This paper addresses the problem of quantifying the cross-country speed capability of military vehicles. While numerous tests have been run to evaluate various aspects of cross-country speed, such as obstacle crossing capability and maximum speed over a specified standard course, quantitative evaluation of the total man-machine system has only been superficially attempted. Recognizing the complex interactions of the man-machine system within various environments, the project was designed specifically to allow separation of various factors in order to determine the relative cross-country performance of vehicles.Two separate tests were established. The first test determined the relative cross-country performance of nine different vehicles by utilizing 18 drivers and 27 test courses in three varied terrains for a total of 563 test runs. Interesting ancillary results indicated the effects that experience and learning have on driver performance and to what extent variations among drivers influence the outcome of a vehicle test.The second test quantified the effect of varying driver's vision on the cross-country performance of an armored, track-laying vehicle.The test vehicle was driven in three distinct vision configurations. Testing involved 81 runs by nine drivers over nine courses on a single terrain.In both tests the data consisted of the average time required for the vehicle to travel between two established points with a free path in between. Terrain areas were selected to minimize the go/no-go obstacles while still requiring rigorous cross-country operation.Due to time limitations only preliminary results are presented for the second test program.


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    Title :

    A Statistical Approach of Determining Cross-Country Speed


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    1969 International Automotive Engineering Congress and Exposition ; 1969



    Publication date :

    1969-02-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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