Partners For Advanced Transit And Highways Research Articles

Lighthill-Whitham-Richards Model for Traffic Flow Mixed with Cooperative Adaptive Cruise Control Vehicles

In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.

Longitudinal safety impacts of cooperative adaptive cruise control vehicle's degradation

Introduction: The adaptive cruise control (ACC) and cooperative ACC (CACC) systems are critical parts of self-driving vehicles. The ACC vehicles detect front vehicle' information via vehicle-mounted sensors and make longitudinal reactions automatically, while CACC vehicles enhance the performance by vehicle-to-vehicle (V2V) wireless communication. However, CACC vehicles may abruptly degrade to ACC mode in reality due to various reasons, including communication failures, driver manipulations, and cyber-attacks. The sudden degradation will definitely bring negative influences on safety. Method:This study quantitatively evaluated the longitudinal safety impacts of vehicles' degradation in a CACC fleet based on microscopic simulations. The realistic CACC and ACC models proposed by the California Partners for Advanced Transit and Highways (PATH) were used for simulation experiments. The time integrated time-to-collision (TIT) was measured to quantify the collision risks. Extensive simulations were conducted via a fleet of 10 CACC vehicles and speed profiles of vehicles in different scenarios were compared. Key factors, including the leading vehicle's deceleration rate, the number of vehicles between degraded vehicles (NVDVs), threshold of TTC, and visibility were also examined via sensitivity analyses. Results and conclusions: Simulation results indicate that degradation has significant negative influences on longitudinal safety of degraded vehicles under the driving state of deceleration. Degradation at middle positions in a CACC fleet, such as fourth and fifth positions, is much safer than that at others. Moreover, nonadjacent degradation is much riskier than adjacent degradation at the front positions of a fleet. NVDVs can bring inverse impacts on safety with different degradation positions. Speed profiles imply that the hysteresis of degraded vehicles' speed control is the major reason for high collision risks. Practical applications: Appropriately, hierarchical countermeasures have the potential to reduce the longitudinal safety impacts of degradation. Findings of this study can contribute to determining the applicable length of CACC fleets.

Characterizing the impact of production adaptive cruise control on traffic flow: an investigation

ABSTRACTThis research conducted a comprehensive study to better estimate the impact of production Adaptive Cruise Control (ACC) on uninterrupted flow facilities using the highly cited ACC car-following models in the literature. Four different car-following models were investigated, including the Autonomous Adaptive Cruise Control (AACC) model, Intelligent Driver Model (IDM), California Partners for Advanced Transit and Highways (PATH) empirical ACC model, and the Technical University of Delft empirical ACC model. Each of the four models were recalibrated using data collected by a 2013 Cadillac SRX with production ACC engaged while following a human-driven 2013 Cadillac SRX in northern Virginia. Off-the-shelf commercial microscopic simulation software VISSIM was utilized to simulate the ACC traffic flow. Sensitivity analysis was conducted on ACC market penetration and following headway. Capacity and fundamental diagrams were used to quantify the impact of the ACC on traffic flow. Results indicate that freeway capacity highly depends on the market penetration of ACC vehicles. Small number of ACC vehicles (<25%) is beneficial to roadway capacity, while wider deployment of ACC vehicles (>75%) significantly harms capacity. The results strongly suggest the urgent need for vehicle connectivity.

PATH at 20—History and Major Milestones

The California partners for advanced transit and highways (PATH) program was founded in 1986, as the first research program in North America focused on the subject now known as intelligent transportation systems (ITS). This paper reviews the history of the founding of PATH and of the national ITS program in the U.S., providing perspective on the changes that have occurred during the past 20 years.

Communication Chains: A Methodology for Assessing the Effects of the Internet on Communication and Travel

Click to increase image sizeClick to decrease image size Acknowledgments Data collection was funded by the California Department of Transportation Traffic Operations Program, and previous analysis of the data was funded by the Partners for Advanced Transit and Highways (PATH) program of California. The current analysis was supported through a University of California Transportation Center research fellowship awarded to the first author. This project would not have been possible without the help of the individuals responsible for implementing the Davis Community Network, including Vicki Suter, Russ Hobby, Joan Gargano, and others. David Stanek and Michael Bagley contributed to the design of the data collection instruments, as well as through ongoing discussion. Krishna Varma and Prasuna Reddy provided data entry, initial analysis, and report-writing. Ilan Salomon and Hani Mahmassani also offered their invaluable insights to this study, while Daniel Sperling and Debbie Niemeier provided critical input to the initial Master's thesis that laid the groundwork for this paper. Last but not least, we are grateful to the DCN system users who completed the surveys that provided us with the data used in this study.

LTV controller design for vehicle lateral control under fault in rear sensors

This work focuses on vehicle lateral control for automated highway systems (AHSs) studied as a part of the California Partners for Advanced Transit and Highways (PATH) Program. In the PATH lateral control system, magnetometers are installed under both front and rear bumpers of the vehicle; these magnetometers measure the lateral deviation of the vehicle relative to the magnets buried along the centerline of each automated lane. Lateral controllers have been designed and tested successfully provided that there is no fault in magnetometers. It has been argued that these controllers are NOT tolerant to the fault in magnetometers. The focus of This work is the degraded-mode lateral control under fault in rear magnetometers. The aim of the controller design is to accomplish adequate performance with the remaining set of magnetometers, the front magnetometers. The effects of the fault are examined, and the significance of the linear time-varying (LTV) property of the front-magnetometer-based vehicle lateral dynamics is recognized. Popular control methods for LTV systems generally involve gain scheduling by switching between several linear time-invariant (LTI) controllers. Such methods are complicated and it is difficult to prove the stability of the switching mechanism. To derive a simple effective LTV controller, feedback linearization is applied to approximately cancel out the time-varying terms in the plant and to function as a gain scheduler. However, due to the weakly damped zeroes of the plant, feedback linearization with state feedback or matched observer state feedback results in weakly damped internal dynamics. In order to tune the internal dynamics, a mismatched observer is designed based on H-infinity optimal control techniques. Experimental results are presented to show the effectiveness of the controller design.

Emergency vehicle maneuvers and control laws for automated highway systems

The operation and transit of emergency vehicles (EVs) on an automated highway system (AHS) designed under the control architecture proposed in the California PATH (Partners for Advanced Transit and Highways) program is described. The term is used in a general sense to describe vehicles such as police cars, ambulances and tow trucks, that may service faults inside or outside the AHS. The transit of EVs requires intensive participation of the coordination layer, which directs the interactions of neighboring vehicles, and the link layer, which regulates traffic flow along stretches of highway. Various strategies for these two hierarchical layers that are needed to assign high-priority transit to EVs on the AHS are described. These coordination- and link-layer maneuvers circulate other vehicles around the EV in both free-flowing and stopped traffic.

Coding of Road Information for Automated Highways

Communication of information from the roadway infrastructure to vehicles is expected to enhance Automated Highway Systems (AHS) by supporting subsystem functions like vehicle motion control, multiple vehicle coordination, and vehicle navigation. A suitable communication channel is information coding in the lateral reference used for automatic steering and lane keeping control, e.g. in the magnet reference system used by California PATH (Partners for Advanced Transit and Highways). The presented coding strategy was designed for and tested at the 1–15 test track near San Diego, CA, being prepared for the AHS demonstration of the National AHS Consortium (NAHSC) held in Aug. 1997. A number of aspects are discussed, concerning types and structure of coded information, encoding and decoding schemes, and possible future extensions.

Smart Cars and Automated Highways

This article illustrates the development and use of intelligent vehicles and automated highways to solve the increasing traffic problem. Small networks of computers installed in vehicles and along selected roadways could closely coordinate vehicles and harmonize traffic flow, maximizing highway capacity and passenger safety. A driver electing to use such an automated highway might first pass through a validation lane, similar to today's high-occupancy-vehicle (HOV) or carpooling lanes. The system would then determine if the car will function correctly in an automated mode, establish its destination, and deduct any tolls from the driver's credit account. The article also highlights that basic to the automated-highway schemes are computer simulations to indicate that such systems may be the least expensive way to increase highway throughput. The California Partners for Advanced Transit and Highways (PATH) Program at the University of California has developed the technology whereby magnets buried at intervals in the roadbed would be sensed by magnetometers in vehicles, providing a way to monitor their location and velocity.

An Automated Highway System link layer controller for traffic flow stabilization

Controls for the link layer in the Automated Highway System (AHS) hierarchy proposed in the Partners for Advanced Transit and Highways (PATH) are developed. The link layer is modeled using vehicle conservation flow models. Desired traffic conditions on the highway are given by a pair of density and velocity profiles which are assumed to be consistent with the demand on, and the capability of, the highway system. The link layer control laws presented in this paper then stabilize the actual traffic condition to the desired values. Control laws are derived for three highway topologies: a single lane highway, a highway with multiple discrete lanes and a two-dimensional highway with an arbitrary flow pattern. The control laws obtained for each of the topologies is distributed and are suited for implementation in the lower levels of the AHS control hierarchy. Simulation results are also presented.

024 Automated vehicle control for IVHS systems

This paper reviews research on Advanced Vehicle Control Systems (AVCS) for highway automation in the California PATH (Partners for Advanced Transit and Highways) program. THE AVCS activities at PATH can be divided into two groups: longitudinal vehicle control and lateral vehicle control. The paper describes each of the activities with a concentration on control methodologies and experimental evaluation studies conducted to date.

Automated Vehicle Control for IVHS Systems

Research on Advanced Vehicle Control Systems (AVCS) for highway automation in the California PATH (Partners for Advanced Transit and Highways) program is reviewed. The AVCS activities at PATH can be divided into two groups: longitudinal vehicle control and lateral vehicle control. The paper describes each of the activities with a concentration on control methodologies and experimental evaluation studies conducted to date.

AUTOMATED HIGHWAY SYSTEM EXPERIMENTS IN THE PATH PROGRAM

The accomplishments to date on the experimental evaluation of Advanced Vehicle Control Systems (AVCS) technology for highway automation in the California PATH (Partners for Advanced Transit and Highways) Program are summarized. The AVCS activities at PATH can be divided into two groups: longitudinal vehicle control and lateral vehicle control. The paper describes each of the activities with a concentration on experimental results achieved to date. The experimental setups and results are presented, followed by near-term plans for further work.