Highway Capacity Manual改訂の動向--テイラ-教授の講演より

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.

Transportation network analysis

This review covers research on the topic of mixed criticality systems that has been published since Vestal’s 2007 paper. It covers the period up to and including December 2015. The review is organised into the following topics: introduction and motivation, models, single processor analysis (including job-based, hard and soft tasks, fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, related topics, realistic models, formal treatments, and systems issues. An appendix lists funded projects in the area of mixed criticality.

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Mixed Criticality Systems - A Review

The car-following behavior of individual drivers in real city traffic is studied on the basis of (publicly available) trajectory data sets recorded by a vehicle equipped with a radar sensor. By means of a nonlinear optimization procedure based on a genetic algorithm, the intelligent driver model and the velocity difference model are calibrated by minimizing the deviations between the observed driving dynamics and the simulated trajectory in following the same leading vehicle. The reliability and robustness of the nonlinear fits are assessed by applying different optimization criteria, that is, different measures for the deviations between two trajectories. The obtained errors are between 11% and 29%, which is consistent with typical error ranges obtained in previous studies. It is also found that the calibrated parameter values of the velocity difference model depend strongly on the optimization criterion, whereas the intelligent driver model is more robust. The influence of a reaction time is investigate...

Calibrating Car-Following Models by Using Trajectory Data: Methodological Study

The real-time kinematic differential Global Positioning System (GPS) has facilitated a new horizon in traffic engineering. Multiple car-following experiments conducted with a real-time kinematic GPS with 10 vehicles participating in a probing field gave high-quality results in headway, speed, relative speed, and acceleration. The expected accuracies for measuring position and speed were 10 mm and 0.16 km/h, respectively. The vehicles were driven in a loop consisting of two parallel straight sections connected by two semicircular curves. Different driving conditions were induced in the platoon by instructing the leading driver to follow predetermined speed variations. The experiments yielded sets of continuous observations. Headway, speed, and acceleration were measured using conventional equipment for the purpose of comparing accuracy. The accuracy of the data obtained using the GPS was superior to that of the same data obtained using conventional measurements. The variation in driving characteristics down the stream of vehicles was studied using the experimental data. The results showed that the reaction time between a change in relative speed and the corresponding change in acceleration varies during the driving process. The reaction time of individual drivers also changes along the platoon. The good-quality data were able to give high-resolution plots of acceleration and relative speed illustrating that both the reaction time and the functional relationship between acceleration and relative speed do not remain constant.

Multiple car-following data with real-time kinematic Global Positioning System

The performance of six microscopic traffic flow models was investigated on the basis of how well these models fit with the real-time kinematic Global Positioning System (GPS) measurements. Ten passenger cars equipped with the GPS receivers participated in the car-following experiments, conducted at a test track. The genetic algorithm-based approach is adopted to optimize the model parameters for two different cases: using speed and headway data. The optimized performance of each model is analyzed for various driving conditions introduced by the different level of disturbances to the lead vehicle's speed, which include half-wave, one-wave, two-wave, three-wave, random, and constant speed patterns. In the former case with speed data, five models performed well with the average percentile error ranging from 3.87% to 4.71% and standard deviation ranging from 1.09% to 1.64%. In the latter case with headway data, only three models performed well with the average percentile error ranging from 12.04% to 12.91% an...

Performance Evaluation of Microscopic Traffic Flow Models with Test Track Data

Modeling public-transit connectivity with spatial quality-of-transfer measurements

Car-following model has important applications in traffic and safety engineering e.g. for traffic simulation, Advance Vehicle Control and Safety System etc. A great deal of investigation works were conducted in the last five decades to model the longitudinal interaction between adjacent vehicles as a result numerous models are available now. A performance based benchmarking of these models might be useful to evaluate their capabilities in representing real driving behavior. Data precision is the key factor to make any such evaluation meaningful. RTK GPS is the latest technology in data acquisition that makes it possible to acquire high resolution vehicular movement data at an outstanding level of accuracy. Several car-following models were evaluated based on test track experiment data using a GA based optimization method. It was interesting to see a simple linear model performing better than some sophisticated models.

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Car-following models: an experiment based benchmarking

This paper attempts to analyze the stability of a platoon using experimental data measured by RTK GPS receivers. Car following experiments were conducted in a test track using ten passenger cars and tested various speed patterns for lead car, including random constant and sinusoidal speed patterns, giving different driving conditions. The response of following drivers was measured by RTK GPS receivers equipped in each car. The stimulus-response based car following concept was examined assuming that the reaction time might vary over time. A graphical method was modified to estimate time variant reaction time more efficiently. A new algorithm was proposed to estimate sensitivity factor using Glissandos diagram between relative speed and acceleration. The statistical analysis showed that intrapersonal variability was higher than interpersonal variability for both reaction time and sensitivity factor. However, the influence of driver position in the platoon and speed patterns was low. It was found that the reaction time was distributed in lognormal function for most of the drivers. The variations in the estimated values for the sensitivity factor were relatively high. The stability analysis showed that the average response of drivers was unstable both locally and asymptotically. The influence of speed fluctuations on the stability of the platoon was found insignificant

Prakash Ranjitkar

Papers

Multiple car-following data with real-time kinematic Global Positioning System

Performance Evaluation of Microscopic Traffic Flow Models with Test Track Data

Modeling public-transit connectivity with spatial quality-of-transfer measurements

Car-following models: an experiment based benchmarking

Stability analysis based on instantaneous driving behavior using car following data