High-occupancy Vehicle Lanes Research Articles

LINK PERFORMANCE FUNCTIONS FOR HIGH OCCUPANCY VEHICLE LANES OF FREEWAYS

High Occupancy Vehicle (HOV) lanes are widely used on freeways and play an important role in network design and management. Likewise, link performance functions serve as an essential tool for transport system analysis. This paper aims to support network analysis by providing a tailored link performance function for HOV lanes contiguous with general motor lanes on freeways. Specifically, real traffic data is used for model calibration and evaluation that was assembled from the Performance Measurement System (PeMS) maintained by the California Department of Transportation. Three alternative models for link performance functions of HOV lanes on freeways are developed, which take traffic performance on both HOV lanes and adjacent sets of general motor lanes into consideration. To calibrate the parameters of the models, linear regression is made through stepwise and enter methods and nonlinear regression is carried out using sequential quadratic programming. Statistical analysis together with an evaluation using real traffic data is conducted to evaluate the validity of the proposed models. Our results show that all the three proposed models for contiguous HOV lanes on freeways are statistically significant and perform better in representing real traffic condition with regards to a traditional link performance function, with one specific nonlinear model best supported.

High-occupancy Vehicle Lanes and Tradable Credits Scheme for Traffic Congestion Management: A Bilevel Programming Approach

High-occupancy vehicle (HOV) lanes, which are designed so as to encourage more people to use high-capacity travel modes and thus move more people in a single roadway lane, have been implemented as a lane management measure to deal with the growing traffic congestion in practice. However, the implementation has shown that some HOV lanes are not able to achieve the expected effects without proper HOV lane settings. In this study, the tradable credits scheme (TCS) is introduced to improve the HOV lane management and an optimal capacity of HOV lanes in a multilane highway is investigated to match TCSs. To approach the investigation, a bilevel programming model is proposed. The upper-level represents the decision of the highway authority and the lower-level follows the commuters’ user equilibrium with deterministic demand. The potential influence of TCSs is further investigated within the proposed framework. A modified genetic algorithm is proposed to solve the bilevel programming model. Numerical examples demonstrate that combining TCSs with the HOV lane management can obviously mitigate traffic congestion.

Microscopic Simulation-Based High Occupancy Vehicle Lane Safety and Operation Assessment: A Case Study

This study proposes two general alternative designs to enhance the operation and safety of High Occupancy Vehicle (HOV) lanes at junctions with bus terminals or parking lots. A series of analysis tools, including microscopic simulation, video-based vehicle tracking technique, and Surrogate Safety Assessment Model (SSAM), are applied to model and test the safety and operational efficiency of an HOV road segment near a bus terminal in Québec as a case study. A metaheuristic optimization algorithm (i.e., Whale Optimization Algorithm) is employed to calibrate the microscopic model while deviation from the observed headway distribution is considered as a cost function. The results indicate that this type of HOV configurations exhibits significant safety problems (high number of crossing conflicts) and operational issues (high value of total delay) due to the terminal-bound buses that frequently need to travel across the main road. It is shown that the proposed alternative geometry design efficiently ameliorates the traffic conflicts issues. In addition, the alternative control design scheme significantly reduces the public transit delay. It is expected that this methodology can be applied to other reserved lane configurations similar to the investigated case study.

Quantifying the environmental impacts of increasing high occupancy vehicle lanes in the United States

To what extent will increasing High Occupancy Vehicle (HOV) lane-kilometer incentivize carpooling and reduce emissions of air pollutants and greenhouse gases? To answer these questions, we develop a multiple regression model relating HOV lanes and other socioeconomic factors to carpooling propensity in all 50 U.S. states and the District of Columbia, then calculate the extent to which increasing HOV lane-kilometers would lead to reductions in carbon dioxide equivalent (CO2e) and major air pollutants across the U.S., by state. Increasing HOV lane extent has the greatest potential to reduce annual CO2e in the District of Columbia, followed by Hawaii and New York. The smallest potential is found in states with the lowest population density, led by North Dakota. We then explore the extent to which recommendations made at one level of data aggregation (that of individual states) may be valid for another level, such as individual counties. The only state with sufficient data available to disaggregate the model to the county level is California, where we found a lower potential for state-wide CO2e emission reductions under the county-level model as compared to the state-level model (0.69% as compared to 1.08%, under the same hypothetical scenario), albeit with significant differences in emission reduction potential between counties with higher vs. lower population densities. This analysis demonstrates the potential to generate generalizable insight into the magnitude of vehicle emission reductions that might be achieved through expanding HOV lanes, and highlights the importance of data disaggregation in identifying the optimal locations for potential reductions.

Understanding the emission impacts of high-occupancy vehicle (HOV) to high-occupancy toll (HOT) lane conversions: Experience from Atlanta, Georgia

ABSTRACTConverting a congested high-occupancy vehicle (HOV) lane into a high-occupancy toll (HOT) lane is a viable option for improving travel time reliability for carpools and buses that use the managed lane. However, the emission impacts of HOV-to-HOT conversions are not well understood. The lack of emission impact quantification for HOT conversions creates a policy challenge for agencies making transportation funding choices. The goal of this paper is to evaluate the case study of before-and-after changes in vehicle emissions for the Atlanta, Georgia, I-85 HOV/HOT lane conversion project, implemented in October 2011. The analyses employed the Motor Vehicle Emission Simulator (MOVES) for project-level analysis with monitored changes in vehicle activity data collected by Georgia Tech researchers for the Georgia Department of Transportation (GDOT). During the quarterly field data collection from 2010 to 2012, more than 1.5 million license plates were observed and matched to vehicle class and age information using the vehicle registration database. The study also utilized the 20-sec, lane-specific traffic operations data from the Georgia NaviGAtor intelligent transportation system, as well as a direct feed of HOT lane usage data from the State Road and Tollway Authority (SRTA) managed lane system. As such, the analyses in this paper simultaneously assessed the impacts associated with changes in traffic volumes, on-road operating conditions, and fleet composition before and after the conversion. Both greenhouse gases and criteria pollutants were examined.Implications: A straight before-after analysis showed about 5% decrease in air pollutants and carbon dioxide (CO2). However, when the before-after calendar year of analysis was held constant (to account for the effect of 1 yr of fleet turnover), mass emissions at the analysis site during peak hours increased by as much as 17%, with little change in CO2. Further investigation revealed that a large percentage decrease in criteria pollutants in the straight before-after analysis was associated with a single calendar year change in MOVES. Hence, the Atlanta, Georgia, results suggest that an HOV-to-HOT conversion project may have increased mass emissions on the corridor. The results also showcase the importance of obtaining on-road data for emission impact assessment of HOV-to-HOT conversion projects.

How does the presence of HOV lanes affect plug-in electric vehicle adoption in California? A generalized propensity score approach

Policymakers have sought to spur consumer adoption of advanced clean vehicles by granting them single-occupancy access to high-occupancy vehicle (HOV) lanes. We offer the first evaluation of these policies that accommodates geographic variability in the magnitude of this policy's treatment effect. Focusing on the outcome of plug-in electric vehicle (PEV) adoption in California, we employ a generalized propensity score approach that allows for continuous, rather than binary, treatment effects. We estimate a state-wide dose-response curve to show that access to 6, 20, and 100 miles of nearby HOV lanes leads to 1, 3, and 10 additional PEV registrations in a census tract. The lower end of our 95% confidence interval implies that at least one quarter of California PEV registrations during 2010–2013 were a result of the HOV lane policy. We identify geographically-specific marginal policy effects that are smaller in Los Angeles, but relatively larger in San Diego and Sacramento.

Road Pricing in Theory and Practice: A Canadian Perspective

Like other developed countries, Canada experienced massive increases in road transportation since the end of the Second World War. At first, Canadian governments attempted to match the growing demand for road transportation by improving the quality and capacity of roads and highways - significantly increasing the extent of paved roadways and introducing a national highway system supported by federal shared-cost funding. Since the 1970s, however, Canadian governments have been less willing to invest in roads and highways, as growing environmental concerns lessened public enthusiasm for automobiles and urban expressways in particular. At the same time, government support for public transit decreased, resulting in recurring fare increases and reduced ridership per capita. As a result, road congestion has increased significantly in Canada, particularly in the largest urban areas, the Greater Golden Horseshoe area surrounding Toronto, and along the Trans-Canada highway from Quebec City to Windsor, Ontario. In order to finance improvements to road and transit infrastructure and address the growing problem of road congestion in Canada, the federal government has promised to share a portion of the federal gas tax with municipalities, and provincial governments have established urban transportation authorities, increased funding for public transit, and plan to introduce high occupancy vehicle (HOV) lanes as an incentive for people to carpool. Notably absent from these measures, however, are any concrete proposals to introduce more explicit road prices in the form of tolls and congestion-related charges. This paper hopes to contribute to Canadian public policy by making a case for increased reliance on explicit charges for the use of Canada's roads and highways. Part II considers road pricing in theory, considering the main arguments for and against road user charges as well as their optimal design. Part III reviews international experience with road pricing in order to derive lessons for the Canadian context. Part IV offers tentative conclusions.

Macroscopic and microscopic analyses of managed lanes on freeway facilities in South Florida

Abstract As congestion grows in metropolitan areas, agencies tend to utilize managed lanes on their freeway systems. Managed lanes have several forms and names, such as high-occupancy vehicle (HOV) lanes, high-occupancy toll (HOT) lanes, express lanes, and bus-only lanes. Although managed lanes have received significant attention as they increased the overall throughput and improved mobility without adding more lanes, little has been known about their operational capabilities. In addition, calibrating managed lane facilities can be challenging as they do not necessarily follow the same behavior with general purpose freeway lanes. This paper presents an operational analysis of two HOT lane segments located in South Florida. The sites are one-lane and two-lane segments separated by flexible pylons (FPs). The paper includes a macroscopic capacity analysis, and a microscopic calibration of the two sites using VISSIM microsimulation. The research findings assist in determining the capacity and speed-flow relationship of these segments, and also provide guidance for microsimulation model calibration for practitioners. The results of the study indicate that the percent drop in capacity for the one-lane FP site is 7.6% while the flow did not substantially change after the breakdown in the two-lane FP site. The research findings also include guidelines for simulating the breakdown events and calibrating one-lane and two-lane managed lane facilities in VISSIM microsimulation software. The Wiedemann car-following parameters (CC0 = 3.9 ft, CC1 = 1.9 s, CC2 = 26.25 ft, CC4 = −0.35, and CC5 = 0.35) provided the best fit for the one-lane FP site, while the combination (CC0 = 4.92 ft, CC1 = 1.9 s, CC2 = 39.37 ft, CC4 = −0.7, and CC5 = 0.7) parameters is recommended for the two-lane FP site.

Capacity and safety analysis of hard-shoulder running (HSR). A motorway case study

Operational motorway conditions can be improved by introducing traffic flow management and control systems, such as ramp metering (RM), high occupancy vehicle (HOV) lanes, real-time variable speed limits (VSLs), reversible lanes (RL), automated highway systems (AHS) and hard-shoulder running (HSR). The effects of such devices need to be examined in terms of capacity and safety. This paper examines the case study of the Italian motorway A22, which is supposed to be equipped with an HSR system implemented along 128km in order to reduce congestion with consequent improvement in levels of service (LOS). We studied the traffic processes (capacity, flow distribution between lanes, reliability, etc.) and estimated the expected capacity and safety conditions. These latter were studied with the method provided by the Highway Safety Manual (HSM), as well as by undertaking sensitivity analyses to quantify the expected changes in crash frequency at varying HSR activation hours (from 30 to 200h) in a year. It has been observed that HSR activation does not involve significant variations in the general safety conditions in the presence of a considerable capacity increase up to 35%. Moreover, have been identified the cases which require speed limit implementation (with VSLs system) in function of the values of reliability ϕ and velocity process V‾, and also suggested a speed limit sign system.

A pickup and delivery problem for ridesharing considering congestion

Traffic congestion is a significant social concern that is credited with considerable economic costs, wasted time, and associated public health risks. Efficient ridesharing solutions could help mitigate congestion. Some of the actions that government agencies have taken to encourage ridesharing include the availability of high occupancy vehicle (HOV) lanes and existing policies of discounted toll rates on HOVs. These measures encourage ridesharing by reducing costs or travel times of such trips. To study how the optimal routes change as a function of incentives for ridesharing, we modified existing pickup and delivery problems with time windows to consider changes in passenger travel time and toll cost due to vehicle load. Our computational results explore how the total route cost and time are affected by the use of HOV lanes and toll savings. In addition, our results show that it can be beneficial from a time and cost perspective to take detours to pick up additional passengers and use HOV lanes when the time saving on HOV lanes is significant.

Passenger Compartment Violation Detection in HOV/HOT Lanes

Due to the high volume of traffic on modern roadways, transportation agencies have proposed high occupancy vehicle (HOV) and high occupancy tolling (HOT) lanes to promote carpooling. Enforcement of the rules of these lanes is currently performed by roadside enforcement officers using visual observation. Officer-based enforcement is, however, known to be inefficient, costly, potentially dangerous, and ultimately ineffective. Violation rates up to 50%–80% have been reported, whereas manual enforcement rates of less than 10% are typical. Near-infrared (NIR) camera systems have been recently proposed to monitor HOV/HOT lanes and enforce the regulations. These camera systems bring an opportunity to automatically determine vehicle occupancy from captured HOV/HOT NIR images. Due to their ability to see through windshields of vehicles, these cameras also enable enforcement of other passenger compartment violations such as seatbelt violation and driver cell phone usage, in addition to determining vehicle occupancy. In this paper, we propose computer vision methods for detecting vehicle occupancy, seatbelt violation, and driver cell phone usage from NIR images captured from HOV/HOT lanes. Our methods consist of two stages. First, we localize the vehicle's front windshield and side window from captured HOV/HOT images using the deformable part model (DPM). Next, we define a region of interest in the localized images for each violation type and perform image classification using one of the local aggregation-based image features, i.e., bag-of-visual-words (BOW), vector of locally aggregated descriptors (VLAD), and Fisher vectors (FV), and compare their performances for each case. We also compare the performance of DPM-based detection with the image classification methods for vehicle occupancy and seatbelt violation detection. A data set over 4000 images including front/side view vehicle images with seatbelt and cell phone violations was collected on a public roadway and is used to perform the experiments.

Plug-in electric vehicle readiness: Rating cities in the United States

In order to accelerate the adoption of plug-in electric vehicles (PEV), many municipalities, along with their parent states, offer a variety of benefits to owners and operators of PEVs to make PEV adoption easier and more affordable. Example benefits include financial incentives, infrastructure perks, such as access to high occupancy vehicle (HOV) lanes, and streamlined processes for installing charging equipment. Additionally, some cities are making investments in PEVs and PEV infrastructure for both municipal and public use. However, the policies of states and cities are by no means uniform, and some jurisdictions are doing more than others to promote PEVs.This study presents an index that identifies and ranks the “readiness” of 36 major U.S. cities to deploy electric vehicles. Readiness is the degree to which adoption of electric vehicles is supported, as reflected in the presence of various types of policy instruments, infrastructure development, municipal investments in PEV technology, and participation in relevant stakeholder coalitions. The study also compares cities within states that participate in the Zero Emission Vehicle program, with those that do not, with the objective to understand whether participation in that program has a meaningful impact on PEV readiness.

Sustainable Highway Operations: High Occupancy Lane and Movable Lane

Two managed lane schemes, the high occupancy vehicle lane (HOV) and the movable lane operations, were analyzed to determine their suitability as a sustainable highway operation. VISSIM, a microscopic traffic simulation program, was used for this study, and parameters representing driver behavior in the car following model were calibrated according to a macroscopic speed and flow relationship based on measured data. The analysis results showed that bus travel speed was improved in the HOV operation, while movable lane operation also considerably improved car travel speed.

Operational Assessment of Speed Priority for High-Occupancy Vehicle Lanes over General-Purpose Lanes

Current guidelines arguably do not properly address how much priority high-occupancy vehicle (HOV) lanes should be over general-purpose (GP) lanes. In response to this issue, this study developed a scheme to measure HOV speed priority via mathematical derivation. The concept of vehicle occupancy was incorporated to reflect the HOV core value－carrying more persons in fewer vehicles. As traffic increases, the scheme leads to HOV lanes' speed increasingly greater than GP lanes’. Contrasts were made between the proposed scheme and the conventional travel time saving principle. Two case studies were implemented; the local one indicates that Taiwan’s first HOV lane was under-prioritized while the foreign one shows that the HOV lane of SR-60 in California was well-prioritized. The results can be used to further assess the necessity of HOV policy adjustment.

Aceptabilidad de la implementación de carriles vehiculares de alta ocupación en la Autopista Norte de Bogotá

This paper examines the acceptability of the implementation of a High Occupancy Vehicle (HOV) lane in the north of Bogota (Colombia), a strategy that is compatible with the policies of the mobility master plan of the city. Although the idea of using HOV lanes dates back to the 70's, it is still a valid alternative which is amply documented that produces positive impacts on travel times, accident rates, greenhouse emissions, among others. The study is based on discrete choice survey experiments which allowed calibrating a multinomial logit model. The calibrated model indicated that the acceptability of the HOV lane is very sensitive to travel times experienced by current car users. The model also identified the segment of the population with the highest acceptability for the proposal, which would consist of women over 31 years old, who travel for purposes related to work

Speed-spacing dependency on relative speed from the adjacent lane: New insights for car following models

This paper examines the traffic dynamics underlying a recently observed phenomenon, the so called “sympathy of speeds” whereby a high occupancy vehicle (HOV) lane seemingly exhibits lower vehicular capacity and lower flow at speeds throughout the congested regime compared to the adjacent general purpose (GP) lanes. Unlike previous studies this paper examines a time-of-day HOV lane. During the non-HOV periods the study lane reverts to a GP lane, thereby providing a control condition for the specific lane and location. This work uses the single vehicle passage (svp) method to group vehicle passages before measuring the traffic state and extends the svp to bin vehicles in the study lane based on the relative speed to the adjacent lane. The extended svp method allows the work to also study the impacts during the non-HOV periods when the study lane serves GP vehicles. This work finds that: (1) during the non-HOV periods the study lane exhibited behavior indistinguishable from the adjacent GP lane. (2) The sympathy of speeds persists throughout the day, even when the study lane serves GP vehicles. (3) The relative speed to the adjacent lane provided a better predictor of behavior than whether or not the HOV restriction is active. In short, the car following behavior that gives rise to the sympathy of speeds is unrelated to the HOV restriction per se, persisting under GP operations as well.This dependency on the relative speed in the adjacent lane is an important finding given the fact that most existing car following models assume that the longitudinal acceleration of a following vehicle is strictly a function of the relationship to the leading vehicle in the same lane. Because drivers in general adopt a larger spacing when faced with a high differential in speed between lanes means that car following behavior also depends on the relative speed to the adjacent lane. This fact has likely gone unnoticed to date because generally the conditions that give rise to a differential in speeds between lanes are usually short lived, and thus, do not become apparent in conventional macroscopic data except under exceptional circumstances that include confounding factors like HOV operations.

A New Model for a Carpool Matching Service.

Carpooling is an effective means of reducing traffic. A carpool team shares a vehicle for their commute, which reduces the number of vehicles on the road during rush hour periods. Carpooling is officially sanctioned by most governments, and is supported by the construction of high-occupancy vehicle lanes. A number of carpooling services have been designed in order to match commuters into carpool teams, but it known that the determination of optimal carpool teams is a combinatorially complex problem, and therefore technological solutions are difficult to achieve. In this paper, a model for carpool matching services is proposed, and both optimal and heuristic approaches are tested to find solutions for that model. The results show that different solution approaches are preferred over different ranges of problem instances. Most importantly, it is demonstrated that a new formulation and associated solution procedures can permit the determination of optimal carpool teams and routes. An instantiation of the model is presented (using the street network of Guangzhou city, China) to demonstrate how carpool teams can be determined.

Optimal Deployment of Managed Lanes in General Networks

Falling budget, political, and environmental constraints force decision makers and transportation authorities to develop innovative ways to better manage existing facilities. Managed lanes, more specifically, high-occupancy vehicle (HOV) and high-occupancy toll (HOT) lanes, have been recognized as viable options to improve vehicle trips without constructing additional capacity. This paper investigates how to deploy managed lanes in general networks. A mathematical program with complementarity constraints is formulated to simultaneously determine the locations of managed lanes and the toll rates on HOT lanes to maximize the social benefit. Numerical examples based on the networks in the literature are presented to verify the model.

Different Types of High-Occupancy Vehicle Access Control

High-occupancy vehicle (HOV) facilities have been widely implemented in the United States as a way to improve mobility, trip time reliability, and air quality of freeway systems. In California there are two types of HOV facilities, namely, limited access and continuous access with part-time or full-time operation. This paper presents a framework for comparing the mobility performance of the types of HOV facilities on the basis of regression analyses using a California data set as a case study. Parametric regression models were developed to explain empirical freeway capacity as a function of a set of explanatory variables including the type of HOV access. Modeling results consistently indicated that freeway segments with limited-access HOV lanes would have had higher overall capacities than those of continuous-access HOV facilities, everything else being equal. In addition, the proposed framework can be applied well to the analyses on other types of managed lanes.

A BI-LEVEL FRAMEWORK FOR PRICING OF HIGH-OCCUPANCY TOLL LANES

As a freeway operational management strategy, High-Occupancy Toll (HOT) lanes have been deployed to manage the demand for High-Occupancy Vehicle (HOV) lanes by adjusting the tolls. By doing so, the capacity of freeways with such lanes can be used more efficiently. Periodically, setting the right amount of toll in accordance with the time-varying demand is a key to successful operation of HOT lanes; however, this is often difficult because travellers have heterogeneous willingness to pay for the toll and traffic conditions vary as the demand changes due to the imposition of tolls. This paper proposed an algorithm to determine the optimal level of toll for minimizing the total delay collectively spent by both HOVs and low-occupancy vehicles. Based on real-world traffic and survey data obtained from Gyungbu expressway in South Korea, a case study is presented to verify the applicability of the developed algorithm. The results from the case study show that the proactive dynamic pricing scheme can use the underutilized capacity of HOT lane efficiently and, thereby, shorten total travel time by 22% and generate revenue of more than $8600. Some limitations and future research agendas are also discussed.