Explore Communication Needs Between Highly Automated Vehicles and Other Road Users
Highly Automated Vehicles (HAVs) have the potential to reduce human errors and drive down fatal and injurious crashes. In fully automated driving scenarios, the interaction between HAVs and the other transport users: other vehicles (autonomous or not), pedestrians and cyclists is an important and emerging topic. Especially critical to the safe deployment of HAV’s are their interaction with Vulnerable Road Users (VRU). Other drivers, pedestrians, and road users that currently interact with manually driven vehicles may partially base interaction decisions on cues interpreted from vehicles such as speed and distance as well as cues from drivers, such as eye contact and gestures. With HAVs, vehicle operators will, in many scenarios, become passengers. Their attention may be moved away from the road and their ability to take back control from the vehicle may be limited or non-existent. In this case, other road users will be deprived of important cues from drivers, leaving them to infer awareness and intent from HAV’s design and behavior.
An improved understanding of the way in which drivers currently interact with other road users, along with informed design requirements for future interactions with HAVs, is critical. If the interaction between other road users and HAVs leads to miscommunication/ confusion, there will also be disrupting and inefficient complications for traffic operations. HAVs will only be acceptable and deployable if they are proven to be understandable and safe for pedestrians and all other road users.
(1) Identify and catalogue the current ways in which drivers interact with other road users through gestures, eye contact, vehicle control, etc. Map these behaviors onto different roadways and driving environments, considering the particular characteristics of urban/ rural roads and specific scenarios such as for example unsignalized/ signalized intersections.
(2) Identify and prioritize the safety criticality of communications between drivers and other road users. What information is required and how should it be communicated? For example, is it important or relevant for other road users to understand the vehicle’s driving mode (no automation, semi-automation, full automation)? What are the minimum design specifications and requirements for external vehicle communications with other road users?
(3) Identify key factors (e.g. infrastructure, environment, social norms, demographics, etc.) that will impact the effectiveness of this HAV communication and other road users.
(4) Identify how the infrastructure design can potentially be involved in the process and propose possible modifications to allow safer interoperability between HAVs and all other road users.
Here is a summary of the potential benefits of this research domain:
(1) Many states in the U.S. and other countries have issued regulations which will allow entities to test their Highly Automated Vehicles (HAVs) on the public roads both with and without safety drivers. Findings from this research will highlight safety concerns regarding other road users’ interaction with vehicles equipped with highly Advanced Driver Assistance Systems and Highly Automated Vehicles. Agencies could use this information to determine appropriate regulations to ensure the safe deployment of new ADS and HAVs and to determine possible modifications and adaptations of the road infrastructure design, in the specifically tested road environments and scenarios.
(2) Although the role of interface for Highly Automated Vehicle and other road users interaction is unclear with the absence of fully explored investigations, we hypothesize that indication of automation mode or external communication of vehicle intent would be essential when the Highly Automated Vehicle are introduced especially with mixed levels of automation. For regular manually driven vehicles, the exterior design is the primary distinction among different manufacturers. However, for HAVs, if the interface design of external communication varies from one manufacturer to another it could be hugely challenging for other road users to recognize the intent of automated vehicles. Therefore, recommendations and guidance governing the communication design would be necessary, for the considerations of government agencies at the state level and the federal level, as well as industrial and standard organizations.
(3) A fundamental motivation of this research is to put pedestrians and other vulnerable road users at the center of the investigation, and to capture their views and needs in the forthcoming automation context. For example, what other road users easily identify with and what they expect from the automated vehicles. Positive experiences when other road users encounter HAVs on the road is critical to their confidence, trust, and acceptance of the technology even if they don’t ride on a HAV or own a HAV, which will be beneficial to the technology deployment.
Research emphasis of Highly Automated Vehicles and other road users’ interaction so far is on the technological challenges, such as perception, implementation scenarios, path planning and vehicle control. A relatively less explored area is Highly Automated Vehicles interaction with other road users from the human-factors perspective.
Task 1: Identify possible critical scenarios (in a typical road environment) in which Highly Automated Vehicle (HAVs) and other road users may interact.
Task 2: Identify critical information which HAVs need to communicate to other road users.
Task 3: Identify possible ways of communicating the information to other road users.
Task 4: Design and development of prototype
Task 5: Experimental design and experiment preparation
Task 6: Conduct experiment
Task 7: Data analysis
Task 8: Recommendations
Findings will inform researchers, system designers and other stakeholders as well as inform transportation and public health policies and programs at the federal, state, and local levels.
|Sponsoring Committee:||ACH30, Human Factors of Vehicles
|Research Period:||12 - 24 months|
|RNS Developer:||Dr. Sanaz Motamedi, University of California Berkeley & Dr. Paolo Intini, Politecnico di Bari|
|Index Terms:||Autonomous vehicles, Drivers, Vulnerable road users, Communication, Level 5 driving automation, Level 4 driving automation, Driver vehicle interfaces, Pedestrian vehicle interface, |
Pedestrians and Bicyclists
Safety and Human Factors
Vehicles and Equipment