Benefit

Evaluation of the Environmental Effects of Intelligent Cruise Control (ICC) Vehicles


7-11 January 2001
United States


Summary Information

This study used field experiments and simulation models to quantify the environmental benefits of intelligent cruise control (ICC) vehicles. Field tests were conducted using one ICC vehicle and two other manually operated vehicles in a single lane of freeway traffic. During the field trials driver responses and vehicle dynamics were recorded as they followed a lead vehicle with a pre-programmed speed profile (aggressive-rapid-acceleration or smooth-acceleration). The ICC vehicle trailed the other vehicles at different positions and implemented a smoothing effect to decrease the variance between the acceleration and deceleration extremes exhibited by the manually operated vehicles. Information from each field test was then input into a simulation model to measure net changes in fuel consumption and emissions.

The ICC vehicle was equipped with a forward looking radar (24 GHz Frequency Modulated Continuous Wave), an autonomous throttle actuator (stepper motor), and an autonomous brake actuator (hydraulic booster motor). The manually operated vehicles were equipped with data acquisition systems that recorded vehicle speeds and measured inter-vehicle spacing. The lead vehicle speed profiles for each test consisted of aggressive (rapid acceleration) or non-aggressive (smooth acceleration) behavior using a common scenario where vehicles accelerated from 37 (miles per hour) to 45 mph, then decelerated to 30 mph, and then accelerated to 50 mph. This baseline field data was input into the PIPES computer simulation model to evaluate the ICC smoothing effect on a larger scale (Table-1).

The Comprehensive Modal Emissions Model (CMEM) 1.00 developed by the University of California was used to analyze and calculate pollution and fuel consumption estimates. The CMEM model quantified tailpipe emissions based on second-by-second velocity, acceleration, and grade changes for each individual vehicle. Emissions measured included unburned hydrocarbons (HC), Carbon monoxide (CO), Carbon dioxide (CO2), and the oxides of Nitrogen (NOx).

RESULTS

The position of the ICC vehicle behind the lead vehicle varied the acceleration and deceleration characteristics of the trailing vehicles and thusly the output of vehicle emissions. The smoothing of traffic flow by the ICC vehicle significantly reduced emissions and the fuel consumption of manual traffic.

The following results were tabulated:

TABLE-1 The pollution and fuel savings below were calculated from the CHEMM model with vehicle dynamics data generated by traffic simulation. The data presented below shows the simulated results of having one ICC vehicle in a line of 10 manually operated vehicles. The experiment was conducted for two different types of traffic conditions (Smooth Acceleration or Rapid Acceleration).

Environmental Measures
Smooth Accel.
Rapid Accel.
CO emission
18.4 %
60.6 %
CO2 emission
8.1 %
60.6 %
NOx emission
13.1 %
1.5 %
HC emission
15.5 %
55.4 %
Fuel consumption
8.5 %
28.5 %


TABLE-2 The pollution and fuel savings below were calculated from the CHEMM model with vehicle dynamics data derived from actual field trials and subsequent simulations of those field trials. The data presented below shows the actual and simulated results of having one ICC vehicle in a line of 2 manually operated vehicles. The experiment was conducted for two different types of traffic conditions (Smooth Acceleration or Rapid Acceleration).

Environmental Measures
Field Smooth Accel.
Simulation Smooth Accel.
Field Rapid Accel.
Simulation Rapid Accel.
CO emission
1.2 %
0.8 %
19.2 %
12.3 %
CO2 emission
0.4 %
0.2 %
3.4 %
3.3 %
NOx emission
1.6 %
1.3 %
25.7 %
19.2 %


There was a significant difference between the simulated savings in TABLE-1 and TABLE-2. The author attributed these differnces to sample size variations.

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Source

Evaluation of the Environmental Effects of Intelligent Cruise Control (ICC) Vehicles

Author: Bose, A. and P. Ioannou

Published By: Paper presented at the 80th Annual Transportation Research Board Meeting. Washington, District of Columbia

Source Date: 7-11 January 2001


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Keywords

intelligent cruise control, ICC, ACC, Intelligent Speed Adaptation, ISA

Benefit ID: 2001-00202