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Non-Motorized Behavior Changes and Communication with Autonomous Vehicles


With Autonomous Vehicles (AV) being introduced into cities and intermixing with human-driven cars, non-motorized corridor users (pedestrians and bicyclists) must interact with a computer driven car instead of a human driver. Non-motorized users at times rely on eye contact, hand motions, or audible dialogue with human drivers to accomplish roadway crossings. The elimination of human interaction and communication with AV technology could influence the behavior of non-motorized users, introducing unpredictability with the elimination of the human element in the driver seat. Additional concerns about the lack of human interaction and vulnerable road users such as the visually impaired or children who rely on the interaction to validate the safety of their behaviors or human drivers to react to unpredictable behavior strengthen the need for enhanced communication between AV and non-motorized users to create predictable behavior.

Identifying training strategies, tools and applications that can guide and influence non-motorized user behavior could reduce unpredictability and improve safety by minimizing the human factor in the interaction, and enhance communication between AV and pedestrians or bicyclists. Many non-motorized users have hand held devices (smart phones) that could provide a means for communication or advanced warning. External features on the AV or the behavior of AV may be used to influence behavior.

Perceiving and predicting pedestrian behavior is a critical piece of the pedestrian-AV interaction, suggesting that models of pedestrian behavior may feed into the protocol for contextual warnings or messages for non-motorized users.

Understanding the differences in information requirement based on the environment is also critical. Context, such as traffic volume, number of lanes, setting, socio-economic status, gender, age, access to technology, and number of non-motorized users could influence behavior and communication. Features may be context-dependent: an audible warning, for example, might be helpful on a rural road at a greenway crossing, but might be useless in a dense urban environment where warnings would occur all the time. Identifying context-sensitive opportunities in the built environment could guide non-motorized user behavior in the interaction with AV as well as provide public agencies with planning guidelines for future facilities that facilitate positive non-motorized user behavior with AV interactions.


The objectives of this research are as follows: · Identify what is needed for non-motorized users to make a decision when interacting with a vehicle. · Summarize current research on effectiveness of warning systems on hand held devices and study influence of warning systems on non-motorized user behavior. · Study options for communicating with hand held devices not currently in use and influences to the non-motorized user behavior. · Study the interaction of vulnerable users and human-driven vehicles to determine communication and influences on behavior and identify behaviors that could influence AV technology development. · Study effectiveness of warning systems on vulnerable users · Study influence of external features and vehicle behavior on non-motorized user behavior. · Identify built environment features that positively influence non-motorized user behavior in AV interactions. · Identify training strategies to educate non-motorized user behavior to improve safety when interacting with AV technology. · Identify the differences in information requirements based on context, such as urban/rural settings, traffic volume, number of lanes, and number of pedestrians. · Study predictive models of pedestrian behavior and how they might inform warning or message systems. Investigate the effects of communication and no communication to non-motorized user behavior.


Most of the current or previous research on AV technology has focused on the built environment, the capabilities of AV technology communicating with built environment aspects or other technology to alert other corridor users to the presence of the AV. This study is expected to identify the human factors that influence non-motorized user behavior. It is also expected to identify the effectiveness of communication tools used by non-motorized users to communicate with vehicles and the resulting influence on non-motorized user behavior. The study of the built environment and influences on non-motorized user behavior in AV interactions may benefit public agencies as those agencies identify infrastructure updates. The study of vulnerable users communication and behavior addresses potential safety concerns and provides equity.

Related Research:

Planning for Walking and Cycling in an Autonomous Vehicle Future, Mid Atlantic Transportation Sustainability University Transportation Center, DTRT13-G-UTC33, 2018


Performance Assessment & Simulation of Pedestrian Behavior at Unsignalized Crossings, Research and Innovative Technology Administration, 98215, 2012-016, 2013

Assessing Pedestrians’

Perceptions and Willingness to Interact with Autonomous Vehicles, US DOT, 69A355174125, 2018, Ongoing


Human-Machine Communication in the Context of Autonomous Vehicles, US DOT, 69A3551747115, 2017, Ongoing


Target Audience: AV technology developers, policy makers in private and public agencies that guide infrastructure updates and oversee equity policy development, technology developers that create advanced warnings systems to improve non-motorized user safety


Key Decision Makers: State DOT and local Chief Engineers


AASHTO Committees: The AASHTO Standing Committee on Highway Traffic Safety, Standing Committee on Highways and the Subcommittee on Design could facilitate the implementation of the research results along with Joint Technical Committee on Non-Motorized Transportation.

Early Adopters: Early adopters could be state and local agencies with an AV presence in their jurisdiction or identified as testing grounds, such as the City of Pittsburgh, M-City, San Diego, Dallas-Fort Worth and Phoenix.


This research was identified by the TRB Standing Committee on Pedestrians (AFN 10) and is highly recommended as AV technology is rapidly evolving and is already in our roadway corridors. Understanding non-motorized user behavior changes and interactions with AV will help researchers and public agencies identify the appropriate tools to provide a communication bridge between computers and humans as well as ensure communication applications remain consistent as the technology progresses. Bridging this communication gap and creating predictable behavior can increase safety and equity for non-motorized users.

Sponsoring Committee:ACH10, Pedestrians
Research Period:12 - 24 months
Research Priority:High
RNS Developer:Amy Rosepiler and Ray Delahanty
Date Posted:01/09/2019
Date Modified:01/11/2019
Index Terms:Behavior, Human factors, Autonomous vehicles, Communication, Pedestrian vehicle interface, Pedestrian safety, Pedestrians,
Cosponsoring Committees: 
Pedestrians and Bicyclists
Safety and Human Factors
Vehicles and Equipment

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