Evaluation of benefits to the federal highway program provided by regulation of vehicle noise emissions.

Mode of access: Internet.

Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sizedtrucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Evaluate traffic noise level based on traffic microsimulation combined with a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sized trucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Truck noise IV-G. Field test results on a heavy duty, diesel truck having reduced noise emissions. Seventh report.

Transportation Department, Office of Noise Abatement, Washington, D.C.

FHWA highway traffic noise prediction model. Final report.

Mode of access: Internet.

Noise abatement tradeoff considerations. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An investigation of site effects on roadside measurement of truck noise. Final report.

Transportation Department, Office of Noise Abatement, Washington, D.C.

Truck noise IV-A: project summary - the reduction of noise levels on the International Harvester quieted truck. Final report.

Transportation Department, Office of Noise Abatement, Washington, D.C.

Truck noise IV-H: post-fleet test results on heavy duty diesel trucks having reduced noise emissions. Final report.

Transportation Department, Secretary of Transportation, Washington, D.C.

Noise insulation of residences near freeways. Final report.

Mode of access: Internet.

Truck noise XI. Evaluation and reduction of heavy-duty truck noise. Final report.

Transportation Department, Office of Noise Abatement, Washington, D.C.

Roadside barrier effectiveness - noise abatement program. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

User's manual: FHWA highway traffic noise prediction model - SNAP 1.0. Final report.

Federal Highway Administration, Environmental Design and Control Division, Washington, D.C.

User's manual: FHWA Level 2 highway traffic noise prediction model - STAMINA 1.0. Final report.

Federal Highway Administration, Environmental Design and Control Division, Washington, D.C.