Marc Green

Bio: Marc Green is an academic researcher. The author has contributed to research in topics: Brake & Poison control. The author has an hindex of 1, co-authored 1 publications receiving 753 citations.

"How Long Does It Take to Stop?" Methodological Analysis of Driver Perception-Brake Times

Abstract: Human perception-brake reaction time (RT) studies have reported a wide variety of results. By analyzing a large number of data sets, however, it is possible to estimate times under specific conditions. The most important variable is driver expectation, which affects RTs by a factor of 2. When fully aware of the time and location of the brake signal, drivers can detect a signal and move the foot from accelerator to brake pedal in about 0.70 to 0.75 sec. Response to unexpected, but common signals, such as a lead car's brake lights, is about 1.25 sec, whereas RTs for surprise events, such as an object suddenly moving into the driver's path, is roughly 1.5 sec. These times are modulated somewhat by other factors, including driver age and gender, cognitive load, and urgency.

A vehicle-to-vehicle communication protocol for cooperative collision warning

Abstract: This paper proposes a vehicle-to-vehicle communication protocol for cooperative collision warning Emerging wireless technologies for vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications such as DSRC are promising to dramatically reduce the number of fatal roadway accidents by providing early warnings One major technical challenge addressed in this paper is to achieve low-latency in delivering emergency warnings in various road situations Based on a careful analysis of application requirements, we design an effective protocol, comprising congestion control policies, service differentiation mechanisms and methods for emergency warning dissemination Simulation results demonstrate that the proposed protocol achieves low latency in delivering emergency warnings and efficient bandwidth usage in stressful road scenarios

Stability and Stabilization of Systems with Time Delay

Abstract: Time-delays are important components of many dynamical systems that describe coupling or interconnection between dynamics, propagation, or transport phenomena in shared environments, in heredity, and in competition in population dynamics. This monograph addresses the problem of stability analysis and the stabilisation of dynamical systems subjected to time-delays. It presents a wide and self-contained panorama of analytical methods and computational algorithms using a unified eigenvalue-based approach illustrated by examples and applications in electrical and mechanical engineering, biology, and complex network analysis.

Adaptive cruise control design for active congestion avoidance

Abstract: We present an adaptive cruise control (ACC) strategy where the acceleration characteristics, that is, the driving style automatically adapts to different traffic situations. The three components of the concept are the ACC itself, implemented in the form of a car-following model, an algorithm for the automatic real-time detection of the traffic situation based on local information, and a strategy matrix to adapt the driving characteristics (that is, the parameters of the ACC controller) to the traffic conditions. Optionally, inter-vehicle and infrastructure-to-car communication can be used to improve the accuracy of determining the traffic states. Within a microscopic simulation framework, we have simulated the complete concept on a road section with an on-ramp bottleneck, using empirical loop-detector data for an afternoon rush-hour as input for the upstream boundary. We found that the ACC vehicles improve the traffic stability and the dynamic road capacity. While traffic congestion in the reference scenario was completely eliminated when simulating a proportion of 25% ACC vehicles, travel times were already significantly reduced for much lower penetration rates. The efficiency of the proposed driving strategy even for low market penetrations is a promising result for a successful application in future driver assistance systems.

Delays, inaccuracies and anticipation in microscopic traffic models

Abstract: We generalize a wide class of time-continuous microscopic traffic models to include essential aspects of driver behaviour not captured by these models. Specifically, we consider (i) finite reaction times, (ii) estimation errors, (iii) looking several vehicles ahead (spatial anticipation), and (iv) temporal anticipation. The estimation errors are modelled as stochastic Wiener processes and lead to time-correlated fluctuations of the acceleration. We show that the destabilizing effects of reaction times and estimation errors can essentially be compensated for by spatial and temporal anticipation, that is, the combination of stabilizing and destabilizing effects results in the same qualitative macroscopic dynamics as that of the, respectively, underlying simple car-following model. In many cases, this justifies the use of simplified, physics-oriented models with a few parameters only. Although the qualitative dynamics is unchanged, multi-anticipation increase both spatial and temporal scales of stop-and-go waves and other complex patterns of congested traffic in agreement with real traffic data. Remarkably, the anticipation allows accident-free smooth driving in complex traffic situations even if reaction times exceed typical time headways.

Sensitivity of eye-movement measures to in-vehicle task difficulty

Abstract: Eye-movement measures were found to be highly sensitive to the demands of visual and auditory in-vehicle tasks as well as driving task demands. Two newer measures, Percent road centre and Standard deviation of gaze, were found to be more sensitive, more robust, more reliable, and easier to calculate than established glance-based measures. The eye-movement measures were collected by two partners within the EU project HASTE to determine their sensitivity to increasingly demanding in-vehicle tasks by means of artificial, or surrogate, In-vehicle Information Systems (S-IVIS). Data from 119 subjects were collected from four routes: a motorway in real traffic with an instrumented vehicle, a motorway in a fixed base simulator, and from rural roads in two different fixed base simulators. As the visual task became more difficult, drivers looked less at the road centre area ahead, and looked at the display more often, for longer periods, and for more varied durations. The auditory task led to an increasing gaze concentration to road centre. Gaze concentration to the road centre area was also found as driving task complexity increased, as shown in differences between rural curved- and straight sections, between rural and motorway road types, and between simulator and field motorways.