Joel VanderWerf

Effects of Adaptive Cruise Control Systems on Highway Traffic Flow Capacity

The effects on traffic flow of increasing proportions of both autonomous and cooperative adaptive cruise control (ACC) vehicles relative to manually driven vehicles were studied. Such effects are difficult to estimate from field tests on highways because of the low market penetration of ACC systems. The research approach used Monte Carlo simulations based on detailed models presented in the literature to estimate the quantitative effects of varying the proportions of vehicle control types on lane capacity. The results of this study can help to provide realistic estimates of the effects of the introduction of ACC to the vehicle fleet. Transportation system managers can recognize that the autonomous ACC systems now entering the market are unlikely to have significant positive or negative effects on traffic flow. An additional value of studying ACC systems in this way is that these scenarios can represent the first steps in a deployment sequence that will lead to an automated highway system. Benefits gained at the early stages in this sequence, particularly through the introduction of cooperative ACC with priority access to designated (although not necessarily dedicated) lanes, can help support further investment in and development of automated highway systems.

Effects of vehicle-vehicle/roadside-vehicle communication on adaptive cruise controlled highway systems

We study the effect of vehicle vehicle/vehicle-roadside communication on the performance of adaptive cruise control (ACC) systems. Two simulation works are presented One is a single ACC vehicle simulation using MATLAB/SIMULINK. A cut-in scenario and a braking scenario are tested Communication greatly saves control effort in the former scenario, while has little effect in the latter. The other work simulates ACC controlled highway merging with SHIFT language. The results show beneficial effects of communication in terms of braking effort, waiting-to-merge queue length, and main lane traffic shock wave caused by merging.

Modeling Effects of Driver Control Assistance Systems on Traffic

A set of mathematical models is defined to predict the effects of emerging driver control assistance systems such as adaptive cruise control (ACC) on traffic flow dynamics and capacity. It is important to understand these effects in order to ensure that ACC systems are implemented in ways that improve, rather than degrade, traffic conditions. Existing traffic models were not designed for, and are not suitable for, this purpose, so it has been necessary to develop a new family of simulation models incorporating the key elements of driver behavior and control system design that will affect traffic flow dynamics and capacity. Example outputs from simulation validation test cases are illustrated and explained to show that the models are producing reasonable results.

Dependence of Cooperative Vehicle System Performance on Market Penetration

Cooperative vehicle systems (CVS) can provide intelligent transportation systems services such as probe vehicle information and hazard warnings by exchanging data among suitably equipped vehicles as they travel. The sensitivity of the performance of CVS to the market penetration of suitably equipped vehicles is explained by using Monte Carlo analyses and simulations of wireless message propagation. The CVS functions are implemented by using wireless vehicle-vehicle data communications, which can be successful only when other equipped vehicles exist within wireless range to receive the messages and relay them to further vehicles. These relays may be accomplished by direct wireless transmission to nearby vehicles, but they may also be facilitated by transport relay, by which vehicles traveling in the opposite direction carry the messages and rebroadcast them to the vehicles that they pass. The effectiveness of both direct and transport relay mechanisms as a function of wireless communication range, market penetration, and traffic density and their influence on the speed of message propagation is shown. The direct relay is most effective with a high density of equipped vehicles, but when the density of equipped vehicles is low, the relays become much more dependent on the slower transport relay. When the market penetration is low early in the development of CVS, the most promising use cases are likely to be those that do not require rapid message propagation.

Design of Alert Criteria for an Intersection Decision Support System

This paper describes the design and preliminary evaluation of the criteria for alerting drivers to a specific set of intersection hazards. The research is being conducted as part of the development of an intersection decision support (IDS) system that uses the sensing and computational technologies of infrastructure-based intelligent transportation systems. The IDS system under consideration is intended to help drivers avoid conflicts with oncoming traffic when they are making left turns under a permissive (i.e., unprotected) green signal. These conflicts account for a significant proportion of intersection crashes and are difficult to mitigate without imposing serious costs and burdens on intersection capacity associated with providing a protected left-turn signal cycle. The human factors and sensing issues that need to be considered in designing the system are discussed and are followed by a description of the logic used to define the gaps in opposing traffic that should be considered adequate for left-turn maneuvers. The simulation model used to evaluate alternative system designs is described, and sample results are shown for evaluation of the effectiveness of a warning under a relatively stressful scenario. The influence of alternative sensor configurations on the effectiveness of the warning is illustrated and indicates the importance of providing information about both the presence and speed of approaching vehicles sufficiently far from the intersection.

Implementing Vehicle–Infrastructure Integration: Real-World Challenges

In recent years, much attention in the field of intelligent transportation systems has been devoted to conceptualizing and starting development of vehicle-infrastructure integration (VII), which would provide new vehicles with the capability to communicate data with each other and with roadside transceivers located throughout the roadway network. The bulk of the federal VII activities have focused on defining an overall architecture and the wireless vehicle-infrastructure communication link, while exploring the institutional challenges to deployment. A somewhat different perspective to VII focuses on the real-world challenges that have been encountered and overcome in implementing the first VII test bed environment in California. It is important to understand these practical aspects of installing, operating, and maintaining the VII communications infrastructure when developing plans and cost estimates for large-scale national VII deployment. Lessons learned from the initial VII California test bed development and operations are provided in the hope that they can contribute to decisions about VII design and development.

Providing Intersection Decision Support Under Challenging Conditions

This paper describes the results of simulation studies to determine how effectively left-turning drivers can be alerted to imminent conflicts with opposing traffic under difficult operating conditions and with limited detector capabilities. These conditions include approaching vehicles changing speed in locations that are not covered by detectors and detectors that may only be able to detect vehicle presence, but not speed. In cases without direct speed detection, one may try to rely on historical speed statistics to estimate the speed of approaching traffic, but unless the approach speeds are confined to a very narrow range the system is vulnerable to both false positive and false negative alerts in the respective cases of the real vehicle speeds being less than and greater than the assumed historical value.