Skip to main content
eScholarship
Open Access Publications from the University of California

Longitudinal Model Development For Automated Roadway Vehicles

Abstract

In today’s society minimizing the use of the roadways is becoming an issue of increasing concern.Many major cities in the US are plagued with such problems as traftic congestion, poor air quality, andsafety problems. To solve these problems research throughout the world is being conducted on the use ofautomated roadways.Currently in the state of California research is being conducted involving several major institutionsas to the feasibility of the automated roadway. The Program on Advanced Technology for the Highway,PATH, aims to increase the capacity of the most used highways, to decrease traffic congestion and improvesafety and air quality.This research is in part being conducted by the Department of Mechanical Engineering at theUniversity of California, Berkeley. Professor J. K. Hedrick is the principal investigator along with M.S.candidate D. H. McMahon. This aspect of research deals with longitudinal model development andlongitudinal control algorithm development.Chapter 2 of this report describes the vehicle model development for longitudinal analysis. Themodel is capable of predicting engine transients due to changes in throttle angle, spark advance, fuelinjection rate, as well as EGR changes and vehicle transients due to brake inputs.Chapter 3 describes the longitudinal model simulation package, LONSIM. The program structure,inputs, outputs, and supporting material are discussed in this chapter.Chapter 4 gives the results of simulations using the powertrain model. The model is subjected toengine inputs (throttle) and brake inputs. Comparisons are made to a model used in control algorithmstudies for automated vehicle simulations. The necessity of the complexity of the full vehicle longitudinalmodel is then evaluated.Chapter 5 describes the conclusions of our first year’s research. In addition objectives for the nextyear’s research are discussed.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View