HOV Priority
Strategies to Improve Transit and Ridesharing Speed and Convenience
~~~~~~~~~~~~~~
Victoria Transport Policy Institute
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Updated 21 March 2019
This chapter describes High Occupant Vehicle (HOV) priority strategies, which give priority to public transit vehicles, vanpools and carpools in traffic and parking.
HOV Priority refers to strategies that give priority to High Occupant Vehicles (also called Rideshare Vehicles), including transit buses, vanpools and carpools. HOV Priority is a major component of many regional TDM programs. Two, three or four occupants (indicated as 2+, 3+ or 4+) may be required to be considered an HOV, depending on circumstances. This is opposed to Single Occupant Vehicles (SOVs).
HOV Priority includes:
· HOV highway and arterial lanes. These are sometimes reversible (or “counter flow” lanes), which means that they provide traffic capacity in the peak direction. Lanes open only to buses are called busways. These are a type of managed lanes (WSDOT, 2001; Obenberger, 2004; Goodin, 2005).
· High Occupancy Toll (HOT) lanes. These are HOV lanes that also allow low occupancy vehicles if they pay a toll, as described in Road Pricing.
· Busways, that is, special lanes dedicated to transit buses, often incorporating other features to insure high quality transit service. Priority bus service is sometimes called Bus Rapid Transit, and busway are sometimes called Quickways.
· Queue-jumping lanes (other vehicles must wait in line to enter a highway or intersection, but HOVs enter directly).
· Intersection controls that give priority to HOVs. For example, a traffic light might be set to stay green for several extra seconds if that allows a bus to avoid stopping.
· Complete Streets policies and Streetscaping design changes to favor High Occupant Vehicles, such as improved bus stops and bus pullouts.
· Preferred parking spaces or parking fee discounts provided to rideshare vehicles (Parking Management).
· Special benefits to HOV riders, often included in Commute Trip Reduction programs.
· Prioritize use of curb space and loading rights to favor higher-value trips and space-efficient modes, such as public transit and taxi loading (Hao 2018).
Bus Rapid Transit (BRT) is a term used for a set of Transit Improvements that include grade-separated right-of-way and other transit priority measures, comfortable stations, high-quality vehicles (high capacity, easy to board, quiet, clean and comfortable to ride), frequent service, convenient user information, efficient pre-paid fare collection, and efficient operations.
HOV Priority is a form of Prioritization that provides travel time savings, operating cost savings and increased travel reliability to space efficient modes under congested modes. HOV lanes typically provide time savings from 0.5-minute per mile on arterial streets up to 1.6-minutes per mile on congested freeways. Queue-jumper HOV facilities can provide savings up to 20 minutes (Turnbull, Levinson and Pratt (2006). Many travelers place a high value on these time savings, particularly if unpredictable delays are reduced.
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Under, Over or Through Grade separation means that high occupancy vehicles have separate right-of-way, so they are not delayed by traffic congestion. This can be accomplished by providing separate rights-of-way, giving transit vehicles priority at signaled intersections, creating grade-separated intersections, and locating lines underground (subways) or above roadways (elevated lines and SkyTrain). All can be effective, although from a users perspective underground tends to be least pleasant, since users must descend underground to stations and have no views while traveling. Fully grade-separated underground and elevated systems are generally faster, but surface-level systems eliminate the need to descend/ascend to stations, which can save two or three minutes per trip, making them relatively attractive, particularly for shorter trips. Many transit systems use a combination of these features to increase transit speeds. |
HOV Priority effectiveness depends on maintaining significant travel advantage for efficient modes. Ideally, HOV lanes should be uncongested, maintaining Level Of Service (LOS) A or B, which means less than about 1,000 vehicles per hour on a grade-separated highway and half that on a surface street (Congestion). In practice, HOV lanes often have greater volumes and therefore lower speeds, and so provide modest travel time savings. For example, Kwon and Varaiya (2008) found that 18% of all HOV-miles during the AM peak hour and 32% during the PM peak hour have speeds below 45 mph for more than 10% of weekdays, and so only offer small travel time saving, averaging 1.7 minutes for a 10-mile route (although HOV travel times are somewhat more reliable), which they consider insufficient to motivate many commuters to carpool.
There is often pressure to compromise this advantage to achieve other objectives, for example, to reduce HOV requirements, such as from 3+ to 2+, and to allow single occupant vehicles such as motorcycles, hybrid cars and taxis; and transportation agencies are sometimes under financial pressure to maximize the number of single-occupant vehicles allowed if they pay on High Occupant Toll (HOT) lanes. Buses typically impose about two Passenger Car Equivalents (PCEs) and vans about 1.2. Thus, if there are 100 buses during a peak period, causing 200 total PCEs, the available capacity totals about 800 PCEs on grade-separated highways and just 300 PCEs on surface streets. In several cases these limits have been exceeded, spoiling the HOV advantage and contradicting strategic transport planning objectives.
The value of HOV Priority depends on the criteria and assumptions used in evaluation (Wellander and Leotta, 2001). HOV priority measures can be justified as a more efficient and equitable allocation of road space (travelers who share a vehicle and therefore impose less congestion on other road users, are rewarded by bearing less congestion delay), an efficient use of road capacity (they can carry more people than a general use lane), and as an incentive to shift to more efficient modes. HOV lanes usually carry fewer vehicles than other lanes but they often carry more people.
Evaluation also depends on whether the HOV facility uses an existing highway lane or is new capacity, and whether the alternative to HOV lanes would be no additional capacity, additional general use lane, or an additional transit lane (Kwon and Varaiya 2008). Some critics oppose HOV lanes on the grounds that they increase total road capacity and encourage longer-distance commuting (Leman, Schiller, Pauly, 1996; Szoboszlay, 1999), while others oppose them on the grounds that they are underutilized (Orski, 2001). HOV lanes often take years to reach their full potential, since they affect long-term decisions such as where consumers live or choose to work.
Below are criteria used to evaluate HOV facilities in Oregon (www.hov.odot.state.or.us).
· Total Person Throughput. This is a measure of how many people move past a point in a given period in time. Traditionally transportation agencies measure only the number of vehicles, but on HOV lanes they measure the number of vehicles, number of people per vehicle, and the number of people using transit. Increased person throughput and higher average vehicle occupancy are goals.
· Travel Times. Transportation agencies measure travel time to determine how long it takes HOVs, SOVs and freight vehicles to travel on roads with HOV lanes. No net increase in travel times during the afternoon rush hour is a goal.
· Safety. Agencies measure the accident and incident rates on sections of highway before and after HOV lanes are established. No increase in incident and crash rates is a goal.
· Enforcement. This is a qualitative measure of how enforceable a HOV lane is. Agencies will track the number of tickets issued, the HOV lane violation rate and observations of police enforcing the lane. Minimal violation rate, and maximum perception that users obey HOV rules is a goal.
· Beginning and Ending Transitions. The beginning and ending of an HOV lane can create weaving movements or other traffic flow problems. Agencies will monitor the traffic operations to evaluate how HOV lanes affect traffic flow.
· Traffic Diversion. There is a concern that excessive delays in general purpose lanes may cause traffic to divert to parallel routes. Traffic counts will be taken before and after HOV lanes are established to determine if significant traffic is diverted. The goal is to minimize traffic diversion.
· HOV Lane Utilization. This is a measure of how many vehicles are using the HOV Lane in a given time period, and how this compares with their maximum capacity.
· Transit Ridership. Agencies will track how many people ride transit during peak periods when the HOV lane is in service.
· Increase in Transit Service. Agencies will measure the increase in transit service and compare it to the increase in transit ridership. This would help understand the increase in transit ridership due to the HOV project compared to normal increases in ridership that result from an increase in transit service (without an HOV lane).
· Number of People Per Vehicle. Agencies observe traffic to determine the number of people per vehicle during peak periods.
· Park & Ride Use, Van Pools & Employer Programs. Agencies will track the use of the Park & Ride and vanpools.
· Public Perception. Agencies survey commuters and compare responses before and after HOV lanes are established.
HOV facilities can be implemented by adding new road capacity designated for HOVs. Sometimes, existing lanes are converted to HOV use (called “take a lane”). HOV lanes can be separated from regular traffic using signs, markings, painted buffer or physical barriers. HOV lanes can be 24 hour or designated for peak hours only, and some use reversible lanes. HOV programs are most successful as part of an integrated regional transportation strategy that includes other improvements and incentives for transit and rideshare use.
(Turnbull, Levinson and Pratt, 2006) suggests that HOV highway lanes are most effective at reducing automobile use on congested highways to large employment centers in large urban areas with 25 or more buses per hour during peak periods, where transit provides time savings of at least 5 to 10 minutes per trip. Turnbull (2001) provides guidelines for implementing HOV facilities which suggest that they are most effective in major urban areas with large employment centers, heavy congestion and supportive TDM policies.
HOV Priority improves the performance of transit and ridesharing (a direct benefit to users), and encourages shifts from SOV to HOV travel modes (which benefits all road traffic). Travel time savings and mode shift effects depend on circumstances, including the degree of congestion and the facility design. Turnbull, Levinson and Pratt (2006) provide detailed discussion of the travel effects of various types of HOV facilities.
Comsis (1993) and Turnbull, Levinson and Pratt (2006) find that HOV facilities can reduce vehicle trips on a particular roadway by 4-30%. Ewing (1993) estimates that HOV facilities can reduce peak-period vehicle trips on individual facilities by 2-10%, and up to 30% on very congested highways if HOV lanes are separated from general-purpose lanes by a barrier. One study estimates that HOV lanes can reduce up to 1.4% of VMT and up to 0.6% of vehicle trips in a region (Apogee 1994).
Adding HOV lanes can be considered to increase total automobile travel compared with no additional road capacity, and HOV priority can sometimes encourage longer-distance trips (and therefore sprawl), and may attract some travelers from other alternative modes, such telecommuting and cycling.
The travel impact of HOT lanes depends on the price structure used. If the price is too low, the facility will experience congestion, reducing the performance for both single-occupant vehicle users and HOV users, resulting in reduced transit and ridesharing. It is therefore important for the sake of overall transportation system efficiency that HOT facilities be managed to favor HOV performance.
Table 1 Travel Impact Summary
|
Travel Impact |
Rating |
Comments |
|
Reduces total traffic. |
2 |
Encourages HOV use during peak periods. |
|
Reduces peak period traffic. |
3 |
|
|
Shifts peak to off-peak periods. |
0 |
|
|
Shifts automobile travel to alternative modes. |
3 |
|
|
Improves access, reduces the need for travel. |
0 |
|
|
Increased ridesharing. |
3 |
|
|
Increased public transit. |
3 |
|
|
Increased cycling. |
0 |
|
|
Increased walking. |
0 |
|
|
Increased Telework. |
0 |
|
|
Reduced freight traffic. |
0 |
|
Rating from 3 (very beneficial) to –3 (very harmful). A 0 indicates no impact or mixed impacts.
Benefits include increased travel speeds and reliability for HOV passengers. This increases Transportation Options by allowing travelers to choose between driving alone in congestion or bypassing congestion in an HOV. HOT facilities add a third option: SOV drivers can avoid congestion by paying a toll. This allows individual consumers to choose which option best suits their needs for each trip.
HOV Priority measures can increase transit service efficiency by increased ridership per vehicle-hour and reduced fuel consumption per vehicle-mile. For example, an HOV Priority system that increases average travel speeds on a particular transit route from 25 to 20 minutes increases maximum carrying capacity and revenue per bus-hour by 20%.
To the degree that HOV Priority causes urban peak travelers to shift from driving to alternative modes it can be an effective Congestion Reduction strategy, and help achieve other TDM objectives. Because HOV facilities tend to have their greatest impact on highly congested urban corridors, they can provide significant benefits in terms of road and parking facility cost savings, transit system operating cost savings, congestion and pollution reductions, and consumer benefits (Transit Evaluation).
Using a general equilibrium model, Zhao (2019) finds that HOV lanes reduce traffic congestion and improve welfare, but the fall in transportation cost leads to urban sprawl, which results in higher dwelling energy use and a larger carbon footprint. As a result, HOV lanes have little overall effect on total energy consumption and carbon emissions.
Pravin Varaiya (2008) argues that 2+HOT facility benefits are exaggerated. His analysis indicates that 2+HOT facilities (tolled SOVs allowed access alongside free 2+HOVs) will not recover their operating costs, let alone their capital costs, but a two-lane 3+HOT facility (tolled SOVs allowed access alongside free 3+HOVs) can recover operating cost if the general-purpose lanes are allowed to become congested.
HOV Priority can reduce pollution emissions by smoothing vehicle flow and attracting travelers from automobiles. Table 2 summarizes the estimated pollution emission reductions from particular bus priority measures in London.
Table 2 Bus Priority Measures in London (Bayliss 1989)
|
Measure |
Proportion of Buses Affected |
Exhaust Emission Reduction Per Bus Affected |
|
Peak period bus lane |
5% |
20% |
|
Contra-flow lane, all day |
2% |
35% |
|
Signal pre-emption |
20% |
12% |
|
Segregated bus street |
2% |
60% |
|
Priority turns |
5% |
7% |
Costs include project construction, management and enforcement. Some critics argue that HOV lanes encourage urban sprawl and contribute to poor air quality (Leman, Schiller and Pauly, 1994), while others argue that they are an inefficient use of road capacity (Orski, 2001). A study by Varaiya (2005) found that 2-Plus carpool lanes in Southern California have more congestion delay and less maximum vehicle flow than general purpose lanes. HOV lanes that increase total road capacity can increase overall vehicle capacity and trips, but less than if the additional capacity were a general use lane. HOV lanes may increase crash rates due to conflicts between vehicles in higher-speed HOV lanes and vehicles in lower speed general use lanes (Cothron, et al, 2005).
Table 3 Benefit Summary
|
Objective |
Rating |
Comments |
|
Congestion Reduction |
3 |
HOVs avoid congestion, encourages mode shifting. |
|
Road & Parking Savings |
0 |
Involves project costs, but usually cheaper for roads and parking than accommodating the same number of trips by SOV. |
|
Consumer Savings |
2 |
Provides consumer time savings. |
|
Transport Choice |
3 |
Allows consumers to avoid congestion by using HOV modes. |
|
Road Safety |
0 |
Mixed. Safety benefits from reduced driving may be offset by operational hazards. |
|
Environmental Protection |
2 |
Encourages mode shifting. |
|
Efficient Land Use |
-1 |
May encourage longer-distance commutes and sprawl. |
|
Community Livability |
1 |
Reduces automobile trips. |
Rating from 3 (very beneficial) to –3 (very harmful). A 0 indicates no impact or mixed impacts.
Some people consider HOV Priority unfair because it favors one group (HOV passenger) over other road users. Others consider HOV priority a fairer allocation of road space by giving travelers who use less space, and therefore contribute less to traffic congestion, priority over those who use more space. Some critics argue that HOV lanes do not meet the needs of people who cannot use transit (e.g., parents who drive alone to pick up their children are cited as examples), but others argue that many people who drive alone could use HOVs, but choose not to, and that SOV users benefit from reduced congestion if HOV Priority causes mode shifting.
HOV facilities benefit transit and rideshare passengers, which includes a proportionally large share of lower income and transportation disadvantaged people, and is therefore progressive with respect to income and need. HOT lanes have been criticized as elitist because wealthy motorists are able to avoid congestion experienced by lower-income motorists (Pricing Evaluation). HOV Priority can help achieve Basic Mobility by favoring basic modes (transit and ridesharing) over automobile travel.
Table 4 Equity Summary
|
Impacts |
Rating |
Comments |
|
Treats everybody equally. |
0 |
Mixed. Depends on assumptions and circumstances. |
|
Individuals bear the costs they impose. |
3 |
Reduces congestion externalities. |
|
Progressive with respect to income. |
3 |
Lower-income people tend to rely on HOVs. |
|
Benefits transportation disadvantaged. |
3 |
Benefits HOV users, which includes transportation disadvantaged people. |
|
Improves basic mobility. |
3 |
Improves basic access. |
Rating from 3 (very beneficial) to –3 (very harmful). A 0 indicates no impact or mixed impacts.
HOV facilities are most appropriate on congested highways where it is technically feasible to convert or add lanes, where HOV use could increase, and which would result in significant time savings to users. Transit priority traffic controls can be implemented on surface streets in any urban area. Resort communities can give traffic and parking priority to buses. Developers and businesses can provide priority parking for HOVs, and transit priority in loading areas.
Table 5 Application Summary
|
Geographic |
Rating |
Organization |
Rating |
|
Large urban region. |
3 |
Federal government. |
3 |
|
High-density, urban. |
3 |
State/provincial government. |
3 |
|
Medium-density, urban/suburban. |
2 |
Regional government. |
3 |
|
Town. |
1 |
Municipal/local government. |
3 |
|
Low-density, rural. |
0 |
Business Associations/TMA. |
2 |
|
Commercial center. |
3 |
Individual business. |
1 |
|
Residential neighborhood. |
1 |
Developer. |
1 |
|
Resort/recreation area. |
3 |
Neighborhood association. |
1 |
|
|
|
Campus. |
3 |
Ratings range from 0 (not appropriate) to 3 (very appropriate).
Incentive to Use Alternative Modes
HOV programs support and are supported by other Transit and Rideshare encouragement efforts, including Commute Trip Reduction, Parking Management, Park-and-Ride, and Marketing efforts. HOV Priority is a way to Prioritize Transportation and Reallocate Road Space, supported by Complete Streets policies.
HOV facilities are implemented through partnerships between provincial/state departments of transportation, local and regional transportation and planning authorities, ridematching organizations, Transportation Management Associations, and highway patrol and enforcement bodies.
HOV facilities are often expensive to construct, may cause traffic operation and enforcement problems, and may be controversial. SOV drivers may oppose HOV on the grounds that they are unfair and ineffective, in preference to general-purpose lanes. Others may oppose HOV facilities on the grounds that they increase total road capacity, leading to increased total vehicle traffic and urban sprawl.
Turnbull, Levinson and Pratt (2006) and Turnbull (2001) provide guidelines for effective HOV facilities. These include:
· More than one million people in the metropolitan region.
· High levels of traffic congestion in the corridor.
· Access to an employment center with 100,000 or more workers.
· Well designed facilities.
· 25 or more buses during peak periods.
· Supportive TDM programs and policies with ongoing marketing.
· Visible enforcement.
· Cooperation among responsible transportation agencies.
HOV Priority by itself is generally insufficient to motivate many people to shift mode. Many facilities provide only one or two minutes travel time savings for a typical commute, much less than the total incremental time costs of organizing carpools or using public transportation. However, they can be very useful as part of a comprehensive package of measures that encourage ridesharing and public transit.
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A drunk was hanging out on a street corner. Another drunk walks by holding a large bag. The first drunk asked, “Hey, what have you got in that bag there? “Wine. Bottles of very valuable wine,” was the reply. “How many bottles do you have in that bag then?” the first drunk asked. “I’m not telling,” he replied. “Will you share some with me?” asked the first drunk. “I’ll tell you what,” replies the second drunk, “If you guess how many bottles I have in this bag – I’ll give both of them to you!” |
The Virginia Department of Transportation (VDOT) launched HOVcalculator.com, a Web site that allows Northern Virginia commuters to calculate the time they could save by carpooling on the high-occupancy vehicle (HOV) lanes instead of driving in the regular, congested lanes. VDOT research reveals that before commuters try the HOV lanes, they want to know specifically how many minutes they will save. VDOT developed HOVcalculator.com so commuters could see the potential time savings for themselves and try carpooling even if only once a week.
HOVcalculator.com users enter the typical time of their commutes as well the longest time their commutes may take. They also enter the names of landmarks closest to their home and office and the calculator tells them how many minutes they would save by using the HOV lanes. The calculator also offers information about the nearest park-and-ride lots and their features-such as bus service or vanpools. Data for HOVcalculator.com was gathered under typical morning rush-hour conditions from travel-time studies conducted by the Council of Governments and VDOT.
Comsis (1993), and Turnbull, Levinson and Pratt (2006) describe numerous successful HOV facilities in U.S. cities, including New York, Washington DC, Los Angeles, Pittsburgh, Minneapolis and Miami areas.
Houston, Texas has 105 miles of HOV lanes. They move 96-228% more people per lane than general access lanes, and account for 5% of the travel by the workforce. HOV lanes can be used by buses, carpools, vanpools and motorcycles. On weekday mornings, HOV lane traffic moves toward Downtown (inbound). On weekday afternoons and evenings, HOV lane traffic moves away from Downtown (outbound). On the Katy HOV lane, minimum occupancy increases to three persons from 6:45 a.m. to 8 a.m. and 5 p.m. to 6 p.m. weekdays; a minimum of three passengers per vehicle also is required on the Northwest HOV lane from 6:45 to 8 a.m. At other times, the minimum occupancy requirement is two. QuickRide, a pilot program started in January 1998, allows carpools with two people per vehicle to use the Katy HOV during weekday peak periods for a fee. QuickRide commuters are tracked and billed using a transponder attached to their windshields.
A legislative study of HOV facilities in California found that they carry an average of 2,518 passengers per hour during peak hours – substantially more people than a congested mixed-flow lane and roughly the same number of people as a typical mixed-flow lane operating at maximum capacity. This only represents two-thirds of their capacity. Regional data indicate that HOV lanes induce mode shift to carpooling.
Eric Taub, The New York Times, September 14, 2000
(www.fta.dot.gov/brt/projects/losangeles.html)
Thanks to new technology plus common sense, 70,000 commuters a day can now often outpace the drivers on nearby clogged freeways by traveling on two routes served by red Metro Rapid buses, powered by natural gas. Los Angeles County transportation officials have managed to shave as much as 25% off the travel time of a local bus trip by adopting technology that, among things, can keep green lights on just a little longer as the bus approaches – as long as doing that does not cause another set of traffic problems.
The regional authority decided to take action because a survey showed that speed was the biggest complaint of bus passengers. In just a few years, average bus speeds had declined 17 percent, to just 10 miles per hour from a torrid 12. The Metropolitan Transportation Authority learned through its surveys that buses spent half their time standing still, either at red lights or at bus stops, waiting for passengers to get on and off. Officials had tried to speed things up a decade earlier by equipping buses with special transmitters that would hold traffic lights on green until buses passed through. But that just backed up the traffic on cross-streets, so the initiative was abandoned.
In 1997, traffic officials heard about a similar effort in Curitaba, Brazil, that was successful because the system was smarter in several ways. For one thing, it held the lights for buses only when that did not cause other traffic snarls. Still, there was no guarantee that the system would work in Los Angeles. Curitaba was built to handle public transportation, while public transit in Los Angeles often appears to be an afterthought. Even though one million people ride buses each day in the county, the bus is the transportation mode of last resort for most Angelenos.
On June 24, the transit authority began a system that gives express special buses priority at traffic signals. It first had to embed 210 antenna loops in the pavement at various spots along the route. As a bus passes over one of the loops, a $75 transmitter mounted on its front sends an identifying signal to an equipment box that controls the traffic light at the next intersection. The signal is also sent to a central control center downtown, so the bus can be tracked in the computer system.
But the $10 million project needed to find a way to ease the way for buses to clear intersections without tying up traffic on cross-streets. So the Los Angeles Department of Transportation wrote software that lets a green light be extended – held on green longer or switched to green earlier – for no more than 10 seconds. If several buses approach an intersection as the light is about the change, they can still get only 10 more seconds of green. Buses arriving later than that have to wait. And at important intersections, the green light can be extended in only every other cycle.
To prevent bus drivers from speeding up to make the system extend green lights, there are no visual indicators in the buses to tell drivers when some extra speed would accomplish that. The movement of each express bus is tracked in the authority's bus control center downtown, both on a computer screen (using the transmitter signals) and through information from video cameras placed at strategic intersections throughout the region.
As a bus passes over a pair of electronic loops embedded in the street, its speed is calculated. Then its arrival time is transmitted via a cell phone link to an electronic display at the next bus stop. Buses are dispatched every 3 to 10 minutes. And if a Metro Rapid bus finishes its route quicker than scheduled, that’s fine. That just makes for a more contented rider. To prevent Metro Rapid buses from bunching up into packs, the central dispatcher radios the driver to slow down or speed up (without breaking the speed limit) to keep from getting too close to another bus.
The project has been successful so far. On the 16-mile Ventura Boulevard route, from Warner Center to Universal City, the average travel time has decreased by 25 percent, to 45 minutes from 1 hour. On the 26-mile route from Santa Monica through Beverly Hills to Montebello on the east side of the city, travel times have also dropped by 25 percent, to 1 1/2 hours from 2 hours. Arrival times for Metro Rapid buses are coordinated with the area’s new Red Line subway extension so that even during rush hour, Mr. Gephart said, a trip across the San Fernando Valley into Union Station can now be done in about one hour, often faster than a car journey.
Will the improvements brought about by this new technology be enough to persuade the middle classes, and not just people without cars, to use public transportation? “That’s what we’re hoping for,” Mr. Gephart said. The authority hopes to add 15 to 20 new express lines, he said, and transit systems around the country are calling him to find out how they can adapt the Los Angeles system to speed up their bus services.
The report, Innovation Required: Moving More People With Less Traffic (KPC 2013) argues that spending $18 million to convert existing traffic lane into an optimized High Occupancy Toll (HOT) lane and improving public transit services is overall more cost effective and beneficial than spending $150 million to add new HOV lanes on Highway 101 north of San Francisco.
The Puget Sound region has more than 170 miles of HOV lanes on the region’s freeways. An additional 106 miles are in state and regional plans to complete the central Puget Sound Core HOV system, though funding currently is available only for some of the design work. Direct access ramps, which connect surface streets directly to an HOV lane, are being added to eliminate the need for HOVs to weave through traffic to reach the HOV lanes.
The Washington State Department of Transportation (WSDOT) has been monitoring freeway vehicle occupancy since October 1989. Vehicles are counted and classified by occupancy at 56 sites. When combined with traffic counts and transit ridership data, these observations provide a good picture of the ability of the region's freeway system to move people.
Table 6 shows the average peak hour traffic volumes, numbers of buses, Average Car Occupancy (ACO), and people moved per hour per lane for both non-HOV and HOV lanes at three sites on the freeway system. The traffic volumes in the non-HOV lanes are several times higher than in the HOV lanes because each facility has several non-HOV lanes and only one HOV lane. But each HOV lane can move more people per hour than each adjoining non-HOV lane. Average Car Occupancy (ACO) in non-HOV lanes ranges from 1.07 people per vehicle to 1.14 people per vehicle. The ACO for HOV lanes ranges from 2.09 people per vehicle to 2.76 people per vehicle, and most transit vehicles also use the HOV lanes. The chart clearly shows the people-moving ability of the HOV lanes.
The non-HOV traffic volume on I-5 at N. 145th (Seattle) decreased from 1990 to 1998 as many 2-occupant vehicles took advantage of the new HOV definition. The additional HOV volume more than made up the difference. In fact, there is no room for any further traffic on this part of the HOV system. Although the traffic in the HOV lane doubled, the number of people using the lane did not, because most of the additional traffic was cars with two occupants.
The traffic volumes in all lanes on I-5 at S. 216th (SeaTac) increased even with the addition of an HOV lane. The HOV lane could be carrying even more traffic, but it is congested by the incompleteness of the HOV system and by the general congestion of this part of I-5. The HOV lane on SR-520 at Yarrow Point continues to operate at an HOV definition of three or more persons per vehicle. Even at a relatively light volume (455vph), this lane carries about the same number of people as each of the adjoining general purpose lanes. There is room to add even more buses to this lane, which will increase the number of people carried by the lane.
This table probably understates true HOV lane ridership because vehicle occupants are difficult to observe. A more accurate count would probably indicate that the number of travelers per HOV lane-hour is higher than shown. A detailed annual report HOV Evaluation and Monitoring is available on the Internet at www.wsdot.wa.gov/eesc/atb/atb/HOV/Titlepg.html.
Table 6 Seattle Area Freeway Carrying Capacity
|
Year and Location |
Peak Hour |
Peak Hour |
Average Car |
Persons |
|
1990 |
|
|
|
|
|
I-5 @ N. 145 general purpose lanes |
7,648 |
4 |
1.12, 1.18 |
2,590 |
|
I-5 @ N. 145 HOV lanes (3+) |
985 |
35 |
2.76, 2.61 |
4,120 |
|
I-5 @ S. 216 general purpose lanes |
6,978 |
16 |
1.16, 1.24 |
2,246 |
|
SR-520, Yarrow Pt, AM westbound, General purpose lanes |
3,159 |
11 |
1.11 |
1,894 |
|
SR-520, Yarrow Pt, AM westbound, HOV lane (3+) |
142 |
27 |
2.60 |
980 |
|
1998 |
|
|
|
|
|
I-5 @ N. 145 general purpose lanes |
6,995 |
10 |
1.07, 1.14 |
2,378 |
|
I-5 @ N. 145 HOV lanes (2+) |
1,910 |
42 |
2.09, 2.16 |
5,889 |
|
I-5 @ S. 216 general purpose lanes |
7,551 |
10 |
1.08, 1.14 |
2,175 |
|
I-5 @ S. 216 HOV lanes (2+) |
1,312 |
27 |
2.13, 2.18 |
3,779 |
|
SR-520 @ Yarrow Pt. AM westbound, General purpose lanes |
3,500 |
5 |
1.11 |
2003 |
|
SR-520 @ Yarrow Pt. AM westbound, HOV lane (3+) |
455 |
34 |
2.42 |
1877 |
The introduction of bus priority measures in Auckland, New Zealand has led to more people using buses. Since 1988, bus patronage has grown 42 per cent on Dominion Road and 40 per cent on Mt Eden Road - two major bus priority corridors. In the two years since bus priorities were introduced on Sandringham Road, patronage has grown by 25 per cent. Auckland City is now introducing more green bus lanes throughout the city.
Jeffrey Ang-Olson and Anjali Mahendra (2011), Cost/Benefit Analysis of Converting a Lane for Bus Rapid Transit—Phase II Evaluation and Methodology, Research Results Digest 352, National Highway Research Program; at http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rrd_352.pdf.
Apogee (1994), Costs and Cost Effectiveness of Transportation Control Measures; A Review and Analysis of the Literature, National Association of Regional Councils (www.narc.org).
D. Bayliss (1986), Background Report for the European Conference of Ministers of Transport, OECD Joint Ministerial Session on Transport and the Environment (www.oecd.org).
Chun-Hung Peter Chen and George A. Naylor (2011), “Development of a Mode Choice Model for Bus Rapid Transit in Santa Clara County, California,” Journal of Public Transportation, Vol. 14, No. 3, 41-61; at www.nctr.usf.edu/wp-content/uploads/2011/10/JPT14.3.pdf.
Complete Streets (www.completestreets.org) is a campaign to promote roadway designs that effectively accommodate multiple modes and support local planning objectives.
Comsis Corporation (1993), Implementing Effective Travel Demand Management Measures: Inventory of Measures and Synthesis of Experience, USDOT and Institute of Transportation Engineers (www.ite.org); available at www.bts.gov/ntl/DOCS/474.html.
A.Scott Cothron, et al. (2005), Crash Analysis of Selected High-Occupancy Vehicle Facilities in Texas: Methodology,Findings,and Recommendations, Report 0-4434-1, Texas Transportation Institute (http://tti.tamu.edu).
John E. Evans and Richard H. Pratt (2005), Vanpools and Buspools; Traveler Response to Transportation System Changes, Chapter 5, TCRP Report 95, Transportation Research Board (www.trb.org); at http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c5.pdf.
Reid Ewing (1986), “TDM, Growth Management, and the Other Four Out of Five Trips,” Transportation Quarterly, Vol. 47, No. 3, pp. 343-366.
T. Fleming (Allatt), S. Turner and L. Tarjomi (2013), Reallocation of Road Space, Research Report 530, NZ Transport Agency (www.nzta.govt.nz); at www.nzta.govt.nz/resources/research/reports/530/docs/RR-530-Reallocation-of-road-space.pdf.
Ginger Goodin (2005), “Managed Lanes: The Future of Freeway Travel,” ITE Journal, Vol. 75, No. 2, Institute of Transportation Engineers (www.ite.org), February 2005, pp. 22-26.
Karen Hao (2018), The Humble Curb is Fast Becoming the City’s Hottest Asset, Quartz (https://qz.com); at https://qz.com/1182385/the-humble-curb-is-fast-becoming-the-citys-hottest-asset.
Michael Kiesling and Matthew Ridgway (2006), “Effective Bus-Only Lanes,” ITE Journal, Vol. 76, No. 7 (www.ite.org), July 2006, pp. 24-29.
KPC (2013), Innovation Required: Moving More People with Less Traffic. How to Improve Highway 101 in San Mateo County, Save Millions, and Give Commuters More Choices, TranForm (www.transformca.org); at www.transformca.org/sites/default/files/final_hot_101_paper.12.16.2013-1_revised_acknowledgement_0.pdf.
Jaimyoung Kwon and Pravin Varaiya (2008), “Effectiveness of California’s High Occupancy Vehicle (HOV) System,” Transportation Research C, Vol. 18, pp. 98-115.
Todd Litman (2015), When Are Bus Lanes Warranted? Accounting For Economic Efficiency, Social Equity, and Strategic Planning Goals, presented at Threadbo 14 Conference (www.thredbo-conference-series.org); at www.vtpi.org/blw.pdf.
LAO (2000), HOV Lanes in California: Are They Achieving Their Goals?, Legislative Analyst’s Office (www.lao.ca.gov/010700_hov/010700_hov_lanes.html).
Herbert Levinson, et al. (2003), Bus Rapid Transit: Vol. 1 - Case Studies and Vol. 2 - Implementation Guide, Transit Cooperative Research Program Report 90, Transportation Research Board (www.trb.org); available at http://gulliver.trb.org/publications/tcrp/tcrp_rpt_90v1.pdf.
Christopher Leman, Preston Schiller, Kristin Pauly (1994), Re-Thinking HOV-High Occupancy Vehicle Facilities and the Public Interest, Chesapeake Bay Foundation (www.fta.dot.gov/library/planning/RETK/retk.html).
Managed Lanes Initiative (http://ops.fhwa.dot.gov/freewaymgmt/managed_lanes/index.htm), sponsored by the U.S. Federal Highway Administration, provides information on various strategies for managing highway lanes to improve their performance.
David R. Martinelli (1996), “A Systematic Review of Busways,” Journal of Transportation Engineering, ASCE, Vol. 122, N0. 3, May/June 1996, pp. 192 - 199.
NACTO (2016), Transit Street Design Guide, National Association of City Transportation Officials (http://nacto.org); at http://nacto.org/transit-street-design-guide.
NYDOT (2009), New York City Street Design Manual, New York City Department of Transportation (www.nyc.gov/html/dot) at www.nyc.gov/html/dot/html/about/streetdesignmanual.shtml.
Jon Obenberger (2004), “Managed Lanes,” Public Roads, Federal Highway Administration (www.fhwa.dot.gov), Nov./Dec. 2004, pp. 48-55.
Kenneth Orski (2001), “Carpool Lanes - An Idea Whose Time Has Come and Gone,” TR News 214 (Special HOV Issue), Transportation Research Board (www.trb.org), May-June 2001, pp. 24-26.
Robert Poole and Kenneth Orski (2001), Hot Networks: A New Plan For Congestion Relief And Better Transit, Paper 305, Reason Foundation, (www.rppi.org/ps305.pdf).
Katherine Turnbull (2001), “Evolution of High-Occupancy Vehicle Facilities,” TR News 214 (Special HOV Issue), Transportation Research Board (www.trb.org), May-June 2001, pp. 6-11.
Katherine F. Turnbull, Herbert S. Levinson and Richard H. Pratt (2006), HOV Facilities – Traveler Response to Transportation System Changes, TCRB Report 95, Transportation Research Board (www.trb.org); available at http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_95c2.pdf.
Pravin Varaiya (2005), “What We’ve Learned about Highway Congestion,” ACCESS, Number 27 (www.uctc.net), Fall 2005, pp. 2-9.
Asha Weinstein Agrawal, Todd Goldman And Nancy Hannaford (2012), Shared-Use Bus Priority Lanes on City Streets: Case Studies in Design and Management, Mineta Transportation Institute (www.transweb.sjsu.edu); at www.transweb.sjsu.edu/project/2606.html.
Chris Wellander and Kathy Leotta (2001), “Gauging the Effectiveness of High-Occupancy Vehicle Lanes; Applying Three Criteria to Available Data Reveals Benefits, Viability,” TR News 214 (Special HOV Issue), Transportation Research Board (www.trb.org), May-June 2001, pp. 12-19.
WSDOT, High Occupant Vehicle Lanes, Washington State Department of Transportation (www.wsdot.wa.gov/hov).
Weihua Zhao (2019), “The General Equilibrium Effects of HOV Lanes on Congestion, Sprawl, Energy Use, and Carbon Emissions,” Journal of Regional Science, (https://doi.org/10.1111/jors.12434)
This Encyclopedia is produced by the Victoria Transport Policy Institute to help improve understanding of Transportation Demand Management. It is an ongoing project. Please send us your comments and suggestions for improvement.
Victoria Transport Policy Institute
www.vtpi.org info@vtpi.org
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