NIST Automated Vehicle Communications Overview

David Wollman (david.wollman@nist.gov)

Deputy Division Chief, Smart Connected Systems Division
NIST AV Communications Team

Ed Griffor

https://www.nist.gov/programs-projects/automated-vehicles-and-av-communications

Dave Wollman Tom Roth Chunmei Liu Lotfi Benmohamed Bob Bohn

Wendy Guo Usman Fiaz Hadhoum Hajjaj Yishen Sun Davide Pesavento

Wesley Garey, Evan Black, 

Samantha Gamboa Quintiliani, 

Aziza Ben Mosbah, et al.

Chenli Wang (postdoc, 

departed NIST)

Tao Zhang

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https://www.nist.gov/programs-projects/automated-vehicles-and-av-communications

AV Communications +

• Prior years’ Automated Vehicle efforts 

(AV Safety Measurement, Operational Envelope 

Specification, Teleoperation, incl. workshops 

and stakeholder engagement) helped to 

establish foundation for NIST-wide AV effort.

• CTL team leads the AV Communications 

project within the NIST SERI program; CTL staff 

also contribute to other systems areas.

• Co-simulation

• Communications network modeling

• Systems integration testbed design/demo

• Teleoperation

• Cyber/Communications protocols analysis

• AI/Trustworthiness

• Traffic infrastructure

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Stakeholders: ADS Technical Working Group

• NIST (IoT) Cyber-Physical Systems organized two workshops 

• Consensus Safety Measurement Methodologies for 

Automated Driving System (June 2019)

• Automated Driving System Safety Measurement 

and Operational Design Domain (July 2020) 

• Automated Driving System Technical Working Group 

(ADS TWG) initiated in 2020, and has been meeting since to 

develop foundations for assessing AV performance (see Ed Griffor, lead)

• NIST introduced the concept of 

an operating envelope specification

(OES), a structured description of the 

operating environment for driving.

• The OES supports calculationbased reasoning for vehicle 

performance in that environment, 

with testing and certification 

applications and in real-time 

driving.

https://nvlpubs.nist.gov/nistpubs/Special

Publications/NIST.SP.1900-301.pdf

https://www.nist.gov/publications/workshopreport-consensus-safety-measurementmethodologies-automated-driving-system

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Stakeholders: Teleoperation Consortium

• NIST Vehicle Teleoperation Forum (November 2020) 

resulted in formation of Teleoperation Consortium. 

• NIST has Board Member (Tao Zhang) on Teleoperation 

Consortium (Bob Bohn, NIST Liaison; Scott McCormick, Pres)

• Teleoperation Guidelines document on vocabulary, 

use cases, and communication technologies for 

Teleoperated Vehicles is anticipated to be published 

in December 2023. https://www.nist.gov/news-events/events/2020/11/nistvehicle-teleoperation-forum

https://www.teleoperation.org/ 

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Outline

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• AV Communications context

• Communications paths in vehicles

• V2X [including 5G NR and Sidelink]

• Developing AV comms network modeling capabilities (co-simulation)

• Use case: V2V Communications and Security/Privacy

• ns-3 network simulator; V2X extension to ns-3

• Use case: Emergency Electronic Brake Lights

• Integrating AV communications with Systems Interaction Testbed

• ROS 2 extension for ns-3

• Co-simulation of ns-3 using ROS 2

• Measurement Framework (initial concept)

• Behavioral competency

• Future Directions
Perspectives on AV Communications

• Current Vehicles

• Vehicle Operational Functions rely on 

onboard sensors for detection

• Motivation for AV communications requires 

clear benefits/value, economics

• Leverage 20+ years of AV communications R&D

• Future Connected Automated Vehicles

• Growing community agreement that 

communications will be increasingly 

important for safe AV operation and 

Cooperative Driving and Tactical Functions

• Mixed environment (human drivers/AV) 

anticipated for a long time – safety 

• Some AV and AV Communications Challenges

• Timing and Latency Adequacy

• Testing Methodology

• Spectrum, Infrastructure, Smart Cities

• Regulatory (incl. New Car Assessment Program)

• Trustworthiness – Safety, Security, Privacy, 

Reliability, Resilience 

Images: NHTSA

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Systems in the Driving Environment

Communication

Environment

Vehicle

Dynamics

Road / Weather 

Conditions

Automated 

Driving System Sensor Model

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Onboard Comms

• CAN

• Ethernet (TTE)

• Wi-Fi

• Bluetooth

Offboard Comms (V2X)

• 4G LTE (C-V2X)

• 5G NR (Sidelink + Cellular), 6G

• DSRC

• Wi-Fi (FOTA)
Simulation of One Car

Communication Paths in Vehicles

Sources of network interference (perturbations) in the driving environment will 

impact network performance and lead to an impact on overall vehicle performance.

Antenna

(V2X) In-Vehicle Network

Sensing

(In Vehicle)

Automated

Feature Actuation

V2X Network

Driving Environment ( Road / Weather / Traffic / ... )

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V2X in AV from 4G LTE to 5G NR

• 3GPP specifies four V2X application types for 4G LTE [1]: 

V2V, V2P, V2I, and V2N.

• AV community envisions advanced use cases and 

services (e.g. [2]), and 3GPP specifies service 

requirements for 5G NR in six areas [3]:

• General Aspects: interworking, communicationrelated requirements valid for all V2X scenarios 

• Vehicles Platooning

• Advanced Driving

• Extended Sensors 

• Remote Driving

• Vehicle Quality of Service Support

1. 3GPP TS 22.185 V17.0.0. In Technical Specification Group Services and System Aspects; 

Service Requirements for V2X Services.

2. H. Bagheri et al., "5G NR-V2X: Toward Connected and Cooperative Autonomous Driving," 

in IEEE Communications Standards Magazine, vol. 5, no. 1, pp. 48-54, March 2021, doi: 

10.1109/MCOMSTD.001.2000069.

3. 3GPP TS 22.186 V17.0.0. In Technical Specification Group Services and System Aspects; 

Enhancement of 3GPP support for V2X scenarios.

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Sidelink and Integrated V2X Communications

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Network

infrastructure

Source Destination

Network

infrastructure

Sidelink

Source Destination

Uu Uu

PC5

• 3GPP specifies sidelink for D2D and V2X communications, which provides direct link between vehicles.

• Direct link enables ultra low latency communications, which is critical in V2X communications, and allows out-ofcoverage communications. 

• Sidelink and cellular network infrastructure can be integrated easily to serve a variety of AV use cases.
3GPP V2X Feature Evolution

NR Proximity Services (ProSe)

Rel-17 +

Direct Communication

Broadcast, Groupcast, Unicast

UE-based Relays

UE-to-Network, UE-to-UE

Direct Discovery

Peers, Members, Relays

NR Sidelink

Sensing

Channel awareness

Inter-UE coordination 

Feedback

Feedback-based retransmissions

Channel State Information

Scheduling

Semi-persistent

Per-packet

Multicast

Connectionless

Distance-based

QoS

Similar to Uu interface

Enhanced for SL

Spectrum flexibility

Numerologies 

Extended modulations

Rel-16 +

NR Vehicle to Everything 

(V2X) Services

Rel-16 +

V2X Communication

Broadcast, Groupcast, Unicast

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Outline

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• AV Communications context

• Communications paths in vehicles

• V2X [including 5G NR and Sidelink]

• Developing AV comms network modeling capabilities (co-simulation)

• Use case: V2V Communications and Security/Privacy

• ns-3 network simulator; V2X extension to ns-3

• Use case: Emergency Electronic Brake Lights

• Integrating AV communications with Systems Interaction Testbed

• ROS 2 extension for ns-3

• Co-simulation of ns-3 using ROS 2

• Measurement Framework (initial concept)

• Behavioral competency

• Future Directions
V2V Communications and Security/Privacy

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Message Authentication

• Basic Safety Messages (BSMs) and Signal Phase 

and Timing (SPaT) messages from road 

infrastructure or other vehicles must be 

cryptographically signed to ensure integrity and 

authenticity

• IEEE 1609.2 – WAVE Security Services

• All vehicles that receive a message must verify 

that it was signed by a valid certificate

• Certificates are issued (and revoked) through 

the Security Credential Management System 

(SCMS)

• Signing and verification introduce delays due to 

computational cost of cryptographic operations

• Future Goal: studying the impact of BSM 

authentication on vehicle reaction time through 

co-simulations

WSMP

PDCP

RLC

MAC

PHY

V2V sidelink

channel

Basic Safety Message

(SAE J2735)

5G NR

(3GPP)

Signing Verification

Safety 

application

WAVE security

(IEEE 1609.2)

Safety 

application

WAVE security

(IEEE 1609.2)

WSMP

PDCP

RLC

MAC

PHY
V2V Communications and Security/Privacy

Source: USDOT

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Certificate Management

• The Security Credential Management System 

(SCMS) is responsible for issuing and revoking 

certificates of road users

• It employs pseudonym certificates for the 

vehicles’ onboard units (OBUs) to ensure 

the user’s privacy.

• Privacy not a large concern for Roadside Units (RSUs).

Source: USDOT

• Future Goal: Analyze the SCMS algorithms and 

protocols for potential privacy shortcomings 

and performance/scalability bottlenecks.
• ns-3 is a discrete-event network simulator that is:

• open-source and maintained by a worldwide community

• focused on the simulation of Internet and cellular systems

• A V2X extension for ns-3, available at https://apps.nsnam.org/app/nr/, was developed for 5G NR 

cellular networks and V2X communications which incorporates fundamental PHY-MAC NR features 

aligned with 3GPP NR Release 16:

• NR frame structure

• PSCCH and PSSCH multiplexing

• resource allocation for NR V2X using mode 2 (autonomous resource selection)

• both sensing-based semi-persistent and dynamic scheduling

• blind- and feedback-based HARQ retransmissions

• Sidelink Control Information (SCI) update

• compliance with scenarios and channel models based on 3GPP TR 38.885 documentation

• A ROS extension for ns-3 was developed to enable these V2X features to be used in a co-simulation 

with automated driving simulators (such as CARLA, MathWorks Automated Driving Toolbox, ...)

https://www.nsnam.org/

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V2X Extension for Network Simulator (ns-3)
AV Communications Use Case Scenario

warning to driver hard braking

V2V communication

Status

Defined simulation scenario details.

Implemented the defined scenario.

Performing sensitivity analysis to network parameters.

• Evaluating Emergency Electronic Brake Lights (EEBL) 

use case from SAE J2945/1 / ETSI TR 102 638 V1.1.1.

• Investigate ability of V2V to lower collision risk.

• Leverage previously-developed ns-3 simulation 

platform and link level simulator for 5G New Radio 

communications.

• Utilize co-simulation to incorporate onboard and 

offboard systems.

AV Communications Use Case Scenario: Emergency Electronic Brake Lights (EEBL)

ego vehicle

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Demo – Communication Only on for ALL Vehicles

250 ms Processing Delay

18 * Demo built upon Netsimulyzer, available at https://apps.nsnam.org/app/netsimulyzer/.
Outline

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• AV Communications context

• Communications paths in vehicles

• V2X [including 5G NR and Sidelink]

• Developing AV comms network modeling capabilities (co-simulation)

• Use case: V2V Communications and Security/Privacy

• ns-3 network simulator; V2X extension to ns-3

• Use case: Emergency Electronic Brake Lights

• Integrating AV communications with Systems Interaction Testbed

• ROS 2 extension for ns-3

• Co-simulation of ns-3 using ROS 2

• Measurement Framework (initial concept)

• Behavioral competency

• Future Directions
• A ROS2 extension for ns-3 was developed to allow co-simulation of 

ns-3 models with different automated driving simulators:

• bridges separate ns-3 and ROS2 processes using TCP/IP

• synchronizes the ns-3 simulator time with the ROS2 /clock topic

• uses virtual links (0 delay) to inject ROS2 messages into the ns-3 network

• tracks vehicle positions (in ROS2) to update ns-3 node mobility models

• integrated with the V2X extension and the EEBL scenario

• This extension was used to integrate ns-3 with Autoware and CARLA 

for the demo shown in the systems interaction presentation.

• The code is still being prepared for public release. When complete, it 

will be released as open-source software on the NIST GitHub 

(https://github.com/usnistgov)

ns-3 with V2X Extension

ROS2 Extension for ns-3

ns-3 gateway

ROS2 Node

nsns3::Node -3 node

(1 car)

virtual link

TCP/IP

ROS2 Network

DDS

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Co-Simulation of ns-3 using ROS

position

velocity

acceleration

V2X

messages

ns-3 models each car as a mobile 

node and simulates V2X (incl. V2V) 

communications using those nodes

ROS 2 provides the time reference 

for ns-3 and manages data transfer 

between the different simulators

An automated driving simulator 

models the physical environment, 

control systems, and the physical 

response of each car

(Robot Operating 

System 2)

Vehicle

Simulator

(CARLA + Autoware)

ego vehicle
Integration with Systems Interaction Testbed

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Goal: Integrate AV Communications 

network simulation capabilities and 

measurements into Systems 

Interaction Testbed (hardware in 

loop, development vehicle)
Integration with Systems Interaction Testbed

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COMMUNICATIONS 

(ways comms impact performance)

Timing, frequency, latency to meet 

application requirements

Infrastructure, protocols, availability, 

coverage, more 

Data requirements, 

information structure / comms

Trustworthiness 

(Security, Privacy, Safety, 

Resilience, Reliability)

Cooperative operations, 

remote control

Human and human-AI interactions, 

adaptability, AL/ML-federated learning

Environmental factors, 

impact on comms
Outline

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• AV Communications context

• Communications paths in vehicles

• V2X [including 5G NR and Sidelink]

• Developing AV comms network modeling capabilities (co-simulation)

• Use case: V2V Communications and Security/Privacy

• ns-3 network simulator; V2X extension to ns-3

• Use case: Emergency Electronic Brake Lights

• Integrating AV communications with Systems Interaction Testbed

• ROS 2 extension for ns-3

• Co-simulation of ns-3 using ROS 2

• Measurement Framework (initial concept)

• Behavioral competency

• Future Directions
• The Automated Vehicle Safety Consortium (AVSC) 

program of SAE Industry Technologies Consortia (SAE ITC) 

proposed a new safety methodology for automated 

vehicles based on an enumerable set of vehicle behaviors.

• The dynamic driving task can be considered a combination 

of vehicle behaviors, and a safety case can be constructed 

by demonstrating whether a vehicle has competency in all 

the behaviors required to execute its intended functions.

• Behavioral Competency in maintaining a lane, for example, 

may be demonstrated by acceptable “wandering distance” 

from the lane center and speed less than the speed limit

Behavioral Competency

Concept cartoon indicating essential 

parameters for maintaining a lane

Example Behavior Specification

Maintaining a lane Driving along roads predictably and consistently

maintaining proper lane position with respect to 

designated lane markings and speed limits.
• Signal temporal logic (STL) can be used to express a specification 

for a vehicle behavior

• For example, a simple STL specification for maintaining a lane:

• Vehicle performance can be assessed against the specification at 

either runtime or post-execution to measure competency

• Competency measured by competency index (n), a real number 

with range [-N,N], where the more positive the better

• The value of N depends on the system parameters

Measuring Behavioral Competency vehicle state

“Alwaysmaintain speed 

less than the speed limit”

“Always maintain distance from lane 

center less than the threshold” AND STLSpec
Future Directions

• Complete sensitivity analysis to V2X communication configurations and 

parameters for emergency braking scenario.

• Compare vehicle performance with perception only, communication only, 

and perception plus communication.

• Co-simulate both on-board and off-board communications.

• Explore 5G NR V2X communication mechanisms to enhance AV performance 

with focus on safety.

• Optimize the communication system to enhance AV performance.

• FY24 Milestone: Develop new capabilities in ns-3 network simulator 

required to study the effects of perturbations on AV communications and 

integrate these capabilities into the systems interaction testbed.

• FY24 Milestone: Develop and demonstrate measurement metrics and 

methods for analysis of AV communications impact on overall system 

performance using a representative use case in systems interaction testbed. 27