The study evaluates lane management strategies along one of the most highly traveled sections of Interstate 81 in the state of Virginia by using the INTEGRATION traffic simulation software. The lane management strategies considered include the separation of heavy-duty trucks from light-duty traffic, the restriction of trucks to specific lanes, and the construction of climbing lanes at strategic locations. Overall, the results demonstrate that a physical separation of heavy-duty trucks from the regular traffic offers the maximum benefits and that restricting trucks from the use of the leftmost lane offers the second-highest benefits in terms of efficiency, energy, and environmental impacts.
INTEGRATION Rel. 2.3 for Windows—User's Guides, Vols. 1 and 2. M. Aerde and Associates, Blacksburg, Va., 2003.
4.
SamuelP., PooleR., and Holguin-VeraJ. R.Toll Trucks: A New Path Toward Safer and More Efficient Freight Transportation.Policy Study N 294. Reason Public Policy Study Institute, Los Angeles, Calif.,2002.
HoelL. A., and PeekJ. L.. A Simulation Analysis of Traffic Flow Elements for Restricted Truck Lanes on Interstate Highways in Virginia.Virginia Transportation Research Council, Charlottesville, 1999.
7.
CateM. A., and UrbanikT.IIAnother View of Truck Lane Restrictions. In Transportation Research Record: Journal of the Transportation Research Board, No. 1867, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 19–24.
8.
A Policy on Geometric Design of Highways and Streets.American Association of State Highway and Transportation Officials, Washington, D.C., 1994.
9.
TruckSim.Mechanical Simulation, Ann Arbor, Mich.www.carsim.com.
10.
Interstate 81 Improvement Study—Town of Christiansburg, City of Salem, Counties of Montgomery, Roanoke and Botetourt—Study Area # 5.HDR Engineering, Norfolk, Va., 1998.
11.
DionF., RakhaH., and KangY. S.. Comparison of Delay Estimates at Undersaturated and Oversaturated Pre-timed Signalized Intersections.Transportation Research, Part B: Methodological, forthcoming.
12.
RakhaH., MedinaA., SinH., DionF., Van AerdeM., and JenqJ.. Traffic Signal Coordination Across Jurisdictional Boundaries: Field Evaluation of Efficiency, Energy, Environmental, and Safety Impacts. In Transportation Research Record: Journal of the Transportation Research Board, No. 1727, TRB, National Research Council, Washington, D.C., 2000, pp. 42–51.
13.
AhnK., RakhaH., TraniA., and Van AerdeM.. Estimating Vehicle Fuel Consumption and Emissions Based on Instantaneous Speed and Acceleration Level.Journal of Transportation Engineering, ASCE, forthcoming.
14.
RakhaH. A., and Van AerdeM. W.. Comparison of Simulation Modules of TRANSYT and INTEGRATION Models. In Transportation Research Record 1566, TRB, National Research Council, Washington, D.C., 1996, pp. 1–7.
15.
RakhaH., LucicI., DemarchiS., SettiJ., and Van AerdeM.. Vehicle Dynamics Model for Predicting Maximum Truck Accelerations.Journal of Transportation Engineering, ASCE, Vol. 127, No. 5, 2001, pp. 418–425.
16.
RakhaH., and LucicI.. Variable Power Vehicle Dynamics Model for Estimating Maximum Truck Acceleration Levels.Journal of Transportation Engineering, ASCE, Vol. 128, No. 5, 2002, pp. 412–419.
17.
RakhaH., and CrowtherB.. Comparison and Calibration of FRESIM and INTEGRATION Steady State Car-Following Behavior.Transportation Research, Vol. 37A, 2003, pp. 1–27.
18.
RakhaH., Van AerdeM., BloombergL., and HuangX.. Construction and Calibration of Large-Scale Microsimulation Model of the Salt Lake Area. In Transportation Research Record 1644, TRB, National Research Council, Washington, D.C., 1988, pp. 93–102.
19.
User's Guide to MOBILE5A: Mobile Source Emissions Factor Model.U.S. Environmental Protection Agency, Washington, D.C., 1993.
20.
2002 Average Daily Traffic Volumes with Vehicle Classification Data on Interstate, Arterial and Primary Routes.Virginia Department of Transportation, Richmond, 2003.
21.
WillumsenL. G.Estimation of an O-D Matrix from Traffic Counts: A Review. Working Paper 99. Institute for Transport Studies, Leeds University, Leeds, England,1978.
22.
Van ZuylenJ. H., and WillumsenL. G.. The Most Likely Trip Matrix Estimated from Traffic Counts.Transportation Research, Vol. 14B, 1980, pp. 281–293.
23.
Van AerdeM., RakhaH., and ParamahamsanH.. Estimation of Origin–Destination Matrices: Relationship Between Practical and Theoretical Considerations. In Transportation Research Record: Journal of the Transportation Research Board, No. 1831, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 122–130.
24.
RakhaH., and Van AerdeM.. Statistical Analysis of Day-to-Day Variations in Real-Time Traffic Flow Data. In Transportation Research Record 1510, TRB, National Research Council, Washington, D.C., 1995, pp. 26–34.
