Risk analysis of traffic and revenue forecasts for road investment projects

Hing Keung William Lam, M. L. Tam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)


In this paper, a simulation model for risk analysis making use of the Monte Carlo technique is devised to incorporate the uncertainty in traffic and revenue forecasts for road investment projects. The risk analysis would give the traffic and revenue forecasts in specified years with a particular probability, or vice versa. These traffic and revenue forecasts and their probability levels will help the authorities or the private sector evaluate road investment projects scientifically and systematically. A case study of the proposed Zhuhai Neilingding Crossing is used to illustrate the application of the risk analysis model. Demand elasticity is also introduced to investigate the effects of different toll charges on traffic demand, together with sensitivity analysis on some of the key variables behind the traffic and revenue forecasts.
Original languageEnglish
Pages (from-to)19-27
Number of pages9
JournalJournal of Infrastructure Systems
Issue number1
Publication statusPublished - 1 Jan 1998

ASJC Scopus subject areas

  • Civil and Structural Engineering


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