light

Accelerate

Start of 

scenario

Participant n

Participant 1

GCDC

Participant n+m

Participant n+2

Participant n+1

Lane A

Lane B

Line Up

Participants “randomly” 

distributed over two lanes

1 2

Urban Scenario

Figure 27. Diagram. Urban scenario of the Grand Cooperative Driving Challenge.

 © TNO Mobility and Transport, the Netherlands
48

relative to their predecessors, which the 

drivers are not able to determine on their 

own without assistance. The blue camera 

icons along the side of the roadway in figure 

29(24) show the locations of the video cameras 

that are used to monitor the trajectories of all 

the vehicles.

Figure 30(16) shows the monitors at the TMC, 

which display the distance–versus–time plots 

in real time during the experiment. To the 

right side of the right monitor in figure 30,(16) 

the white gaps represent the extra gaps in 

the traffic stream created by the equipped 

vehicles following the speed guidance, 

thereby breaking up the shock wave. The 

preliminary indications are that the CACC 

vehicles were somewhat more effective at 

dissipating the shock wave than were the 

vehicles with the guidance displays, which 

it than would be drivers from the general 

public) and with the CACC system. The 

locations and trajectories of the vehicles were 

observed from a traffic management center. 

Figure 29(24) shows one of the displays from 

the TMC, with the locations of the vehicles 

superimposed on an aerial photograph 

of the roadway, with red marks signifying 

equipped vehicles and green marks 

signifying unequipped vehicles. Note that a 

long sequence of unequipped vehicles was 

deliberately grouped at the start to get the 

shock wave triggered, and the increased 

density of the vehicles there is evident in 

the photo. The red marks and the green 

marks following them represent the mixture 

of equipped and unequipped vehicles, 

attenuating the shock wave by requiring the 

red vehicles to maintain appropriate gaps 

Figure 29. Photo. Aerial view of A270 test site with vehicle locations superimposed. 

© Google Earth

Figure 30. Photo. Real-time plots of distance–versus–time diagrams during an attempt to mitigate 

congestion shock waves.

© Shladover, S. (2012)
49

were more subject to the uncertainties of 

driver responses (even with specially trained 

drivers instructed to follow the guidance as 

well as they could).

French Programs

Although the French Transport and Research 

ministries have been supporting research 

on ITS topics for many years, relatively little 

of that research within the past decade 

has been directed toward the longer term 

issues of vehicle automation. Interest in 

automation is being revived within the 

vehicle industry, and it has remained 

strong among researchers all along. Recent 

increased research activity related to 

vehicle automation has been evident within 

economic competition channels rather 

than within more traditional transportation 

or research channels. The increased 

research activity has been motivated by 

concerns about energy saving, mobility, 

and preserving accessibility for senior and 

disabled citizens.

The central group for research on automated 

driving of road vehicles is the LIVIC laboratory 

in Versailles, France, now a part of IFSTTAR. 

LIVIC developed a useful chart that lists their 

active projects on automation and cooperative 

systems, as can be seen in figure 31.(25) The 

project names that are highlighted in red 

boxes are the most relevant to this review. 

The LIVIC researchers have been influenced 

by working with researchers from other 

countries on European projects, such as 

HAVEit, and have adopted the concept of 

protected eLanes, for example. They are in the 

process of forming a larger vehicle automation 

research cluster with other leading French 

research labs, including INRIA and the 

research groups of the Ecole des Mines.

One unique national project listed in 

figure 31(25) is Automatisation Basse Vitesse, 

a €5.5 million ($7.2 million) project that is 

Figure 31. Chart. Relevant current projects at France’s LIVIC laboratory. NOTE: ABV = Automatisation Basse Vitesse.

© IFSTTAR
50

vehicles would follow through electronic 

coupling with nobody onboard. This kind of 

operation could be performed on a specialpurpose dedicated roadway infrastructure 

that minimizes the complexity of the driving 

environment and the interactions with 

pedestrians and other vehicles.

France is an active participant in European 

field operational tests, and in addition to 

the EC-funded projects, they have also 

established their own field operational 

test project for cooperative systems, 

called SCORE@F, in collaboration with 

the European Drive C2X initiative. This will 

include eco–driving at traffic signals and 

driver assistance systems for safety but 

will not include fully automated driving, 

because that is still viewed as being too 

futuristic to be ready for use by naive drivers.

German Programs

KONVOI Project

The KONVOI project was sponsored by 

Germany’s Federal Ministry of Economics and 

Technology (not transport) as an examination 

of the impacts that a truck–platooning 

system could have on traffic flow, fuel 

consumption, and the environment. Because 

researchers for the CHAUFFEUR project 

had already performed extensive truckplatoon technology development and testing 

between 1996 and 2004, KONVOI began 

with the assumption that any technological 

problems were close to being solved. 

In this case, a research team from the RWTH 

Aachen University, the heavy vehicle and 

vehicle supply industry, and major trucking 

firms developed the project to evaluate 

focused on low-speed vehicle automation 

(the meaning of the French words that 

are abbreviated in its acronym). This 

project intends to improve fuel economy 

for vehicles driving in congested traffic on 

urban and suburban freeways. The project 

was developed based on the concept of a 

“secured road,” meaning that there should 

be communication and cooperation between 

vehicles and roadway infrastructure. This 

could include sensing technology and special 

markings on the infrastructure to facilitate 

vehicle automation, but the infrastructure 

should still be capable of being shared to 

some extent with conventional traffic. 

PARTAGE is a related project that is 

focused on sharing responsibilities between 

the driver and the automation system. 

This builds on the “co-pilot” concept in 

HAVEit, with a “decision unit” that shares 

responsibilities with the driver and could 

indeed override the driver’s decisions in 

some cases after warning him or her. The 

research is extending beyond the technical 

issues in sensor fusion, communication, 

and control in an effort to also deal with 

legal and standards compliance issues 

and assessments of impacts on traffic 

congestion and fuel consumption.

The French research institutes and 

automotive companies are also working 

on the development of vehicle automation 

capabilities that can be used in support of 

carsharing services, especially for electric 

vehicles with limited range. Within an office 

park or research campus, the shared vehicles 

could be deposited at locations that do 

not match well with the upcoming demand 

patterns. One employee manually driving a 

lead vehicle would collect the vehicles and 

act as their platoon leader, while the following 
51

how a truck platoon system could operate 

in practice on public roads. This project had 

about €4 million ($5.2 million) of government 

funding, plus industry contributions, which 

raised the total budget to approximately €5.5 

million ($7 million; similar in scale to the newer 

SARTRE project). KONVOI was active from 

mid-2005 to mid-2009, and the work is now 

complete. There is no direct follow-on project.

The technical implementation of the KONVOI 

platooning system was based on the 

integration of components and subsystems 

that were already commercially available or 

getting close to commercial availability and 

did not depend on any exotic technologies 

because the project partners believed that 

the technology was already relatively mature 

and close to deployable. The control design 

approach is conceptually very similar to 

the approach that PATH has adopted in the 

United States but with some differences 

in specific sensing technology. KONVOI’s 

concept of operations for application of 

the truck platoons in public mixed traffic, 

coexisting with other vehicles and drivers, 

was constrained by the need to acquire 

authorization from government agencies and 

safety certification authorities before they 

could conduct their tests. 

The target concept for KONVOI is of a 

platoon of up to four trucks that would 

drive in mixed traffic on the highway, with 

the driver of the first truck making the 

strategic maneuvering decisions for the 

platoon, using his own eyes combined 

with assistance systems to give warnings 

about potential hazards in the driving 

environment. The drivers of the following 

trucks would be in a passive mode, 

monitoring their trucks for problems and 

being prepared to intervene if necessary 

by taking over control in case of a failure or 

emergency. The goals of this truck platoon 

are to increase the capacity of the highway 

lane by enabling the trucks to use less space 

(running at shorter gaps) and reduce fuel 

consumption and greenhouse gas production 

by running them close enough together that 

they could save aerodynamic drag. 

The minimum allowable gap between trucks 

was set at 10 m (33 ft) based on analyses of the 

effects of cut–ins at highway entrance ramps, 

where hard braking of the following truck 

could be required. For the constant distance 

separation policy used here to support energy 

savings at all speeds, it is essential to have V2V 

communication to achieve string stability of 

the platoon. The researchers actually tested 

emergency braking maneuvers with two 

trucks on the test track, with the first truck 

decelerating at 0.7 g (7 m/s2

 or 22.5 ft/s2) and 

the second truck responding to that. During 

this braking maneuver, the gap between the 

trucks was reduced from 10 m (33 ft) to 5 m 

(16 ft) before they stopped because of the 

finite delay time before the second truck 

could apply its brakes, but they were still able 

to avoid a crash. This test was one of project’s 

more important accomplishments.

The lateral control of the KONVOI trucks 

was based on use of a wide-angle, multibeam laser sensor at the front of each truck, 

which detects the lane striping, measures the 

distance to the forward truck, and detects 

cut-in vehicles. With the wide field of view, 

the sensor can see the lane markings even at 

the shortest permitted gap between trucks 

of 10 m (33 ft; but that would not have been 

possible at the significantly shorter gaps of 

3–5 m (10–16 ft) used by Energy ITS in Japan 

or PATH to achieve their drag reductions). In 

this way, each truck follows the lane markings 
52

directly rather than performing an “electronic 

towbar,” that is, following the lateral motions 

of the preceding truck as the CHAUFFEUR 

project was doing. 

To change lanes, the planned operational 

concept was for the driver of the lead truck 

to look for a long enough gap in the adjacent 

lane for the entire platoon to make the lane 

change, to then activate his turn signal to 

alert all other drivers, and then for each driver 

to verify a safe gap next to his truck and press 

a button to confirm it. Although this was 

performed on the test track, the researchers 

were not authorized to test it on the public 

highway (and it does seem cumbersome 

and difficult to implement in practice). The 

drivers of the following trucks expressed a 

strong interest in having a live video feed of 

the forward view from the front truck so that 

they would know what was happening up 

ahead. It was not clear whether this would 

be useful in practice, but it would at least 

help the drivers feel more comfortable about 

their ability to make decisions. This concept 

would, however, impose a significant wireless 

communication burden.

After they performed an extensive set of 

tests on test tracks, the researchers tested 

the KONVOI trucks on public highways for 9 

days, acquiring about 3,300 km (2,000 mi) 

of driving data. Of this, 2,100 km (1,250 mi) 

of driving data were collected by using 

the full four–truck platoon, as shown 

in figure 32.(26) During these tests, the 

platoons were followed by a police escort 

vehicle that had flashing lights and a 

sign that warned drivers approaching 

from behind that these trucks were 

special test vehicles. This police escort 

interfered with the testing goal of obtaining 

completely naturalistic driving data about 

the way drivers of other vehicles would 

interact with the truck platoon. The police 

escorts believed that drivers did not pay 

any special attention to them and that they 

behaved largely as they would have under 

normal conditions. With this caveat, there 

were still 13 cut–ins into the truck platoon by 

other drivers during the highway tests (an 

average of once per 250 km (155 mi) or once 

in approximately every 3 hours of driving), six 

of which occurred when the gaps between 

the trucks were only 10–15 m (33–49 ft). 

The platoon control system was designed 

to split the platoon as soon as a cut-in was 

detected by the wide–angle laser sensors on 

each truck, and these splits were performed 

correctly each time they were required.

Researchers claimed that the trucks on the 

test track achieved some fuel-consumption 

savings even when they were driving at the 

10-m (33-ft) gap between trucks; however, 

there was no fuel-consumption savings in 

the tests on the public highway because the 

trucks had to vary their speeds to respond 

to traffic conditions and other vehicles 

on the road. The trucks’ control systems 

were designed to emphasize accuracy of 

gap control in vehicle-following (which is 

important for safety reasons, among other 

things). To achieve this accuracy, it was 

necessary to design the systems with a 

high bandwidth, which means that it makes 

frequent corrections and tends to be “busy,” 

which increases fuel consumption. This is 

Figure 32. Photo. Four-truck KONVOI platoon driving at 10-m 

(33-ft) gaps between trucks on a German autobahn. 

© Institut für Kraftfahrzeuge (ika), 

RWTH Aachen University
53

a fundamental trade–off in the design of 

such systems and indicates the difficulty of 

saving energy and greenhouse gas emissions 

when the equipped vehicles have to share 

the road with unequipped vehicles that do 

unpredictable things.

There are only limited technical papers 

in English about KONVOI, and because 

the project was funded by the German 

government, the final reports are written in 

German.(27) As a result, there are few good 

reference documents available to cite; 

however, based on detailed discussions 

with several key people who worked on the 

project at RWTH Aachen, the following main 

observations are worth considering:

» Researchers concluded from the start 

of the project that it would be essential 

to operate the truck platoons in a mixed 

traffic environment, because there have 

been no prospects for constructing 

new dedicated truck lanes or other new 

infrastructure in Germany. This imposed 

significant technical constraints on the 

system design and operational concept.

» Although KONVOI researchers say that 

the technology is relatively mature and 

close to deployment, when considering 

what roles the drivers could play in 

practice and how reliable the system 

would actually need to be, it is clear 

that there is a disconnect between desire 

and reality. The researchers understand 

that none of the systems are close to 

the level of reliability needed to permit 

a KONVOI platoon to drive with full 

automation of the following trucks for an 

extended period of time. The safety of 

the system is based on the drivers being 

able to constantly monitor the truck’s 

operations to detect any anomalies, but 

the researchers recognize that it is not 

possible for drivers to take on such a 

responsibility for an extended driving 

period in the real world because of basic 

human factors limitations. Furthermore, 

during the tests, the only drivers who 

were authorized to drive the trucks on 

the public highways were the ones who 

were directly involved in developing the 

system and who knew its peculiarities 

intimately. Professional truck drivers from 

trucking fleets did not drive the trucks on 

the public highways.

» The need to mix the trucks with the rest 

of the traffic was a political imperative and 

goal for the project, but at some level, the 

KONVOI research team also recognized 

that it was an impediment to achieving 

the hoped-for efficiency benefits. The 

traffic dynamics generated by all the 

other vehicles imposed disturbances on 

the truck platoon that prevented it from 

smoothing out its driving profile enough 

to actually save significant fuel. The cut–ins 

required expanding and contracting the 

gaps within the platoon, by decelerating 

and then accelerating, subsequently 

interrupting constant-speed cruising. 

» There were additional political and 

regulatory impediments specific to 

Germany and Europe that would have 

to be changed before a KONVOI type of 

system could be integrated into public 

operation. The short gaps between 

trucks were below what is legally 

permitted for vehicle-following, so those 

rules would have to be changed (these 

rules are more rigid and stricter than 

in the United States), and the Vienna 

Convention on road traffic in Europe 
54

also requires that the driver always 

be in complete control of his or her 

vehicle. Although these issues do not 

apply so directly in the United States, 

they do indicate some of the challenges 

to implementation that will have to be 

considered. 

» In sum, there are doubts as to whether the 

technical and non-technical issues facing 

the KONVOI system can be resolved 

successfully, because they are pulling the 

system design and operational concept in 

opposite directions (regarding the mixing 

of the truck platoons with general traffic). 

The same conflicts might be found 

during U.S. attempts at automated truck 

platooning, and U.S. researchers will need 

to find ways of resolving these conflicts 

within their own environments.

German Study on Legal 

Aspects of Road Transport 

Automation

The German Federal Highway Research 

Institute, BASt (equivalent to FHWA’s Turner–

Fairbank Highway Research Center), has been 

leading a study of the legal implications of 

road transport automation under German law, 

in collaboration with representatives of the 

German automotive industry. A BASt report 

(in German) was published early in 2012, and 

some informal presentations of its findings 

have been given in English at international 

meetings during the final quarter of 2011 and 

have attracted strong interest in Europe. This 

study is very significant because it combines 

technical factors, human factors, and legal 

expertise to make explicit determinations 

about what aspects of automation systems are 

clearly legal, clearly illegal, or in the gray area in 

between. For those aspects that fall within the 

gray area, BASt is currently identifying what 

research is required to resolve the ambiguities. 

The study is focused on automation in mixed 

traffic operations rather than in segregated 

or dedicated infrastructure, because this is 

where the issues are most complicated and 

where they are expected to first arise.

The most important initial contribution of this 

study appears to be a carefully developed 

definition of five different levels of vehicle 

automation, which was an essential 

prerequisite to addressing legal issues 

(figure 33).(28) These levels are:

1. No automation—Driver is in complete 

control of the vehicle.

2. Driver assistance—Partial automation 

of either longitudinal control (e.g., ACC) 

or lateral control (e.g., lane-keeping) 

while the driver controls the other 

functions and remains fully engaged in 

the driving task.

3. Partial automation—Both longitudinal 

and lateral control are automated, but 

the level of automation is sufficiently 

limited in capability that the driver 

needs to continuously monitor its 

behavior and be prepared to take over 

control at any time.

4. High automation—Both longitudinal 

and lateral control are automated but 

at a higher level such that the driver no 

longer needs to continuously monitor its 

behavior and only needs to be prepared 

to take over control within a “certain” 

(currently unspecified) time interval.

5. Full automation—The system has a 

sufficiently high level of automation 
55

that when it requests the driver to 

regain control (because of a condition 

it cannot handle), and the driver fails to 

respond, it can return to a minimum-risk 

condition (such as stopping the vehicle) 

by itself. (Fortunately, BASt avoided the 

common misuse of the term autonomous

to represent this level of automation.)

Researchers for the BASt study found the 

first three levels of vehicle automation to 

be within the current legal requirements of 

the German road traffic codes, based on 

the driver’s duty to drive safely, to monitor 

the traffic and vehicle status, and to be 

prepared to override the vehicle automation 

in case of inappropriate system behavior. 

The two higher levels are not consistent with 

the current legal requirements because of 

the reduced driver role. It was also unclear 

whether a lane-keeping system that permits 

“hands–off” operation would be permissible, 

with more human factors research needed 

to determine whether this would adversely 

affect driver vigilance.

The BASt study group also thought that it 

would be important to conduct more research 

on both human factors and technical issues 

to determine the ability of drivers to recover 

control quickly enough to ensure safety at 

different driving speeds, as indicated in figure 

34.(29) In this case, it would be important to 

compare the driver recovery times with the 

length of time during which the automation 

system could remain safe following a failure 

in each speed range.

The BASt group produced an effective set of 

Venn diagram graphs to illustrate the potential 

safety benefits and disbenefits of automation 

systems. The diagrams use a blue circle to 

represent present-day crashes associated 

with manual driving hazards, and a red circle 

to represent the changes in crashes that occur 

when the automation system is doing the 

driving. The BASt group’s general approach is 

illustrated schematically in figure 35,(16) where 

the overlaps between the circles represent the 

crashes that could potentially be eliminated 

by automation. The crescents outside the 

overlap area represent the crashes that would 

still occur after the introduction of automation. 

The relative sizes of the areas in the Venn 

diagram illustrate the net safety effects of 

automation in a way that can help facilitate 

outreach to the general public. Outreach to the 

general public was another important theme 

in the BASt study, because this was identified 

as the necessary mechanism for fostering the 

legal changes needed to authorize vehicle 

automation through the legislative process.

•Full automation: The system takes over longitudinal and 

lateral control completely and permanently. In case of a 

take-over request that is not followed, the system will 

return to the minimal risk condition by itself.

• High automation: The system takes over longitudinal 

and lateral control; the driver must no longer permanently 

monitor the system. In case of a take-over request, the 

driver must take-over control with a certain time buffer.

• Partial automation: The system takes over longitudinal 

and lateral control, the driver shall permanently monitor

the system and shall be prepared to take over control at 

any time.

• Driver Assistance: The driver permanently controls 

either longitudinal or lateral control. The other task can be 

automated to a certain extent by the assistance system.

• Driver Only: Human driver executes manual driving task

Tom M. Gasser

BASt-Expert-Group definitions of

vehicle automation-degrees:

degree of automation

Figure 33. Chart. BASt definitions of levels of automation. 25th July 2012 slide: 12/ 20

© Gasser, German Federal Highway Research Institute (BASt)
56

The BASt study also addressed the liability 

issues, identified separately as product 

liability and road traffic liability. In the 

product liability category, defectiveness

was identified as the key concept, which 

depends on the instructions that are 

provided to the user to condition his or her 

expectations about system performance. 

These could be conveyed through the 

owner’s manual and by other means as 

well. This concept was used to distinguish 

reasonably foreseeable misuse from 

abuse by the driver. The manufacturer 

of the system would be responsible for 

Congestion

driving

assist

Motorway

assistant

(LaneKeeping

+

ACC)

ACC

Stop & 

Go

automation level

assisting highly automated fully automated

maximum speed range

low:

parking, 

slow manoeuvres

medium: 

Congestion,

city driving 

high:

highways, express highways, 

motorways

Parking

assist

(only

lateral)

Parking

assist

(lateral + 

Longitud.)

Motorwaychauffeur MotorwayPilot

partially automated

ACC

LKAS:

Lane -

Keeping

Assist

Source: BASt Expert Group

Figure 34. Chart. BASt mapping of automation levels into operating speeds for safety. 

(NOTE: Assist = assistance, ACC = adaptive cruise control.)

© Gasser, German Federal Highway Research Institute (BASt)

Automation avoiding most current crashes,

but generating some new ones, producing

a net decrease in crashes

Automation avoiding some current crashes,

but creating enough new ones to produce

a net increase in crashes 

Automation avoiding most current 

crashes, but generating no new crashes

Automation avoiding some current crashes,

but creating many more new crashes

Figure 35. Diagram. Venn diagram of automation safety benefits and non-benefits, inspired by the BASt study. 

NOTE: Existing crashes are represented by the blue circle and changes in crashes associated with automation are 

represented by the red circle. Existing crashes that could be avoided by use of automation are thus represented 

by the overlap areas.

© Shladover, S. (2012)
57

consequences from the former but not 

the latter. Under current German law, the 

manufacturer would be liable for crashes 

that occur at the two higher levels of 

automation unless the crash could be 

determined to be solely the fault of the other 

vehicle or driver. The road traffic liability issue 

was identified to be particularly associated 

with platooned operations, in which each 

vehicle is no longer entirely self–sufficient, 

but its safety depends to some extent on the 

actions of the other vehicles in the platoon.

The identified research needs included:

» Determine human ability to interact with 

automation systems in real road traffic.

» Determine performance and reliability 

of driver–state–monitoring systems that 

may be needed to determine driver 

condition in real time.

» Define functional safety of automation 

systems at two higher levels.

» Determine human capabilities to take 

control over automation under fault or 

emergency conditions.

» Determine driver skill loss from use of 

automation.

» Identify any new driver skills or training 

that would be needed to use automation 

systems safely.

» Review national road traffic codes to 

determine what changes are needed to 

produce sufficient harmonization to sell 

the same vehicles throughout Europe.

» Identify demands of automated systems 

on road infrastructure (e.g., quality of 

road markings).

Private Automotive 

Industry Activities

The automotive industry in Europe has shown 

more interest in automated driving within 

the past few years than at any time since the 

completion of the PROMETHEUS program 

in 1994. Because the industry does not trust 

the infrastructure providers to be reliable 

providers of cooperative infrastructure, 

this interest has been shown unofficially 

rather than officially, through publicity 

demonstrations of autonomous partially 

automated driving. However, companies 

have been gaining practical experience 

with the operation of automated vehicles 

in specialized applications, such as robots 

driving test cars on test tracks or training 

race car drivers in “optimal” strategies for 

driving specific race tracks. BMW even 

staged media demonstrations of automated 

driving for a test course in September 2011. 

Mercedes has presented videos at several 

public meetings of their test vehicles being 

driven by strap-on robotic vehicle controllers 

in precisely controlled close encounters, which 

would be unsafe and insufficiently repeatable 

if the vehicles were driven by humans.

European Commission 

Workshop on Automation 

in Road Transport

The EC organized a workshop in Brussels, 

Belgium, on October 26, 2011, to present and 

discuss the current state of the art and future 

needs in road transport automation. This was 

a rare opportunity to bring together the key 

people interested in the topic area throughout 

Europe, representing the vehicle industry 
58

and research institutions, as well as sponsors 

and participants in the projects associated 

with both DG–CONNECT and DG–RTD. 

The workshop was heavy on presentations, 

leaving very little time for question-andanswer sessions and interactive discussion, 

but it still revealed some contrasts that will 

have to be harmonized. At the most basic 

level, the DG–CONNECT work is strongly 

oriented toward the private automobile 

industry, whereas the DG–RTD work is multimodal in its orientation, with an emphasis 

on public transit and trucking applications. 

This difference in perspectives colored the 

attitudes that were expressed about some 

of the key automation attributes, such as full 

versus partial automation and operations 

in dedicated lanes versus in mixed traffic. 

There were about a hundred attendees, 

who represented a broad cross-section of 

European ITS interests.

Juhani Jääskeläinen of DG-CONNECT 

(then still known as DG-INFSO) opened the 

workshop with a strong statement in support 

of the notion that “the time has come” for 

automation to be considered seriously as a 

means for improving Europe’s road traffic 

safety, mobility, and environmental impacts. 

The other options short of automation have 

been exhausted by now, but more gains 

are needed. Because there has already 

been a substantial amount of research on 

automation issues, Jääskeläinen is eager to 

find automation options that can be tested 

and deployed relatively soon. He wants to 

do what is good for the competitiveness of 

Europe’s automobile industry and for the 

health of its cities.

The bulk of the workshop contained a series 

of presentations about current European 

projects related to automation and crosscutting issues associated with automation, 

with time for only a few questions after each 

presentation. The presentation slides are 

posted online at

http://ec.europa.eu/information_society/

activities/esafety/2011/automation_workshop/

index_en.htm.

Rather than reciting the details of all the 

presentations, which tended to cover many of 

the topics already reported in the preceding 

sections of this report, some of the highlights 

from the workshop and new insights are 

summarized as follows:

» The SMART-64 project was only one 

of the topics under discussion, not the 

centerpiece of the meeting. It used the 

term smart lanes to represent what 

appears to be the same concept as the 

eLanes defined in the CityMobil project 

(sponsored under a different DG). In 

these lanes, the level of automation 

could be increased, but the degree of 

automation increase and the degree of 

separation from the rest of traffic were 

still not completely defined.

» The main hurdles to overcome in pursuit 

of automated vehicle deployment were 

recognized to be (a) human factors (e.g., 

driver interactions with the automation 

systems and driver ability to remain 

sufficiently alert to intervene); (b) liability; 

and (c) the need to enhance technical 

performance (e.g., sensors, driver 

interfaces, driver status monitoring, data 

communication, fail-safe systems).

» There was considerable discussion about 

the need to clearly define and demonstrate 

automation technology benefits to the 

driver (or to those purchasing a vehicle) in 
59

an effort to motivate the purchase of the 

system. Increasing the level of enthusiasm 

by the general public will also be important 

in obtaining political support for some 

of the legal changes that are likely to be 

needed in Europe. The benefits also need 

to be demonstrated to the infrastructure 

owners and insurance industry so that 

they will be amenable to playing a role in 

the deployment of automation systems. 

The automotive people generally saw 

the opportunity for drivers to safely 

perform non-driving tasks while driving 

(e.g., texting, Web surfing, etc.) as the 

major selling point, but at the same time 

this is in conflict with the need to keep 

the driver engaged to handle adverse 

conditions that the state-of-the-art 

systems cannot handle.

» There was considerable discussion about 

driver training needs and driver skill 

loss. The training issue was particularly 

important because of concerns about 

the difficulty of making the driver 

interfaces so completely intuitive 

(especially regarding the different 

possible modes of operations and the 

transitions among those modes) that 

no training would be needed, versus the 

practical challenges of implementing a 

training regimen. This is one aspect in 

which introduction in systems used by 

professional drivers could help pave the 

way for applications to be used by the 

general driving public.

» The HAVEit project leader made the 

important observation that the automation 

systems that keep the driver in the control 

loop have less stringent redundancy 

requirements and can make use of less 

expensive technology, which would have 

to be traded off against the reduction of 

comfort and convenience benefits. He also 

noted that the systems implemented in the 

demonstrator vehicles for HAVEit, which 

do not permit the driver to disengage 

from attention to the road for more than 

2 seconds, would not be marketable to 

the public; rather, it will be necessary to 

have systems that can tolerate longer 

periods of driver disengagement without 

becoming unsafe in case of failures.

» A multi–dimensional conflict in goals and 

practicality became evident, considering 

the expressed needs for systems to 

be affordable (in both vehicle and 

infrastructure elements), to provide 

attractive comfort and convenience 

to users, and to be safe. One of the 

main reasons that additional R&D work 

is needed is to determine whether 

acceptable combinations of these 

attributes can be achieved, given that 

improvements in one of these dimensions 

lead to losses in one or more of the other 

dimensions. For example, the automobile 

industry representatives believe that 

systems must be able to operate in 

mixed traffic, because they do not expect 

protected lanes to be made available (for 

reasons of construction cost and right–

of–way limitations), but at the same time, 

none of their technologies are yet able to 

operate in a sufficiently safe manner in a 

mixed–traffic environment.

» One suggested approach to get around the 

mixed–traffic challenge is to provide timedependent segregation of automated 

traffic from the rest of the traffic. The 

context for this suggestion was nighttime 

operation of trucks on toll roads, where 

the road operator would be responsible 
60

for verifying that any vehicles admitted 

to the road are qualified and would take 

on the liability for any untoward events. 

The driver or vehicle operator would pay a 

premium for the privilege of a guaranteed 

arrival time.

» Early developments in the automotive 

systems are expected to focus on low–

speed automation for congested traffic 

scenarios, where the consequences of 

failures are less severe than at higher 

speeds, and it may be possible to allow 

more time for the driver to intervene when 

a problem arises.

» In contrast to the automotive industry 

representatives, the public transit industry 

representatives were strongly in favor of 

dedicated, protected rights–of–way for 

operation of automated vehicles. The 

most extreme example of this is PRT on 

dedicated special–purpose guideways, 

but they also suggested separated rightsof-way for CyberCars. Because of the 

high density and well-developed mass 

transit systems in the large European 

cities, public transit representatives see 

the most promising applications for 

automated transit systems to be in the 

small–to–medium cities or on the outskirts 

of the larger cities, where the automated 

systems could provide feeder service to 

the high–capacity mass transit systems.

» An important economic incentive for 

truck automation would be the potential 

to relax hours of service restrictions 

if drivers were not responsible for the 

continuous control of their vehicles while 

their vehicles operated in the automated 

mode. This could increase the drivers’ 

productivity and earning power.

» One of the main impediments to the 

deployment of transit automation 

systems is the lack of common 

European standards for certification 

of these systems. The certification 

requirements and approaches differ 

dramatically from place to place, 

which places a severe burden on the 

developers of systems, who have to 

meet incompatible requirements.

» Anna Schieben from the German 

aerospace research center DLR, one of 

the main human factors experts from 

HAVEit, presented an excellent summary 

of the human factors considerations 

and design challenges associated with 

partial automation of road vehicles. She 

emphasized the importance of focusing 

on the transitions between automation 

levels and ensuring that these transitions 

be designed to reinforce drivers’ 

correct mental models of the relative 

responsibilities that they and the system 

have. She also raised the issue of the 

challenges faced by other road users 

(especially pedestrians and bicyclists), 

who are accustomed to communicating 

with vehicle drivers based on eye contact 

but who would not be able to do that 

with automated vehicles. There is not yet 

any well-established knowledge about 

how well and how quickly drivers will be 

able to regain control of their vehicles 

in emergencies if they are significantly 

distracted by other activities (such as 

texting or Web surfing). Surveys of drivers 

who participated in the HAVEit driving 

simulator experiments were very favorable 

about almost all aspects of the automated 

driving experience with the exception of a 

concern that it could be “sleep inducing.”
61

» The BASt study of the legal aspects of vehicle 

automation under German law drew strong 

interest from the conference attendees, 

including requests that it be translated into 

English. This study appears to be the most 

comprehensive current treatment of a topic 

that has induced anxiety in most people 

who think about vehicle automation.

At the end of the workshop, there was a 

proposal to establish a European working 

group on automation, which would include 

representatives of the different parts of the 

EC, for developing a roadmap to define future 

work that will be needed under the next calls 

for proposals for EC research programs. There 

were no definitive answers to the various 

questions posed during the workshop, but 

a substantial number of topic areas were 

discussed and recorded. 

The Working Group on Automation in Road 

Transport was established in response to 

this need for defining future work. The 

group began meeting in the spring of 2012 

under the general structure of the European 

“iMobility Forum,” the stakeholder 

group that promotes deployment of ITS 

technologies. It is one of five parallel 

working groups that address specific 

ITS topics (the others being Clean and 

Efficient Mobility, Digital Maps, Vulnerable 

Road Users, and Nomadic Devices). 

The Working Group on Automation in 

Road Transport is considering a variety 

of automation functions that would 

be needed in four different operating 

environments for automated vehicles and 

identifying the cross-cutting issues that 

need to be resolved.
Current Asian Activities in 

Cooperative Vehicle–Highway 

Automation
63

Japan’s Energy ITS Project 

The most ambitious fully automated 

driving activity appears to be occurring 

in Japan’s Energy ITS project, which has 

been developing and testing a platoon of 

three fully automated trucks for close to 5 

years. This project, under the sponsorship 

of METI through its New Energy Technology 

Development Organization (NEDO), has 

been funded at the equivalent of about 

$12 million per year for 5 years. The work 

is being conducted by researchers at 

multiple universities, with coordination and 

management by the Japan Automobile 

Research Institute (JARI) but with little direct 

involvement by the truck manufacturers. 

The primary goal is to attain energy savings 

(CO2 reductions) through the reduction of 

aerodynamic drag by operating trucks in an 

electronically coupled platoon at shorterthan-normal gaps, with additional objectives 

of improving highway traffic flow and safety. 

Because of Japan’s rapidly aging population, 

its truck fleet operators are concerned about 

future shortages of truck drivers, which 

could be alleviated if the following trucks in 

the platoon could indeed be driverless.

The operational concept for this system 

has gone through some changes, 

motivated by political pressures from the 

sponsoring agency. Originally the project 

was planned to evaluate both a mixed–

traffic and a dedicated–lane approach for 

truck platooning. After some evaluation, 

the researchers decided to focus on the 

dedicated-lane scenario based on technical 

feasibility considerations, but then the 

sponsors directed them to switch their 

attention to the mixed–traffic scenario. After 

several years of development activities, the 

project manager saw problems with the 

feasibility of the mixed–traffic scenario, 

based on its mixed treatment of driver roles 

and responsibilities (unable to control but 

still in the control loop in an ambiguous 

way). At present, the project manager does 

not see a clear way past this challenge, 

because operation of fully automated 

platoons without drivers in the following 

trucks on dedicated lanes will not be 

possible until the future and would involve 

significant complications in assembling 

and disassembling the platoons in special 

staging areas.

The target trucks for this work are 25–ton 

single–unit trucks, which are the typical type 

of heavy truck used for over-the-road freight 

hauling in Japan. The trucks have been 

retrofitted with an extensive suite of sensors, 

actuators, computers, and displays, and their 

cargo compartments have been equipped 

as mobile office space, with computer racks, 

desktops, displays, and seats for visitors to 

receive demonstration rides. Researchers 

tested the trucks on a section of the New 

Tomei Expressway before it was opened 

to public traffic, but most testing and 

demonstrations have been performed at 

the test track of the Agency for Industrial 

Science and Technology, part of METI, near 

Tsukuba City. The researchers provided a 

demonstration of these trucks to attendees 
64

of the active safety conference, FAST-Zero, 

in September 2011.

The intended operations of the Energy 

ITS project truck platoon system are 

summarized in figure 36,(30) indicating that 

all of the trucks are expected to be driven 

automatically while in the platoon, although 

the drivers would be responsible for the 

lane-changing maneuvers associated with 

entering and leaving the platoon.

1

Ahead Vehicle Following Vehicle

Coupling/decoupling Semi-auto Semi-auto

Gap distance within platoon 10m

Control Lane-keeping Machine vision Machine vision

Vehicle speed ACC

・Laser

・Radar(76GHz)

 CACC

・Laser

・Radar(76GHz)

・5.8GHz V2V Communication

Gap distance

Obstacle avoidance Emergency Braking

3Lane-Tracking Control

・Lane recognition

・Steering control

4Closed Gap Distance Control

・Gap distance detection

・V2V Communication

5Obstacle Avoidance Control

・Vehicle recognition and distance detection

・Changing lane or stopping

1Coupling/Decoupling

2Vehicle Speed control

The Specification of Experimental Trucks

Figure 36. Presentation slide. Energy ITS truck platoon definition of capabilities. 

NOTE: V2V = vehicle-to-vehicle communication, ACC = adaptive cruise control, 

CACC = cooperative adaptive cruise control.

© Sadayuki Tsugawa

The components and subsystems that 

were added to the trucks to implement the 

automated platoon functions are summarized 

schematically in figure 37.(30) Note that two 

different sensor technologies are used for 

forward ranging, both laser and millimeter 

wave radars. The laser radar has a very wide 

field of regard so that it can be used to detect 

cut-in maneuvers by cars or other trucks (as 

was demonstrated successfully). When an 

unauthorized vehicle (a private car) cuts 
65

into the platoon, the truck behind it breaks 

away from the platoon and follows the cut–in 

vehicle at a much larger gap, using a basic 

ACC strategy. When the intruding vehicle 

departs, the following truck can re-connect to 

the platoon. The steering actuators and V2V 

communication systems are redundant for 

safety purposes. The lane-position detection 

is performed by using video cameras that 

face down at the front and rear of the truck 

so that the two separate measurements can 

be used to identify both lateral displacement 

and yaw angle relative to the solid lane 

marking on the left side of the truck. A laser 

scanner system for lane–marker detection 

has also been tested and will be added as a 

redundant source of lane position information. 

For safety considerations, the braking rate of 

the first truck is limited to substantially less 

than the braking capabilities of the following 

trucks. The control computers have also been 

designed for safety considerations, with each 

© Sadayuki Tsugawa

Figure 37. Diagram. Automation equipment installed on Energy ITS trucks. NOTE: GPS = global positioning system, 

IMU = inertial measurement unit, V2V = vehicle-to-vehicle communication, HMI = human–machine interface. (財)日本自動車研究所

JARI NEDO自動運1転・隊列Energy 走行プロジITS ェクトAutomated Platoon Project

Configuration of Experimental Vehicle 

-

Millimeter wave radar

Laser Radar Vehicle controller

V2V Communication Antenna

Lane detection sensor

2 redundant Steering Motor

GPS Antenna +IMU

Base Trucks: 25t heavy duty truck manufactured by HINO.

Trucks equip with steering and braking system activated by computer.

HMI
66

truck equipped with two dual–processor 

computers provided by a railway signal 

maker. This increases cost and complexity 

but greatly reduces the likelihood of a 

catastrophic system failure.

The performance requirements for the 

truck platoon system are summarized in 

figure 38.(30) Emergency braking at 0.4 g 

(4 m/s2 or 12.9 ft/s2) was demonstrated for 

visitors in September 2011, and the higher 

braking rate of 0.5 g (5 m/s2 or 16.1 ft/s2) 

is planned for later stages of the project. 

The 0.4 g (4 m/s2

 or 12.9 ft/s2) braking 

rate is hard enough that passengers feel 

significant pressure as their bodies press 

against their shoulder belt restraints.

The Energy ITS team has developed a 

variety of scenarios to prove the feasibility 

of the maneuvers needed to form and 

break a platoon, as shown in figure 39,(30)

and they demonstrated those scenarios 

in September 2011. In the first scenario, 

a third truck joined a two-truck platoon 

in the middle. To accommodate this, the 

(財)日本自動車研究所

JARI NEDO自動運1転・隊列Energy 走行プロジITS ェクトAutomated Platoon Project

Controllability of experimental Vehicle 

 Test Site Speed

Controllability

Lane tracking Gap distance control within Platoon 

At cruising At acceleration 

 (0.05G)

At deceleration 

(0.5G)

Oval Test track

(Straight lane)

80km/hr Within ±0.1m Within 㼼1.0m Within+0.5 m Within -2.0m

Highway under the 

construction 

・curvature:3,000m

・Gradient: 2.0%

80km/hr Within 㼼0.15m Within 㼼1.0m Within +0.5m Within -2.0m

Lane Tracking Platooning Emergency Braking

Figure 38. Presentation slide. Performance requirements for

Energy ITS truck platoon system.

© Sadayuki Tsugawa

1

Demonstration Scenario

Test Demonstration Scenario Outline of Control Process

1 Coupling of three vehicles from two vehicles. ◆ Split of two vehicles with the engagement.

◆ Enlargement of gap distance up to 35m.

◆ Cut in front of second vehicle.

2 Platoon with three vehicles at a speed of 

80 km/h.

◆ Gap distance of 15 m at speed of 80 km/h.

3 The cutting of other vehicles into the platoon ◆ Detection of the cut-in vehicle.

◆ Decoupling of vehicles.

◆ Deceleration and maintaining safe gap distance.

4 Emergency braking for collision avoidance. ◆ Maintaining gap distance under large deceleration.

Figure 39. Diagram. Maneuver scenarios for Energy ITS project truck platoon. 

NOTE: 80 km/h = 50 mi/h.

© Sadayuki Tsugawa
67

following truck in the platoon increased 

its following distance to 35 m (115 ft) to 

leave enough space for the new truck 

to enter, and they then formed a new 

platoon. The steady cruising of the second 

scenario was performed at a 15-m (49-ft) 

gap, although the target gap for the end 

of the program is 10 m (33 ft). In the third 

scenario, an unauthorized non-equipped 

vehicle cut into the gap between the second 

and third trucks, but this was detected by 

the wide-angle laser radar on the third 

truck, which proceeded to increase its gap 

so that it followed the intruder vehicle at 

a safe gap by using ACC car following. 

The final scenario was the emergency 

braking already mentioned. An additional 

scenario that was not demonstrated to 

visitors was a coordinated lane change 

by the entire platoon to avoid a vehicle 

stopped in its lane. 

The goal of the Energy ITS project is, of 

course, drag reduction to reduce CO2 

emissions. In support of this goal, researchers 

conducted computational fluid dynamics 

simulations to predict the extent of the drag 

reduction before full-scale tests could be 

performed under all conditions of interest. 

Some of the results of these simulations are 

shown in figure 40,(30) together with some 

early results from test–track tests of the fullsize trucks. The colored plots on the left of 

figure 40(30) show visualizations of air speeds 

and pressures around the truck platoon. 

The plot on the upper right of the figure 

shows the estimated reductions in the drag 

coefficients of each truck at the minimum 

gap of 4 m (13 ft). Because the aerodynamic 

drag accounts for only about half of the 

truck energy use at highway speeds, these 

percentage reductions are much larger than 

the reductions in energy use. The plot in the 

1

Estimation of CO2 Reduction by Platoon 

Speed Contours (longitudinal center section)

Cp Contours (longitudinal center section) 

Relative Cd value rate

(single vehicle as 100 percent)

Vehicle 3Vehicle 2 Vehicle 1

Simulation under the condition of vehicle speed of 80 km/h and 

gap-distance of 4–12 m

Aerodynamics simulation of the platoon

Relative Cd value rate 䢪䢧䢫

䢲 䢶 䢺 䢳䢴 䢲

䢷

䢳䢲

䢳䢷

䢴䢲

䢴䢷

䣉䣣䣲 䣆䣫䣵䣶䣣䣰䣥䣧 䢪䣯䢫

䣔䣧䣦䣷䣥䣶䣫䣱䣰 䣱䣨 䣨䣷䣧䣮 䣅䣱䣰䣵䣷䣯䣲䣶䣫䣱䣰䢪䢧䢫

䢳䢲

Simulation

Vehicle1

Vehicle3

Vehicle2

Platoon

Experimental

Figure 40. Presentation slide. First predictions of aerodynamic drag effects of

Energy ITS project truck platooning, compared with experimental results on full–scale trucks. 

NOTE: 80 km/h = 50 mi/h, 4 m–12 m = 13 ft–40 ft, Cd = drag coefficient, Cp = pressure coefficient.

© Sadayuki Tsugawa
68

request of the truck drivers, it includes 

live video of the first driver’s forward view, 

which is transmitted to the drivers of the 

two following trucks. This display screen 

is shown in figure 41(16) as a picture that was 

taken before the trucks started to move. In 

addition to the display screen in the truck, the 

driver is also expected to monitor three types 

of information displays on the back of the 

preceding trailer, as shown in figure 42.(16) The 

three colored lights at the lower center of the 

trailer have been coded to represent a large 

number of different operating conditions, 

based on different patterns of colors for the 

center and outer lights and whether they are 

illuminated steadily or flashing.

The Energy ITS program has not yet 

succeeded in stimulating strong interest in 

the Japanese trucking fleets, who would 

be the end users of the system. Although 

Japanese trucking fleets are intrigued by 

the potential energy savings and reductions 

in driver labor costs, they are concerned 

Figure 41. Photo. In-vehicle display screen of a following truck in the Energy ITS platoon.

© Shladover, S. (2012)

lower right corner of figure 40(30) converts 

these results to estimates of fuel consumption 

savings as a function of vehicle–following gap. 

The results of test-track experiments with the 

full–scale truck platoon at a 10-m (33-ft) gap 

are plotted for comparison with the predictions. 

The second truck had the largest fuel savings, 

whereas the third truck saved slightly less fuel. 

The 14–percent average fuel saving for the 

entire platoon shown here was somewhat 

higher than the trend of what was predicted 

from the simulation. Note that even the 

first truck saved about 10 percent of its fuel 

consumption by being coupled in the platoon 

at a 10-m (33-ft) gap.

One aspect of the Energy ITS truck platoon 

system that is not yet well developed is the 

driver interface. There is a complex display 

screen in each truck, which includes much 

technical information of interest to the 

researchers developing the system, but 

it is likely to be overwhelming for a truck 

driver in real–world operations. At the 
69

about the complications of forming a platoon 

among trucks from different fleets, especially 

when the energy–saving benefits depend on 

their position within the platoon.

Toyota’s Platooning 

Development Work

Toyota Motor Company has developed 

and tested a platoon of three Lexus LS460 passenger cars that follow each 

other closely to reduce fuel consumption. 

Toyota has described this work in a few 

conference papers but has not provided any 

demonstrations of the system to visitors. This 

system uses frequent V2V communication 

to coordinate longitudinal motions of the 

vehicles and includes both forward– and 

rear–facing millimeter–wave radars on each 

vehicle to provide redundant information 

about the range and range rate between 

successive vehicles. Toyota reported string 

stability of vehicle-following control, with 

10-m (33-ft) gaps and spacing errors of 1 m 

(3.3 ft) or less, including decelerations up to 

0.4 g (4 m/s2

 or 12.9 ft/s2). These vehicles did 

not include automation of lateral control.

Published results show impressive fuel 

savings from this system, which was 

optimized for fuel economy.(31) The 

aerodynamic drag reductions were reported 

in the 40 percent range for the following 

vehicles and in the 8–9 percent range for 

Figure 42. Photo. Rear view of Energy ITS truck

with three information displays. 

LED text status display

Three-light display

indicating position of

truck in platoon

Three-light display, with

pattern of colors indicating

operating condition

Reector to aid sensors

© Shladover, S. (2012)
70

the leading vehicle at a 10-m (33-ft) gap. 

Even at a 20-m (66-ft) gap they were still 

reporting 25 percent drag reductions for 

the following vehicles. The second vehicle 

saved somewhat more than did the third 

vehicle when direct fuel consumption 

measurements were recorded, in the 8–10 

percent range (compared with 1–2 percent 

for the leading vehicle) at 10-m (33-ft) 

gaps, with gradual declines in savings as 

the gaps were increased in 5-m (16-ft) 

increments to 30 m (98 ft). 
Comparison with

Current U.S. Status
72

technical documentation of this vehicle was 

presented at the 2011 ITS World Congress 

in Orlando, FL, combined with a public 

demonstration of the vehicle (which was 

also exhibited very prominently at the 2010 

Shanghai World Expo).(32) The EN/V showed 

sophisticated short–range obstacle detection 

and avoidance and automated platooning 

capabilities, including completely unmanned 

and remote–controlled operations, which 

appear to exceed the technical capabilities 

of the analogous but more highly publicized 

European developments.

Much media attention has been attracted 

by the DARPA Challenges for autonomous 

automated vehicles and the subsequent 

announcement by Google that it is 

experimenting with autonomous automated 

vehicles on public roads in the vicinity of its 

headquarters. A variety of university research 

groups have also been working on autonomous 

automated driving research, but these activities 

are outside the scope of this review.

Similarities and 

Differences Between 

Overseas and U.S. 

Situations

This review of current international status on 

road vehicle automation has revealed some 

significant similarities and differences 

between the situations overseas and in 

the United States. Resources to support 

new developments are tight everywhere, 

but the current level of activity appears 

to be higher overseas and the planning 

horizons are longer.

U.S. Activities 

Although the United States established a 

clear position of international leadership in 

CVHAS in the mid-1990s, the level of activity 

in this area has declined significantly since then. 

There have been several R&D efforts continued 

in recent years but at relatively modest funding 

levels. The following experiments have used 

full–scale vehicles with partial or full control of 

driving functions and V2V or V2I cooperation:

» Transit bus lateral guidance and steering 

control—University of California PATH 

Program and University of Minnesota ITS 

Institute, with support from the Federal 

Transit Administration, ITS Joint Program 

Office, and their respective State 

Departments of Transportation.

» Heavy truck longitudinal platoon control—

University of California PATH Program, 

with support from FHWA’s Exploratory 

Advanced Research Program.

» CACC—University of California PATH 

Program, with support from FHWA’s 

Exploratory Advanced Research Program, 

Caltrans, and Nissan.

There has also been a simulation study of the 

operation of arterial intersections with fully 

automated vehicles—using a slot reservation 

protocol to provide system–level coordination 

of their movements—by the University of 

Texas at Austin with support from FHWA’s 

Exploratory Advanced Research Program.

General Motors has entered the CyberCar 

world with their development of a twoperson, two-wheeled dynamically balanced 

vehicle called the EN/V (pronounced envy) 

in collaboration with Segway. The first 
73

Similarities 

The growing use of hybrid–electric and 

all–electric powertrains has increased 

the in-vehicle electrical power availability 

and voltage significantly, making it easier 

to add electronic and electro-mechanical 

subsystems, such as the sensors and 

actuators needed for automated 

driving. Electronic actuation systems for 

steering, braking, and engine control are 

becoming standard equipment on more 

vehicles, leading to increased production 

economies of scale.

The research teams working on automation 

have encountered some of the same primary 

operational concept dilemmas as the NAHSC 

did in the 1990s, without resolving them. 

These dilemmas are as follows:

» To what extent do automated vehicles 

need to be segregated from general non–

automated traffic to ensure their safety?

» How much of the vehicle control 

responsibility should be transferred from 

the driver to the vehicle automation 

systems and under which conditions?

» Is it better for automated vehicles to 

be totally autonomous, or is it better 

for them to communicate and actively 

coordinate maneuvering with each other 

and/or with guidance or even some 

degree of control from the infrastructure? 

 

Institutional issues, such as uncertainties 

about liability exposure, are impeding more 

active development and implementation 

of automated driving systems. Vehicle 

manufacturers are reluctant to provide 

functions that could remove the driver 

from the vehicle control loop without some 

assurance about their liability exposure in 

the event of a crash. In Europe, the situation 

is further complicated by the Vienna 

Convention and legal systems that handle 

this issue differently, motivating the need for 

European–level harmonization of policies and 

possibly legislation.

Differences 

» The primary motivation for applications 

of vehicle automation in Europe and 

Japan is saving energy and reducing 

CO2 emissions, whereas the primary 

motivations in the United States have 

been associated with mobility, safety, and 

driver convenience.

» The primary public sector support for 

vehicle automation system development 

in Europe and Japan has come from 

agencies whose missions are oriented 

toward economic competitiveness, 

the information technology industry, 

or more general research and 

technology enhancement. By contrast, 

transportation technology support 

in the United States has historically 

come from the U.S. Department of 

Transportation (or Department of 

Energy), which are more directly focused 

on the improvements in transportation 

measures of effectiveness or energy 

efficiency and self-sufficiency.

» The European thinking about driving 

automation has been colored 

significantly by the Vienna Convention 

on Road Traffic, which specifies a 

uniform set of rules and policies. Some 

of the Vienna Convention language 
74

the United States has funded very 

little work on automation within the 

past decade after establishing an 

international leadership role in this area 

in the 1990s.

Implications of These 

Contrasts for Future

U.S. Actions

The United States pioneered thinking about 

and development of road traffic automation 

systems for several decades, from the GM 

Futurama of the late 1930s(8) through the 

NAHSC research and demonstration of the 

late 1990s. During the past decade, Army 

research, the DARPA Challenges, and the 

ensuing Google development work have 

advanced technologies for individual vehicleoriented automation, largely independent of 

traffic considerations. At the same time, the 

levels of activity in road traffic automation 

have increased significantly in Europe and 

Japan, to the extent that at this point in time 

they probably have the leading expertise in 

the world in several key areas:

» Automated truck platooning

(Energy ITS in Japan).

» Automated buses (several European 

projects).

» PRT (e.g., ULTra PRT at Heathrow and 

2getthere at Masdar).

» Human factors and partial automation 

concepts (HAVEit project in Europe).

The sponsors of the European and Japanese 

work have strong interests in industrial 

about driver responsibilities has loomed 

large over automation discussions 

in Europe, although these concerns 

appear quaint from a U.S. perspective, 

because the Convention does not apply 

in the United States (or Japan) and can 

be amended if necessary.

» European and Japanese auto 

manufacturers have already introduced 

a wider range of advanced driver 

assistance systems across a wider 

range of vehicle models, including 

those in moderate price ranges, in their 

home markets than in the United States. 

This means that drivers in those countries 

have been exposed to more sophisticated 

warning and control assistance systems 

than their U.S. counterparts, in large 

part because they have shown more 

willingness to pay a higher price to gain 

those greater capabilities.

» European and Japanese projects 

have been focusing their attention 

primarily on partially automated 

systems rather than fully automated 

systems and have tended to start from 

the assumption that new dedicated 

lanes will not be available for use by 

automated vehicles. This appears to be 

a consequence of their higher density 

urban development patterns and high 

urban land costs. In the United States, 

with somewhat lower density and land 

costs, significant attention has been 

given to automated vehicles that could 

be physically segregated from other 

road users.

» European and Japanese projects have 

increased their emphasis on automation 

issues within the past 4 years, whereas 
75

competitiveness and in developing their 

ability to export products to the rest of the 

world. Unless the United States invests some 

effort in automation systems soon, it will have 

no choice but to import the systems from 

Europe and Japan when it needs them.

The European and Japanese systems, 

however, have been developed based on 

somewhat different requirements, needs, 

and economic and societal constraints 

derived from the characteristics of their 

transportation systems. For example, the 

density of development and land costs in 

Europe and Japan are substantially higher 

than in the United States, which leads 

them to reject the concept of dedicated 

lanes for automated vehicles a priori. The 

automobiles currently being sold in other 

countries are substantially better equipped 

with advanced driver assistance systems 

than are U.S. vehicles (and indeed most of 

the vehicles that have these systems in the 

United States are imported from Europe or 

Japan). This means that the incremental 

costs of adding automation capabilities are 

likely to be smaller in Europe and Japan, 

because they are starting from a higher 

baseline. Both of these factors tend to tilt 

toward more vehicle-intensive solutions in 

other countries than what may be ideal for 

U.S. applications.

The United States still retains some important 

strengths relative to Japan and Europe in the 

field of automation:

» Availability of comprehensive traffic 

safety and crash data to provide more 

insight into traffic safety and crash 

causality specific to the U.S. environment. 

As a result, the safety–oriented system 

designs can be targeted most effectively 

at solving the most important and relevant 

safety problems.

» A well–developed transportation human 

factors research community that can 

focus on designing systems that are safe 

and easy to use, without creating new 

safety or usability problems.

» A substantial research community with 

vehicle automation knowledge and 

experience developed over decades of 

work in both the road transportation and 

military domains.

» A road network with a relatively high 

percentage of travel on limited–access 

highways, where it is likely to be simplest 

to implement automation technologies.

» Recent and current projects that can 

provide the technological foundations for 

new developments (GM’s EN-V, Google’s 

driverless cars, PATH’s automated 

trucks and buses and CACC, GM’s 

Exploratory Advanced Research 

project on partial automation).

» System engineering approaches and 

expertise, to design and develop solutions 

to problems rather than solutions looking 

for problems.

The United States can build on the 

combination of its extensive heritage of 

experience and capabilities relative to 

automated road transport, its current 

areas of international leadership, and the 

knowledge being developed in current 

programs in other countries to develop 

a robust program in automated road 

transportation. The focus should be on 

areas in which U.S. needs differ from the 

needs of other countries and where it can 
76

control of a vehicle after they have been 

engaged in non-driving activities for an 

extended time.

» Pursue more in–depth work on truck 

platooning to complement current 

activities in Japan and Europe. This 

should include refining the concepts of 

operation for truck platooning systems 

to address both urban and intercity 

applications, experimental work to 

develop reliable quantitative data about 

the fuel and emissions-saving potential of 

the concepts, and benefit–cost studies to 

support the definition of business cases 

for further development and deployment.

» Seek opportunities to collaborate with the 

European and Japanese programs where 

synergies can be identified. The technical 

issues are sufficiently challenging that it 

should be to the benefit of everybody to 

distribute the needed work among the 

experts on all continents so that progress 

can be accelerated.

build on the strengths that it already has. 

Suggested actions include:

» Conduct concept studies of a range 

of automation applications to address 

transportation problems in the United 

States in an effort to identify which could 

be most beneficial. This should be done to 

establish an “application pull” approach 

to automation system development, in 

contrast to some of the international 

activities which have been more of a 

technology push.

» Build on the BASt study of legal 

issues in Germany, focusing on the 

differences between German and 

American law, to establish what the 

realistic legal issues and constraints 

are in the United States.

» Build on the recent GM studies of driver 

interactions with partially automated 

vehicles to develop a systematic set of 

data regarding drivers’ ability to resume 
References
78
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Transportation Systems, Orlando, FL.
Office of Operations Research and Development

Turner-Fairbank Highway Research Center

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