Sustainability

In freight transportation vehicles are very heavy, especially in the Nordic countries of Europe.
Therefore the impacts on the fuel consumption as well as pollutant emissions are sensitive for
slight changes in the vehicle motion. The fleet itself is small compared to the one of passenger
cars, but due to the large size of the vehicles the energy need and emissions occupy an
essential share of the totality. In order to reduce the energy consumption and avoid climate
changes attention must be paid to way, how these vehicles are used. Truck drivers are in a key position, and they can affect the climate change by the driving technique. 
 
In case of a heavy duty vehicle the driving technique comprises two items, the (target) speed
selection and the gear shift strategy. The target speed is the speed, which the driver tries to
maintain any time when possible, but on upward slopes the speed naturally falls from the
target speed like 80 km/h, which is a typical legal speed in most countries of Europe. When
this slope ends, the vehicle will be naturally accelerated back up to the target speed. 
 
In the concept of the target speed there is also another factor, which does not appear in case of passenger cars or in general light vehicles. This is called a “schwung”, which means the
excess of the speed that can be utilized on downward slopes achieved by the gravitation. The
grade resistance is negative on downward slopes and causes high acceleration for a heavy
vehicle, and no fuel is consumed. The kinetic energy is increased and can be utilized on the
next upgrade. However, the “schwung” appears only, if the vehicle is heavy and the road must be hilly. Utilizing the “schwung” is one of the most efficient ways to save energy, although it is not legal, if the base target speed is equal to the speed limit.  

FinnRA 

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

Traffic simulation models should reflect a wide variety of operating and environmental conditions in order to be useful in estimation and prediction of real world traffic behavior.  One area that traffic simulations have to accurately model is the effect that weather has on driver behavior and traffic flow characteristics. Recently, the Northwestern University and the University of Virginia have addressed this deficiency by investigating observed impacts of weather on both the supply and demand of traffic networks. This paper has two research purposes: to present the methodology for incorporating weather impacts into the DYNASMART-P traffic estimation and prediction tool and to assess the relative accuracy and fidelity of the developed weather module. The results indicate that the weather adjustment factor module developed by the Northwestern University is capable of reducing overestimation of vehicle speeds from 2 mph to 1 mph for light rain conditions and reducing the absolute error in estimating speeds during heavy rain by 33% when compared against simulations performed using normal parameters.  Additionally, of the three scenarios tested for two different weather conditions, the weather adjustment factor method consistently produced the smallest root mean squared error between simulated and observed speeds.

Department of Civil and Environmental Engineering, University of Virginia

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

While most existing models for predicting fuel consumption utilize vehicle parameters
(i.e. vehicle type, engine type, fuel type, etc.) and environmental parameters (i.e. weather,
terrain, geography etc.) these parameters can rarely be controlled. Recent studies suggest
that driver behavior can also affect fuel consumption. To date, no statistical model
evaluates the link between driving behavior and economic driving. This paper evaluates
the correlation between on-road driving behavior and fuel consumption.
The measurement of driving behavior is taken by an innovative in-vehicle data recorder
(IVDR) system named GreenRoad Safety Center. The system uses acceleration and
speed measurement to extract an overall measure of safe driving. This study compares the
measure of driving behavior taken by GreenRoad to fuel consumption variables.
A significant correlation was found between higher risk driving behavior, as measured by
GreenRoad Safety Center, and fuel consumption variables. The data showed:
· Safe, Green Drivers achieve “MPG” improvements between 7% and 11%;
· Green Drivers average 2 additional miles per gallon versus higher risk Red
Drivers;
· Red Drivers visit fuel stations every 3 days on average compared to 5.1 days
on average for Green Drivers;
There is a strong correlation between driving risk and fuel consumption.

GreenRoad Technologies

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

This paper examines how the CO2 cost of implementing and operating some ITS schemes could be almost halved  through  the  use  of  renewable  energy.  A  case  study  analysis  of  an  ITS  scheme  which  includes 40Km  of  Variable  Mandatory  Speed  Limits  (VMSL)  and  road  lighting  shows  that  wind  turbine generation is a feasible power supply option, with an estimated payback period of 19 years. Given that the expected life of a wind turbine is 25 years, this arrangement is demonstrated to be an economically viable solution. Climate change poses a major challenge to society and opportunities such as this to reduce CO2 emissions should be implemented to help address this global issue.

Mouchel

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York

In several cities in the Netherlands, ITS strategies are developed with the objective to
improve the quality of the air (NOx en PM10). This paper presents the ‘state-of-art’, based
on several studies that have been carried out recently by DHV in this field. At first, it will
describe a project on the ‘Maasboulevard’ in the City of Rotterdam. In this project we
have established a ‘green’ coordination between traffic signals on one of the main
arterials of the city. This ‘green’ coordination proved to have a significant effect on the
reduction of emission levels of air pollutants. Secondly, the paper will describe a research
project in the City of Apeldoorn. Here we have studied for an environmental friendly way
of optimization of traffic signals, and in the same time we have developed a procedure to
calculate the effects of changes in traffic dynamics, obtained by this optimization, on the
emission of air pollutants in a micro simulation model (AIMSUN). Thirdly, we will
describe a pilot for the implementation of an ITS strategy that’s reduces noise and air
quality in the City of Arnhem. In this project DHV has written an action plan for the
implementation of this environmental friendly ITS strategy. The paper will end with
some concluding remarks concerning the general effects that ITS strategies can possibly
have on the air quality in urban areas, based on the three case studies presented.

DHV BV

Presented at the 15th World Congress on Intelligent Transport Systems, November 16-20, 2008, New York, New York