Microsimulation and Analytical Models
Traffic simulation techniques have been used since the early days of the development of traffic theory. The ever-increasing power of personal computers and search for ITS solutions to growing urban transport problems has led to the emergence of a number of microscopic simulation models as practical traffic analysis tools.
There is great potential for useful application of microsimulation models to the analysis of complex traffic problems in urban areas, alongside the analytical techniques that are in use. Microsimulation is useful due to increasing levels of system complexity and uncertainty involved in the operation of urban traffic networks. However, concerns are often expressed regarding misuse of microsimulation. Response to a survey of microsimulation model users was summarised as "microsimulation is useful but dangerous" (Algers et al 2000; Fox 2000). The traffic flow theory textbook by Drew (1968) stated: "Simulation is a powerful tool, and like all powerful tools it can be dangerous in the wrong hands. Pitfalls exist in simulation as in every human attempt to abstract and idealize."
Users of microsimulation models should not assume that a more detailed model will necessarily result in reduced model error. This is because, it is likely that, while model specification error will decrease with increased model detail (complexity), the total measurement error will increase due to the increased model complexity (more variables each associated with a degree of measurement error) as indicated by the above figure (Alonso 1968; Richardson 2001). Thus, there is an optimum degree of model complexity. In fact, using more complex models with bad data will increase the total model error, and the effects of bad data cannot be overcome by using more complex models (Richardson 2001). This consideration applies to all models, simulation or analytical.
Akçelik and Besley (2001) discussed the compatibility between microsimulation methods and established analytical techniques that are used in traffic engineering (paper available for download under the reference list below). They discussed several key components of traffic models:
(i) the use of simulation for capacity analysis;
(ii) modelling of queue discharge (saturation) flow rate, queue discharge speed and other queue discharge parameters at signalised intersections, and relating them to the general queuing, acceleration and car-following models used in microsimulation;
(iii) modelling of gap-acceptance situations at all types of traffic facilities, e.g. permitted or filter turns (right-turn or left-turn) at signalised intersections, minor movements at give-way (yield) or stop signs, traffic entering unsignalised roundabouts, and freeway and other traffic merging situations; and
(iv) estimation of lane flows at intersection approaches, and relating this to lane changing models used in microsimulation.
The consistency of definitions and measurement methods for traffic performance variables such as delay (stopped, geometric, etc) and queue length (cycle average and back of queue) is an important issue. Comparison of specific microsimulation and analytical model components is useful towards model benchmarking for evaluation of new and existing models (Yoshii 1999).
For an introductory discussion and an extensive reference list on simulation models, refer to the Highway Capacity Manual 2000 edition, Chapter 31 (TRB 2000).
Next Generation Simulation Program, NGSIM
The objective of FHWA's Next Generation Simulation (NGSIM) program is to develop a core of open behavioral algorithms in support of traffic simulation with a primary focus on microscopic modeling, including supporting documentation and validation data sets. detailed documentation is available from the FHWA NGSIM web site.
AKÇELIK, R., and BESLEY M. (2001). Microsimulation and analytical methods for modelling urban traffic
Paper presented at the Conference on Advance Modeling Techniques and Quality of Service in Highway Capacity Analysis, Truckee, California, USA. (231KB). Reprint with revisions. Made available: 12 Oct 2001.
ALGERS, S. et al (2000). Review of Micro-Simulation Models. SMARTEST (Simulation Modelling Applied to Road Transport European Scheme Tests) Project Report. Institute of Transport Studies, University of Leeds, UK. SMARTEST web site
ALONSO, W. (1968). The quality of data and choice and design of predictive model. Highway Research Board Special Report 97, pp 178-192.
DREW, D.R. (1968). Traffic Flow Theory and Control. McGraw-Hill, New York.
FHWA (1982). Application of Traffic Simulation Models. Proceedings of a Conference on the Application of Traffic Simulation Models, June 1981. Federal Highway Administration, US Department of Transportation. Techshare Report FHWA-TS-82-207.
RICHARDSON, A.J. (2001). Never mind the data - feel the model
Keynote paper presented at the International Conference on Transport Survey Quality, Kruger National Park, South Africa. (200KB)
TRB (2000). Highway Capacity Manual. Transportation Research Board, National Research Council, Washington, D.C., U.S.A.
YOSHII, T. (1999). Standard Verification Process for Traffic Simulation Model - Verification Manual. Draft Report. Kochi University of Technology, Kochi, Japan.