Connected and Automated Vehicles

A Specification Of An Automated Freeway With Vehicle-Borne Intelligence

Hitchcock, Anthony
1992

The focus of this work is to derive a technique of safety analysis for an automated freeway system. To demonstrate the method of safety analysis a procedure called fault tree analysis is applied. The specified freeway operates with vehicles in platoons. The safety criterion used here is that two or more simultaneous faults must occur independently before the hazards can arise.

Single-Channel IVHS Communication Architecture

Linnartz, Jean-paul M. G.
1994

This report documents a single-channel architecture offering two-way communication between vehicles and a fixed communication infrastructure. Part I discusses the technical advantages and disadvantages of a dedicated Intelligent Vehicle Highway Systems (IVHS) communications infrastructure versus the use of a hybrid system involving several existing communication networks. Aspects such as spectrum efficiency, message capacity, and network performance are described. Part II proposes a network architecture that offers several transmission services essential to IVHS communications, using only...

Robust Eco-Driving Control of Autonomous Vehicles Connected to Traffic Lights

Sun, Chao
Guanetti, Jacopo
Borrelli, Francesco
Moura, Scott
2019

This paper focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized intersections on the road is considered. The eco-driving problem is formulated as a data-driven chance constrained robust optimization problem. Effective red light duration (ERD) is defined as a random variable, and describes the feasible passing time through the signalized intersections. In practice, the true probability distribution for ERD is usually unknown. Consequently, a data-driven approach is adopted...

Design and Implementation of Ecological Adaptive Cruise Control for Autonomous Driving with Communication to Traffic Lights

Bae, Sangjae
Kim, Yeojun
Guanetti, Jacopo
Borrelli, Francesco
2019

This paper presents the design and implementation results of an ecological adaptive cruise controller (ECO-ACC) which exploits driving automation and connectivity. The controller avoids front collisions and traffic light violations, and is designed to reduce the energy consumption of connected automated vehicles by utilizing historical and real-time signal phase and timing data of traffic lights that adapt to the current traffic conditions. We propose an optimization-based generation of a reference velocity, and a velocity-tracking model predictive controller that avoids front collisions...

Real-time Ecological Velocity Planning for Plug-in Hybrid Vehicles with Partial Communication to Traffic Lights

Bae, Sangjae
Choi, Yongkeun
Choi, Yeojun
Guanetti, Jacopo
Borrelli, Francesco
2019

This paper presents the design of an ecological adaptive cruise controller (ECO-ACC) for a plug-in hybrid vehicle (PHEV) which exploits automated driving and connectivity. Most existing papers for ECO-ACC focus on a shortsighted control scheme. A two-level control framework for long-sighted ECO-ACC was only recently introduced [1]. However, that work is based on a deterministic traffic signal phase and timing (SPaT) over the entire route. In practice, connectivity with traffic lights may be limited by communication range, e.g. just one upcoming traffic light. We propose a two-level...

Charging Infrastructure Demands of Shared-Use Autonomous Electric Vehicles in Urban Areas

Zhang, Hongcai
Sheppard, Colin J. R.
Lipman, Timothy E.
Zeng, Teng
Moura, Scott J.
2020

Ride-hailing is a clear initial market for autonomous electric vehicles (AEVs) because it features high vehicle utilization levels and strong incentive to cut down labor costs. An extensive and reliable network of recharging infrastructure is the prerequisite to launch a lucrative AEV ride-hailing fleet. Hence, it is necessary to estimate the charging infrastructure demands for an AEV fleet in advance. This study proposes a charging system planning framework for a shared-use AEV fleet providing ride-hailing services in urban area. We first adopt an agent-based simulation model, called BEAM...

Optimal Eco-Driving Control of Connected and Autonomous Vehicles Through Signalized Intersections

Sun, Chao
Guanetti, Jacopo
Borrelli, Francesco
Moura, Scott J.
2020

This article focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized intersections on the road is considered. The eco-driving problem is formulated as a data-driven chance-constrained robust optimization problem. Effective red-light duration (ERD) is defined as a random variable, and describes the feasible passing time through the signalized intersections. Usually, the true probability distribution for ERD is unknown. Consequently, a data-driven approach is adopted to...

Cooperation-Aware Lane Change Maneuver in Dense Traffic based on Model Predictive Control with Recurrent Neural Network

Bae, Sangjae
Saxena, Dhruv
Nakhaei, Alireza
Choi, Chiho
Fujimura, Kikuo
Moura, Scott
2020

This paper presents a real-time lane change control framework of autonomous driving in dense Traffic, which exploits cooperative behaviors of other drivers. This paper focuses on heavy Traffic where vehicles cannot change lanes without cooperating with other drivers. In this case, classical robust controls may not apply since there is no "safe" area to merge to without interacting with the other drivers. That said, modeling complex and interactive human behaviors is highly non-trivial from the perspective of control engineers. We propose a mathematical control framework based on Model...

Joint Fleet Sizing and Charging System Planning for Autonomous Electric Vehicles

Zhang, Hongcai
Sheppard, Colin J. R.
Lipman, Timothy E.
Moura, Scott
2020

This paper studies the joint fleet sizing and charging system planning problem for a company operating a fleet of autonomous electric vehicles (AEVs) for passenger and goods transportation. Most of the relevant published papers focus on intracity scenarios and adopt heuristic approaches, e.g., agent based simulation, which do not guarantee optimality. In contrast, we propose a mixed integer linear programming model for intercity scenarios. This model incorporates comprehensive considerations of 1) limited AEV driving range; 2) optimal AEV routing and relocating operations; 3) time-varying...

Intersense: An XGBoost Model for Traffic Regulator Identification at Intersections Through Crowdsourced GPS Data

Vlachogiannis, Dimitris
Moura, Scott
Macfarlane, Jane
2023

Digital maps of the transportation network are the foundation of future mobility solutions. Autonomous and connected vehicles rely on real-time, at-scale updating of the environment in which they operate. Successful operation in a hybrid environment, where human and machine intelligence coexist, requires explicit knowledge of the traffic regulator infrastructure. Future generation traffic management strategies and path planning systems must be tightly integrated with the regulator infrastructure in order to improve traffic dynamics and reduce congestion in urban environments. In this...