THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.

A Review of Motion Planning Techniques for Automated Vehicles

Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles

/pdf/the-impact-of-cooperative-adaptive-cruise-control-on-traffic-4jhs8l466d.pdf

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

Human mobility: Models and applications

Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on drivers' workload and situation awareness through a meta-analysis and narrative review of simulator and on-road studies. Based on a total of 32 studies, the unweighted mean self-reported workload was 43.5% for manual driving, 38.6% for ACC driving, and 22.7% for HAD (0% = minimum, 100 = maximum on the NASA Task Load Index or Rating Scale Mental Effort). Based on 12 studies, the number of tasks completed on an in-vehicle display relative to manual driving (100%) was 112% for ACC and 261% for HAD. Drivers of a highly automated car, and to a lesser extent ACC drivers, are likely to pick up tasks that are unrelated to driving. Both ACC and HAD can result in improved situation awareness compared to manual driving if drivers are motivated or instructed to detect objects in the environment. However, if drivers are engaged in non-driving tasks, situation awareness deteriorates for ACC and HAD compared to manual driving. The results of this review are consistent with the hypothesis that, from a Human Factors perspective, HAD is markedly different from ACC driving, because the driver of a highly automated car has the possibility, for better or worse, to divert attention to secondary tasks, whereas an ACC driver still has to attend to the roadway.

/pdf/effects-of-adaptive-cruise-control-and-highly-automated-zm9ko1q3vg.pdf

Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence

We describe an analytical queuing and network decomposition model developed to study the complex phenomenon of the propagation of delays within a large network of major airports. The Approximate Network Delays (AND) model computes the delays due to local congestion at individual airports and captures the " ripple effect" that leads to the propagation of these delays. The model operates by iterating between its two main components: a queuing engine (QE) that computes delays at individual airports and a delay propagation algorithm (DPA) that updates flight schedules and demand rates at all the airports in the model in response to the local delays computed by the QE. The QE is a stochastic and dynamic queuing model that treats each airport in the network as a M(t)/. Ek(t)/1 queuing system. The AND model is very fast computationally, thus making possible the exploration at a macroscopic level of the impacts of a large number of scenarios and policy alternatives on system-wide delays. It has been applied to a network consisting of the 34 busiest airports in the continental United States and provides insights into the interactions through which delays propagate through the network and the often-counterintuitive consequences. Delay propagation tends to " smoothen" daily airport demand profiles and push more demands into late evening hours. Such phenomena are especially evident at hub airports, where some flights may benefit considerably (by experiencing reduced delays) from the changes that occur in the scheduled demand profile as a result of delays and delay propagation. © 2011 Elsevier Ltd.

Modelling delay propagation within an airport network

Dynamic queueing systems : behavior and approximations for individual queues and for networks

This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed assistance. In general there are clear indications for an improvement in traffic safety. It also shows that traffic efficiency impacts are limited and in specific conditions even negative. Given the increasing attention 10 more advanced driver assistance system, the paper proposes new research directions Assistance' and advanced modeling techniques toward 'integrated driver assistance'.

Modelling traffic flows with intelligent cars and intelligent roads

The application of ITS is seen as very promising to address the negative consequences of road transport. However, the mechanisms which have an impact on the CO2 emissions are very complex, while not much about this is known from existing studies. Therefore, the EC commissioned this study, ‘Impact of Information and Communication Technologies on Energy Efficiency in Road Transport’, with the objective to perform an analysis on how ICT can contribute to reduction of emissions of CO2 and possible other greenhouse gases (from here on called “CO2 emissions”) through innovative technologies. The study is intended to support the policy making process, by providing an assessment of the most important systems and models able to resolve some of the challenges related to clean and efficient mobility. The result will help to define DG INFSO’s role in the ICT debate.

Impact of information and communication technologies on energy efficiency in road transport - Final Report

The demand for passenger mobility has grown exponentially in Europe in the past 25-30 years. Policy makers place great emphasis on the ability to predict, analyse and manage the growth of passenger mobility. Predicting passenger mobility, especially 15 or more years into the future, requires taking into account the most relevant variables in the modelling process. For example, accounting directly for the effects of the diversification of leisure time or the increase in individualization, and their consequent (potential) impact on the demand for mobility. These trends are difficult to quantify. The ability to account for these and other important variables is important in the process of modelling the demand for mobility. The scenario-development process can be used to identify these trends. The use of scenarios can assist planners and researchers in predicting mobility in the following three ways: (1) they assist in structuring, understanding and thinking through a changing situation. There are general glo...

The Scenario Explorer for Passenger Transport: A Strategic Model for Long-term Travel Demand Forecasting

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