Abstract

VENTURER was one of the first three UK government funded research and innovation projects on Connected Autonomous Vehicles (CAVs) and was conducted predominantly in the South West region of the country. A series of increasingly complex scenarios conducted in an urban setting were used to: (i) evaluate the technology created as a part of the project; (ii) systematically assess participant responses to CAVs and; (iii) inform the development of potential insurance models and legal frameworks. Developing this understanding contributed key steps towards facilitating the deployment of CAVs on UK roads. This paper aims to describe the VENTURER Project trials, their objectives and detail some of the key technologies used. Importantly we aim to introduce some informative challenges that were overcame and the subsequent project and technological lessons learned in a hope to help others plan and execute future CAV research. The project successfully integrated several technologies crucial to CAV development. These included, a Decision Making System using behaviour trees to make high level decisions; A pilot-control system to smoothly and comfortably turn plans into throttle and steering actuation; Sensing and perception systems to make sense of raw sensor data; Inter-CAV Wireless communication capable of demonstrating vehicle-to-vehicle communication of potential hazards. The closely coupled technology integration, testing and participant-focused trial schedule led to a greatly improved understanding of the engineering and societal barriers that CAV development faces. From a behavioural standpoint the importance of reliability and repeatability far outweighs a need for novel trajectories, while the sensor-to-perception capabilities are critical, the process of verification and validation is extremely time consuming. Additionally, the added capabilities that can be leveraged from inter-CAV communications shows the potential for improved road safety that could result. Importantly, to effectively conduct human factors experiments in the CAV sector under consistent and repeatable conditions, one needs to define a scripted and stable set of scenarios that uses reliable equipment and a controllable environmental setting. This requirement can often be at odds with making significant technology developments, and if both are part of a project’s goals then they may need to be separated from each other.

Highlights

  • Autonomous vehicles (AVs) have the potential to revolutionise the way we interact with our cars and those of other road users and the surrounding infrastructure [1]

  • We provide an evaluation of the technology development during the VENTURER project, the ways in which that technology was used for the purposes above, and the most important lessons that were learned from both a summary of the technical aspects, and a more general review of how to set up and operate a large consortium-based project that spans across research institutions and advanced industry

  • The VENTURER project systematically assessed the responses of passengers and other road users, including pedestrians and cyclists, to Autonomous Vehicles (AVs), in a successfully executed series of controlled but increasingly complex trials and demonstrations in urban settings

Read more

Summary

Introduction

Autonomous vehicles (AVs) have the potential to revolutionise the way we interact with our cars and those of other road users and the surrounding infrastructure [1]. A high level overview is given of the Decision Making System (DMS), the sensing capabilities and the Wireless communication systems This is followed by a brief, predominantly awareness raising, focus on selected technology developments associated with the vehicles that were used in the trials. Sensor data was created by Fusion Processing Ltd., and the Wildcat’s Velodyne LIDAR, on-board cameras and radar data was stored This is an invaluable amount of data which can be used by research students and other interested parties, to study, develop and test new algorithms, techniques and capabilities. It forms part of the VENTURER project legacy and is available on request

The Venturer Trials
Project Partners
The Wildcat Vehicle
Decision Making System Development
Optimisation-Based Approaches for Driving
Fixed-Path Planning with Speed Trajectories
Decision-Making Engine for Driving Scenarios
Integration and Implementation
Trial 2 Experiences
Lessons Learned for DMS
Sensing
Fusion Processing Technology Development
Example Fusion Processing Scenario
Wireless Communication System Demonstration Using a Bus
Project-Level Lessons Learned
Summary and Recommendations
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call