High-occupancy Vehicle Research Articles

Optimal merging into a high-speed lane dedicated to connected autonomous vehicles

In the future, High Occupancy Vehicle (HOV) lanes or other dedicated lanes might be restricted to autonomous vehicles, e.g wirelessly connected vehicles with longitudinal motion control. These vehicles would likely travel at high speeds in platoons. New criteria for the merging of a vehicle from an adjacent freeway are proposed. To reduce disruption to the flow, only merges into gaps between platoons, not within, are considered. To minimize HOV lane trip time and vehicle deceleration, the optimal merge position is determined from simulations of linear combinations of the deviation of the headway from equilibrium and vehicle velocity differences. These are between the merging vehicle and the trailing vehicle (on the HOV lane) and the merging vehicle and the last vehicle of the preceding platoon. The merging vehicle, due to acceleration limitations on the freeway, generally will merge at a significantly lower velocity than the HOV lane average velocity.

The Impact of High-Occupancy Vehicle Lanes on Commuters: Field Evidence

Governments are actively investing to alleviate traffic congestion. Starting from the 1970s, a common policy has been to introduce high-occupancy vehicle (HOV) lanes, that is, traffic lanes exclusively reserved for vehicles with more than one occupant. Following the introduction of HOV lanes in several countries, their effectiveness has been the topic of heated debates. In this paper, we have a unique opportunity to empirically examine the impact of introducing HOV lanes on carpooling. In October 2019, the Israeli government has decided to introduce three HOV lanes. In this context, we have access to traffic and carpool data — from Waze (the free GPS navigation app owned by Google) — both before and after introducing the HOV lanes. We can thus rigorously quantify the impact of introducing an HOV lane on carpool intent and adoption. We also study refined questions around the effectiveness of different types of HOV lanes (2+ versus 3+), the impact at different times of the day, and the behavioral effect on commuters (e.g., strategically adapting commute times). Our study shows that the introduction of the HOV lanes led to a median time saving during rush hours of 5.7-15.7 minutes and increased the carpool rates by hundreds of percent for some routes. Interestingly, we find that the new HOV lanes have a global impact as they also raised the carpool rates for routes unaffected by the HOV lanes. This effect can be explained by the increased awareness of the public about the opportunity of carpooling.

Human factors evaluation of an in-vehicle active traffic and demand management (ATDM) system

This research study focused on the evaluation of an emulated in-vehicle Active Traffic and Demand Management (ATDM) system on Interstate 66 in Northern Virginia. Traditional ATDM systems rely on infrastructure-mounted variable message signs (VMS) to provide information (speed limits, lane availability, etc.) to the traveling public. By providing information about dynamic roadway conditions on an in-vehicle device, the ATDM may improve driving safety and performance by allowing drivers to remain consistently aware of forthcoming traffic conditions and roadway requirements; even when external signage is inaccessible. This study represents an initial investigation of an emulated in-vehicle ATDM to provide developers with design guidance and ensure that unintended consequences, such as distraction, do not undermine the potential benefits.Twenty younger and 20 older participants, accompanied by a member of the research team, experienced the following ATDM features on an in-vehicle device (IVD) mounted to the dashboard: (1) dynamic speed limits, (2) dynamic lane use/shoulder control, (3) High Occupancy Vehicle (HOV) restrictions, and (4) roadway information from variable message signs. The IVD was equipped with auditory and visual alerts notifying the driver when relevant visual information was updated. Research questions addressed distraction and driver behavior associated with use of the system. Qualitative and quantitative participant data was acquired from the instrumented vehicle, various questionnaires, and researcher observation.Several key findings were uncovered: (1) The IVD, as tested, did not warrant classification as a source of distraction according to the NHTSA guidelines; v2) There was a significant difference in eye-glance durations to the IVD when comparing the VMS alerts to both the speed limit and lane management alerts; and (3) The speed limit alert motivated participants to alter their speed (per survey results and participant speed data).

A comprehensive welfare impact analysis for road expansion projects: A case study

This study provides the overall social welfare implications of key road-capacity expansion options considering free capacity, high occupancy vehicle – HOV, high occupancy toll – HOT, and toll lanes. The broad welfare impacts are estimated in terms of transport users, residents, the regional economy, and private-sector’s welfare. The study uses Dallas County and Tarrant County, Texas, as a case-study region. The study result shows that the HOT option outperforms all other options. It results in an overall increase in social welfare in net present value of $6.7 billion. Apart from that, estimation results do not clearly suggest a preferred option, but instead, depend on the criterion used. The best option in each criterion is: “Do nothing” for investment costs, “HOT” for regional economic impact, “All-tolled” for corridor travel time, “HOT” for network-wide travel time, “Free capacity” for users’ travel costs, “All-tolled” for energy and environmental costs, and “All-tolled” for revenue. The proposed social welfare analysis integrates these conflicting criteria by offering a unified index, and provides the best road-investment option for society.

Dynamic carpool in morning commute: Role of high-occupancy-vehicle (HOV) and high-occupancy-toll (HOT) lanes

This study analyzes carpool in morning commute, using a bottleneck model that allocates a fraction of the bottleneck capacity to a high-occupancy-vehicle (HOV) or a high-occupancy-toll (HOT) lane. Commuters are homogeneous cost minimizers who participate carpool through a platform, either as solo driver, carpool driver or carpool rider. At user equilibrium (UE), no commuter can unilaterally lower her cost by switching to a different departure time, carpool role or road facility. Because a rider can use the in-vehicle time more productively than her driver, she enjoys a cost benefit that grows with the journey time. Therefore, the driver must be compensated more when travel delay due to congestion is longer. This requirement is fulfilled through a time-dependent carpool ratio that determines how much a driver is paid. We characterize and numerically obtain the UE solutions for this dynamic carpool problem. Results of numerical experiments show that the HOV lane promotes carpool and boosts welfare. The larger capacity the HOV lane is allocated, the greater benefit it offers to the system. In addition, an HOT lane can bring additional welfare gains with a modest level of toll.

Toll-managed lanes: A simplified benefit-cost analysis of seven US projects

Toll managed lanes are expressway lanes where tolls are used—often in combination with preferred access for high occupancy vehicles and other special traffic management techniques—to improve the highway's capacity, speed or reliability. Such lanes have become popular with transportation policymakers as a way of maintaining free-flowing traffic on certain sections of the highway while also, in some cases, financing the construction of new lanes in congested urban areas. This study examines whether toll-managed lanes are as beneficial as they are popular. The heart of the analysis is the application of a simplified social benefit-cost analysis (BCA) to seven projects. In brief, our results paint a complicated picture of toll-managed lane efficacy. Only two of the seven projects have benefit-cost (B/C) ratios above 1.0 using our base case assumptions about the value of travel time saved and the discount rate, although three others approach or exceed 1.0 with more optimistic but plausible assumptions. The most successful generate not only a significant savings of around 4–5 min per trip for motorists who switch to the managed lane but also smaller per-trip savings for the large majority of motorists who continue to use the general-purpose lanes. It is important to acknowledge, however, that these calculations depend upon some uncertain assumptions about the value of travel time savings and improved reliability.

Investigating the Effects of Pavement Roughness on Freeway Safety using Data from Five States

Traffic crashes occur usually because of a combination of human, roadway/environment, and vehicle factors. Pavement condition is closely related to these three factors as it is one of the most important roadway/environment factors and it affects driving behavior and vehicle performance at the same time. Previous studies have shown that pavement condition plays an important role in safety. This study develops four different safety performance functions to evaluate the effect of pavement roughness, measured by the International Roughness Index (IRI), on the number of crashes using the interstate highway data from five U.S. states representing different geographical and weather regions: Arizona, Colorado, Florida, Maryland, and Michigan. The modeling results identify many significant variables including traffic volume and proportion of trucks, through lane count, shoulder type, median width, high-occupancy vehicle (HOV) lane operation and HOV lane count, speed limit, area type along with IRI-related factors. The results indicate that increased IRI (deterioration of pavement quality) contributes to large numbers of total crashes. On interstate highways with speed limits of 70 mph and higher, the effects of IRI are relatively smaller. On the other hand, the effects of IRI increase with a larger traffic volume. Based on the modeling results, seven crash modification functions of IRI values by crash type and speed limit were estimated. The findings from this study are expected to be useful for both pavement and safety engineers to understand the relationship between IRI and safety on freeways.

Parking Behavior: Park ‘n’ Ride (PnR) to encourage multimodalism in Brisbane

‘Park ‘n’ Ride’ facilities (PnR) initially emerged to accommodate motorists that would otherwise exhaust the local supply of parking around train stations and other rapid high occupancy vehicle nodes but increasing became a planning strategy to provide commuters from auto-dependent suburbs with access to rapid high occupancy vehicle to reduce their environmental impacts and inner-city road and parking capacity requirements. Theoretically, PnR should influence modal choice by making the transfer between car and rapid transit more convenient yet this base assumption rarely matches the empirical reality. Our synthesis of the PnR literature suggests that motorists deciding whether to park-and-ride have considerations beyond minimising their travel duration and expenses, and we develop a new integrative model of PnR, multi-modalism, and modal choice to illustrate how reliability and competing transport planning strategies such as inter-city mobility, transit-oriented development, and active transport interact and inform modal choice. Upon laying these theoretical foundations, we empirically examine the extent to which developing or modifying PnR influences modal choice in our case study context, Brisbane, Australia. Our research findings suggest that it is new rather than modified PnR that influence modal choice and that new park and riders are typically drawn from nearby locations rather than peripheral and therefore auto-dependent areas. This influence is particularly evident in suburbs closer to the inner city, and is problematic given that these are not the intended users of PnR. Our synthesis and examination of multi-modalism and modal choice has important implications for researchers, planners, and policy makers attempting to influence modal choice and improve the efficiency of urban mobility.

Practical guidance for using mesoscopic simulation tools

Mesoscopic simulation has many advantages such as requiring less effort for network building and calibration than microscopic simulation and generating more detailed simulation results in terms of traffic conditions than macroscopic simulation. As more and more transportation practitioners become interested in it, this paper aims at providing practical guidance by demonstrating the capabilities of mesoscopic simulation tools. In order to provide practical guidance, two commercially available mesoscopic simulation software, AIMSUN and VISSIM were chosen and a testbed network consisting of a system of freeways in Richmond, Virginia was prepared. The testbed was calibrated and used to evaluate the potential impacts of various levels of High Occupancy Vehicle (HOV) lane usage on system operations. The goal of the HOV lane implementation was to demonstrate practical guidance of utilizing mesoscopic simulation package as a tool for evaluating traffic management strategies. Results of the demonstration study, using both AIMSUN and VISSIM, were deemed to be reasonable. Some lessons learned during the study as well as through communications with the software vendors are also shared in the paper. This paper should provide transportation practitioners with practical guidance when selecting and/or conducting mesoscopic simulation.

Leveraging existing high-occupancy vehicle lanes for mixed-autonomy traffic management with emerging connected automated vehicle applications

Transportation agencies have started including phased deployment of connected and automated vehicle (CAV) technologies in their transportation plans and programs. While theoretical analyses have indicated significant benefits of CAVs for improving system performance, deploying these technologies at existing or adapted highway facilities concerns more than technological issues. This study introduces the concepts and operational strategies of using managed lanes, High-Occupancy Vehicle (HOV) lanes in particular, for mixed-autonomy traffic management. The study enhances existing and develops new algorithms for three selected freeway CAV applications as a CAV technology integration, including speed harmonization, cooperative adaptive cruise control (CACC), and cooperative merge. Instead of evaluation on a synthetic segment, this study reports a large-scale simulation-based real-world case study to investigate CAV early deployment opportunities on Interstate 66 outside the Beltway. The simulation results show that, for all scenarios, individual and bundled CAV applications can significantly improve traffic performance in terms of delay and throughput. CACC platooning is the most effective individual strategy to improve traffic performance. The bundled CAV applications can benefit the system, even with low CAV market penetration, and fully handle more than 130 percent of the existing demand with high CAV market penetration rates. Additionally, left-side dedicated ramps and shared managed lane operational strategies are also beneficial, even during early deployment stages.

Traffic Flow Impacts of Converting an HOV Lane Into a Dedicated CACC Lane on a Freeway Corridor

Cooperative Adaptive Cruise Control (CACC) systems can increase roadway capacity, but the benefits are marginal at low market penetration rates (MPRs). Thus, a CACC dedicated lane is considered to group CACC vehicles for efficient traffic stream. Concepts of converting existing High Occupancy Vehicle (HOV) lanes into CACC lanes emerge, which leverages the infrastructural facilities and experience with HOV lanes. However, it is unclear to which extent changing HOV lanes to CACC lanes can influence freeway operations. This study examines the traffic flow impacts of converting HOV lanes into CACC lanes regarding CACC MPRs on a complex freeway corridor with multiple interacting bottlenecks in California. A simulation model capable of reproducing flow characteristics with HOV lane and CACC systems is employed for the assessment. Special attention is paid to macroscopic congestion patterns, CACC lane utilization, travel time reliability and CACC operation characteristics. The results show that converting to CACC lanes at low MPRs (130%) can exacerbate congestion in general purpose lanes, whereas at mediate CACC MPRs (40%-50%) the congestion is drastically alleviated due to a large share of traffic carried by CACC lanes.

High Occupancy Vehicle Lanes are an Expected Failure

High Occupancy Vehicle Lanes are an Expected Failure

An in-depth examination of electric vehicle incentives: Consumer heterogeneity and changing response over time

Abstract We investigate the impacts of a combination of incentives on the purchase decision of electric vehicle buyers in California from 2010 through 2017. We employ a comprehensive survey on over 14,000 purchasers of electric vehicles in the state of California. The survey covers a swath of purchase intentions, general demographics, and importance of various incentives. Our results indicate that the most important incentives for plug-in electric vehicle (PEV) owners are the federal tax credit, the California state rebate, and high occupancy vehicle (HOV) lane access. In addition, the importance of the incentives and their associated effect on purchase behavior has been changing over time: respondents are less likely to not change their decision and more likely to not buy a vehicle at all as time passes and the technology moves away from early adopters. Incentives are becoming more important for vehicle adopters as PEV market entry progresses.

Analysis of the Feasibility of Hov Lane of Shichang Avenue in Weihai City

Based on the experience of international traffic demand management policies, the Hov(high occupancy vehicle)has been introduced to the research on urban traffic planning and design. Through the collection and analysis of international experience in the design and operation of Hov lane, the requirement for Hov setting has been analyzed in China and the evaluation indexes of Hov lane have been proposed. By building the Hov design platform, this paper provides the methodology for the design and evaluation of Hov lane program. Through the research of this paper, we provide some scientific basis for the decision-makers and give some theoretical guidance for the Hov project in future.

Incentivizing Commuters to Carpool: A Large Field Experiment with Waze

Traffic congestion is a serious global issue. A potential solution, which requires zero investment in infrastructure, is to convince solo car users to carpool. In this paper, we leverage the Waze Carpool service and run the largest ever digital field experiment to nudge commuters to carpool. Our field experiment involves more than half a million users across four U.S. states between June 10 and July 3, 2019. We identify users who can save a significant commute time by carpooling through the use of a high-occupancy vehicle (HOV) lane, users who can still use a HOV lane but have a low time saving, and users who do not have access to a HOV lane on their commute. We send them in-app notifications with different framings: mentioning the HOV lane, highlighting the time saving, emphasizing the monetary welcome bonus (for users who do not have access to a HOV lane), and a generic carpool invitation. We find a strong relationship between the affinity to carpool and the potential time saving through a HOV lane. Specifically, we estimate that mentioning the HOV lane increases the click-through rate (i.e., proportion of users who clicked on the button inviting them to try the carpool service) and the on-boarding rate (i.e., proportion of users who signed up and created an account with the carpool service) by 133-185% and 64-141%, respectively relative to a generic invitation. We conclude by discussing the implications of our findings for carpool platforms and public policy.

Application of parallel tabu search in solving Ride-sharing problem with HOV Lanes

Ride-sharing can be defined as a system where travelers can share their vehicles and travel cost with others who have a similar destination and time schedule. Ride-sharing problem with High Occupancy Vehicle (HOV) Lanes is a problem of finding an optimal route to serve costumer demand where each demand and vehicle consists of origin and destination point, and some of the route are restricted-use freeways lanes reserved for vehicles with more than a predetermined number of occupants, which called HOV lanes. With the use of ride-sharing and HOV Lanes, it is expected to reduce the number of the vehicles thus will mitigate the congestion. The optimal solution is the one with minimum number of total distance, passenger’s ride time, and cost. This study discusses the application of insertion heuristic and parallel tabu search to optimize the use of Ride-sharing with HOV Lanes. Insertion heuristic is applied to obtain an initial solution and parallel tabu search algorithm is applied to improve the initial solution and obtain a better solution. For the case of eight vehicles and eight requests, from insertion heuristic we obtained an initial solution with an objective function value of 425 and with the used of parallel tabu search method we obtained a better solution with an objective function value of 420.

Are HOT Frauds Laughing at You?

High-occupancy vehicle and toll (HOV and HOT) lanes are designed to reward passenger-carrying drivers with faster journey times and discounts. But cheating is rife. Paul Willis looks at the enforcement solutions authorities can use to fight back, from manual checks to automated cameras and the latest in smartphone-based systems

Why Do They Ride with Others? Meta-Analysis of Factors Influencing Travelers to Carpool

Carpooling can be viewed as a simple intervention to reduce congestion, environmental problems, and land use for parking spaces. The present study assembled 18 studies on carpooling from all over the world that were published during the last five years (2014–2018) for a meta-analysis. By calculating effect sizes of 20 different factors, the study aimed to understand user characteristics, motives, and barriers to carpooling, and to gain insights about carpool interventions. Our results indicate that carpooling is very weakly related to socio-demographic variables, and that psychological factors are becoming more important, including monetary and time benefits, reducing congestion, and environmental concerns. Policy-makers can increase carpooling by offering cheaper parking or special parking spaces for carpoolers and introducing high-occupancy vehicle (HOV) lanes. Not surprisingly, fuel prices influence mode choice. The overall findings support previous results, but we found judgmental factors becoming more important for the choice to carpool. We conclude that carpooling services still fail to include many potential users and to serve users adequately. The challenge of meeting the needs of all users requires new approaches to designing carpool concepts, systems, and encounters.

Optimal capacity allocation for high occupancy vehicle (HOV) lane in morning commute

In this paper, we analyze the optimal capacity allocation for high occupancy vehicle (HOV) lane in morning commute, using the classical bottleneck model to a single corridor. The vehicular traffics are divided as high occupancy vehicle (HOV) and low occupancy vehicle (LOV) based on the number of in-vehicle travelers. The whole corridor is allocated as general purpose (GP) lane and HOV lane, separately with a bottleneck at the end of each lane. The optimal capacity of HOV lane for minimizing the system’s total cost is analytically derived. It is found that with optimal capacity of HOV lane, each HOV traveler experiences lower cost than each LOV traveler. Numerical examples are presented to verify all analytical results.

High-occupancy vehicle lanes on the right: an alternative design for congestion reduction at freeway merge, diverge, and weaving areas

ABSTRACTHigh-occupancy vehicle (HOV) lanes have been widely deployed in freeways with high demands and traffic congestion. This paper discusses how an alternative design with the HOV lane on the right side of the freeway could effectively mitigate congestion problems at freeway merge, diverge, and weaving areas as compared with the benchmark design of HOV lanes on the left. Simulation experiments show that the alternative design will result in a reduction in average delay by 5% to 10% and increase in throughput by 10% to 30% for all traffic. While the alternative design generally improves performance for the general purpose (GP) lanes, it will degrade HOV lane performance. Nonetheless, HOV lane vehicles enjoy a higher level of service than GP lane vehicles under the same background settings. The study suggests that it is practical to implement the alternative design on freeways, especially for areas with low HOV traffic volumes.