HOV lane management

Summary: The decision to designate a traffic lane as a High Occupancy Vehicle lane is based on traffic analysis, computer simulations, and mathematical models showing the effects of implementation.

High occupancy vehicle (HOV) lanes are intended to improve automobile transportation efficiency by reserving certain traffic lanes for vehicles carrying at least two or three people. The idea is to encourage carpooling by allowing cars with multiple occupants to use a dedicated lane and thus reduce the number of cars on the road relative to the number of people traveling. Sometimes traffic lanes are designated HOV only at certain times of the day, or they may be used under special circumstances by buses, hybrid power vehicles, or other single-passenger vehicles. HOV lanes have been tested or used in many countries, including the United States, Canada, Spain, the United Kingdom, Norway, Austria, Indonesia, Australia, and New Zealand. Mathematical modeling, data analysis, and computer simulation are widely used for making decisions regarding when and where to use HOV lanes, for designing their construction and geometric properties, and for evaluating their safety and effectiveness. Many mathematical modelers are using cross-disciplinary concepts and approaches to analyze traffic. For example, engineer Morris Flynn and mathematicians Aslan Kasimov, Jean-Christophe Nave, Rodolfo Rosales, and Benjamin Seibold modeled traffic jams using continuous density and flow functions similar to those used for modeling fluid flow and the propagation of detonation waves. Analogous to the traveling nonlinear wave solutions called “solitons,” they christened traffic waves “jamitons.”

HOV lanes are typically most useful in regions that have severe traffic congestion and many vehicles carrying only the driver. The opportunity to use less-congested, quickly moving HOV lanes is intended as an incentive to encourage drivers to decide to use carpooling or to carry passengers, with the overall intent of reducing traffic jams and accidents caused by traffic volume and lane changing. Studies of HOV lane usage and effectiveness showed that, as of 2008, 21 U.S. states had HOV lanes for a total of 1,745.14 miles with an average density of 833 vehicles per lane per hour and a total of over 276 million miles of vehicle travel. Exclusive HOV lanes were most common (993.27 miles) and carried the highest density of traffic (an average of 906 vehicles per hour), followed by normal lanes designated HOV in certain periods (545.82 miles, 790 vehicles per hour) and shoulder or parking lanes designated HOV in certain periods (206.6 miles, 596 vehicles per hour).

Experience with HOV lanes is mixed, although it should be noted that this is a relatively new method of organizing transportation and that local variation in conditions and implementation could explain why some projects were more successful than others. An example of a successful HOV implementation was that introduced in 1998 near Leeds, United Kingdom (the first HOV lanes in the United Kingdom). Prior to HOV lane implementation, 30% of the cars had two or more occupants, and a journey that should take three minutes if traffic were moving freely regularly took more than 10 minutes. After implementation of the HOV lanes, traffic was reduced 10% to 20%, journeys were quicker for both HOV and non-HOV traffic, lane violations were low, casualties were reduced 30%, and noise reduction was noticeable—although little change was noted in air quality. In the United States, an HOV lane scheme near Washington, D.C., for vehicles carrying four or more occupants, proved successful, with the HOV lanes operating at twice the speed of travel of the regular lanes. However, a study of HOV lanes in San Francisco, California, found that they actually increased congestion. HOV lanes have also been criticized on grounds of safety, because of the differing speeds of traffic in adjacent lanes, and as a violation of the right of motorists to freely use highways paid for with their tax dollars.

Mathematicians continue to investigate issues for HOV lane design, implementation, and management. Analyses using concepts from fields such as geometry, graph theory, and statistics help designers optimize features like lane setbacks, entrance and egress paths, gates and signals, and shoulder widths. Speed contour plots can be used to visualize recurrent blockages, while probability models and scatterplots can be used to quantify and display spatial distribution of accidents as functions of one or more variables. Other mathematicians seek to simplify existing multiparameter models, which may rely on unobservable quantities, using smaller sets of physical and measurable variables in order to study the impact of design features and traffic behavior. Yet others have used logit-type models to investigate economic concerns, like converting HOV lanes to high occupancy toll (HOT) lanes.

Bibliography

Kwon, Jaimyoung, and Pravin Varaiya. “Effectiveness of High Occupancy Vehicle (HOV) Lanes in the San Francisco Bay Area.” Transportation Research Part C: Emerging Technologies 16, no. 1 (February 2008). http://paleale.eecs.berkeley.edu/~varaiya/papers‗ps.dir/HOV.pdf.

Menendez, Monica. An Analysis of HOV Lanes: Their Impact on Traffic. Saarbrücken, Germany: VDM Verlag, 2008.

U.S. Department of Transportation, Federal Highway Administration. “High Occupancy Vehicle (HOV) Lanes by State.” http://www.fhwa.dot.gov/policyinformation/tables/03.cfm.