Travel Patterns of Frequent and Non-Frequent Users on I-66 High-Occupancy Toll Lanes and Implications for the Value of Time Estimation
Mecit Cetin, Old Dominion UniversityShow Abstract
Shanjiang Zhu (email@example.com), George Mason University
Hong Yang, Old Dominion University
Olcay Sahin, Argonne National Laboratory
Based on a three-month toll-transaction dataset that includes an anonymized unique identifier for each vehicle, this paper presents an in-depth analysis of traffic volumes and tolls on the I-66 High-Occupancy Toll (HOT), i.e., express, lanes in Northern Virginia. The unique identifiers allow quantification of how frequently each vehicle travels through the corridor. Vehicles observed in selected time intervals are categorized into frequent and non-frequent groups based on the total number of trips made by each vehicle. For the morning commute, the analyses show that those traveling frequently on the HOT lanes are more sensitive to high tolls and typically travel earlier in the morning to avoid higher tolls. In other words, when tolls are relatively high (e.g., larger than $20), the fraction of frequent users in the traffic is much smaller as compared to that of non-frequent users (e.g., 25% versus 75%). To estimate how much toll the HOT-lane users are paying per unit of travel time saved, i.e., value of travel time saving (VTTS), speeds on alternative routes parallel to the I-66 corridor are computed from probe data and compared to those on I-66 express lanes. The distributions of VTTS are analyzed for both frequent and non-frequent users and the implications of the difference in these distributions for dynamic tolling are discussed in the paper.
Permitting Trucks in Transit-Only Lanes: Evaluation of a Pilot Test in Seattle
Seyma Gunes, University of WashingtonShow Abstract
Anne Goodchild, University of Washington
Chelsea Greene, University of Washington
Venu Nemani, Seattle Department of Transportation
With ongoing population growth and rapid development in cities, the demand for goods and services has seen a drastic increase. Consequently, transportation planners are searching for new ways to better manage the flow of traffic on existing facilities and more efficiently utilize available and unused capacity. In this research, a lane management strategy that allows freight vehicles to use bus-only lanes is empirically evaluated in an urban setting. This paper presents an analysis of data that was collected to evaluate the operational impacts of the implementation of a freight and transit (FAT) lane, and to guide the development of future FAT lane projects by learning from the case study in Seattle. The video data was converted to vehicle counts, which were analyzed to understand the traffic impacts and used to construct a discrete choice model. The analysis shows that transit buses used the FAT lane 96 percent of the time, and authorizing trucks to use the lane did not impact that lane choice. Trucks used the FAT lane but their utilization decreased with increasing numbers of buses in the FAT lane. Instead of higher rates of trucks, unauthorized vehicles, such as passenger cars and work vans, increasingly used the FAT lane during congestion. Due to their differing schedule patterns, trucks and buses used the FAT lane at complementary times and trucks showed relatively low volumes in the FAT lane. Overall, the results are promising for a lane management strategy that may improve freight system performance without reducing transit service quality.
Bi-level Optimization Algorithm for Dynamic Reversible Lane Control based on Short-term Traffic Flow Prediction
Chenxi Liu, University of WashingtonShow Abstract
Hao Yang, University of Washington
Hsiu-Yuan Chen, University of Washington
Yinhai Wang (firstname.lastname@example.org), University of Washington
Traffic congestion is a more and more serious problem in all over the world. Reversible lanes have been used throughout the world to mitigate the effects of congestion and optimize roadway performance for more than 80 years. They have been applied on a variety of roadway types using different control methods to address an assortment of needs. However, the limited traditional control methods can not meet the increasing various demands. To address the needs on freeway scenario, the study introduces a bi-level method based on short-term traffic flow prediction for the dynamic reversible lane control algorithm. The work improves the traditional traffic management method, reversible lane control, from static control to dynamic real-time traffic management. Taking advantage of the development of neural network technology, the input of the algorithm covers not only historical data and real-time data but also the predicted data. Advanced Bi-directional Long Short-term Memory (Abi-LSTM) model is employed for the short-term traffic flow prediction. For the control algorithm, the study introduces bi-level optimization method to maximize the total traffic flow in both directions which determine the lane deployment. Also, the study considers the user costs in the lower level optimization formula. Finally, the paper builds up a simulation to test the effect of the dynamic reversible lane control algorithm.
A Framework Considering Deep Uncertainty of CAV Impacts on Managed Lanes Using a New Dynamic Traffic Assignment Model
Jack Klodzinski (email@example.com), AECOMShow Abstract
Barbara Davis, Florida Department of Transportation
Lihe Wang, AECOM Technology Corp
Genoveva Fruet, AECOM Technology Corp
Cesar Segovia, AECOM
As the connected and automated vehicle (CAV) fleet expands, understanding their impact on future transportation plans including tolled managed lanes becomes essential. However, there is no CAV modeling data available, and better tools are needed to assess future impacts. Therefore, the deep uncertainty associated with evaluating effects from CAVs on traffic in a metropolitan area may best be assessed with an exploratory planning approach. Exploratory modeling for quantitative estimates using qualitative data is an approach gaining recognition for addressing issues of deep uncertainty. It can provide an analytical framework for accommodating future improvements with available data, while considering the levels of uncertainty for identified variables. Robust Decision Making (RDM) is one approach that uses simulation modeling to “stress-test” strategically defined scenarios to provide insight on how transportation plans may perform under specific assumptions. RDM can employ Florida’s Turnpike Enterprise Express Lanes Time of Day (ELToD) Model. It is a dynamic traffic assignment (DTA) model with a mixed multinomial logit (MMNL) toll choice submodel that allows vehicles to perform an en-route choice at each ingress and egress point. For CAV modeling, multiple enhancements were completed including income level and land use density for influencing adoption rate; activity-based model (ABM) output as input to DTA assignment; lane capacity by facility type by CAV penetration rate, induced demand trips, CAV freeway preference, and value of travel time savings (VTTS). A demonstration of the exploratory approach on a managed lanes network showed the varied levels of impact based on the selected CAV variables. Either a one-lane or two-lane system may be more robust depending on the future impact levels.
Dynamic Pricing for High Occupancy Toll Lanes along a Freeway Corridor based on Bathtub Model
Irene Martinez Josemaria (firstname.lastname@example.org), University of California, IrvineShow Abstract
Wenlong Jin, University of California, Irvine
Congestion pricing is a well-known strategy to control the demand to certain infrastructures. In particular, high-occupancy-toll (HOT) lanes charge a toll to single-occupancy vehicles (SOVs) that want to use it, while high-occupancy-vehicles (HOVs) can drive in it at no cost. This strategy can maximize the flow of vehicles in HOT lanes when the demand of HOVs is low. At the same time, the shift of SOVs to the HOT lane will reduce the congestion in general purpose (GP) lanes. The objective of this paper is to design a dynamic pricing strategy for the HOT lanes along a freeway corridor, so as to reduce traffic congestion and environmental impacts, and improve equity among drivers. To do so, we assume the generalized bathtub model (1) to capture the traffic flow dynamics of the system. An important variable of the bathtub model is the trip distance distribution, which in the corridor case will be a probability mass function, since the entrances and exits of the freeway will determine the possible trip distances. Moreover, we propose a pricing scheme that depends on both the traffic state and on individual's trip distances. Under certain assumptions, is shown how the proposed control strategy on this system has a stable equilibrium solution for Vickrey's bathtub model (2-3). In the future we are interested in looking at numerical solutions to test the equilibrium and stability for the generalized bathtub model.
Departure time choice and tolls for a high-occupancy toll lane system with heterogeneity in arrival time
Xuting Wang, Pennsylvania State University, University ParkShow Abstract
Vikash Gayah (email@example.com), Pennsylvania State University
Commuter’s departure time choice behavior is one cause of congestion in peak periods. The departure time choice problem has been studied for various transportation systems, such as freeway bottlenecks and urban networks. However, relatively little attention has been paid to freeway systems with both general purpose and high-occupancy toll (HOT) lanes. HOT lanes combine higher occupancy vehicle (HOV) lanes and congestion pricing strategies by charging single-occupancy vehicles (SOVs) to use HOV lanes during peak periods. This study attempts to fill this gap by examining how commuter departure time choice will impact the presence of congestion and optimal tolling schemes on freeways with HOT lanes when commuters have different desired arrival times. The two objectives of this study are: (i) analytically study the departure time user equilibrium for heterogeneous commuters, and (ii) obtain pricing schemes to minimize the commuters’ total travel time and schedule delay cost. To make the analysis manageable, at most three groups of commuters are considered. Numerical results are provided to show how commuters’ heterogeneity changes the system performance and the design of optimal tolls. The results of this study show that heterogeneity in desired arrival times will reduce the commuters’ total travel time and schedule delay cost, and introducing appropriate pricing schemes can further reduce the cost. The analysis can be extended to general cases with multiple groups of commuters.
Dedicated Lane Design for Connected and Automated Vehicles on Freeways
Xiangdong Chen, Tsinghua UniversityShow Abstract
Chen Yang, Tsinghua University
Meng Li (firstname.lastname@example.org), Tsinghua University
Azusa Toriumi, University of Tokyo
Xi Lin, Tsinghua University
The establishment of dedicated CAV (connected and automated vehicle) lanes has been regarded as an effective approach to address heterogeneous traffic with both CAVs and regular vehicles (RVs), thereby promoting both traffic efficiency and safety. In the start implementation of dedicated CAV lanes, freeways may be regarded as the more practical scenario, since urban roads have complicated road networks with intensive intersections. Therefore, this study proposes a design scheme of dedicated CAV lanes on freeways to enable CAVs of Level 3 to perform some Level-4 functionalities. Road geometric design is investigated to achieve a separated right-of-way (ROW) for CAVs and support automated driving functions. The central lanes are reformed to dedicated lanes to eliminate the intervention of RVs, with entrances and exits being deployed along the dedicated lane for CAVs to enter or leave. Simulation approach is applied to obtain the parameters of the entrance and exit configuration, including the length of lane-changing areas on both the CAV lane and the RV lane, and the intermediate length between the two lane-changing areas. In addition, the performance of the proposed scheme is validated by simulation experiments under different demand patterns and lane configurations.
Influence of Lane Policies on Four-lane Freeway with Mixed Traffic of Manual and Connected and Autonomous Vehicles
Yitong Chen (email@example.com), Southeast UniversityShow Abstract
Xuedong Hua, Southeast University
Huasong Zhang, Southeast University
Dan Yang, Southeast University
Wenqiang Zhang, Southeast University
Connected and autonomous vehicles (CAVs) have become a hot spot and are soon to be applied in widely use. Previous studies have been carried out to find traffic management measures to enhance the capacity and efficiency of traffic with CAVs, especially mixed traffic of CAVs and Manual Vehicles (MVs), including setting exclusive lanes. However, little research involved with specific exclusive lane policies. Therefore, this paper aims to study the influence of different exclusive lane policies on mixed traffic and provide recommended lane policies under various traffic volumes and CAV penetration rates. A four-lane freeway with 14 different exclusive lane policies was considered, and cellular automaton model was applied to simulate the running of vehicles. By comparing traffic flow, average speed and speed difference between MVs and CAVs, we can draw some useful conclusions on exclusive lane setting. It is found that When the occupancy rate is 0.1, GGGG performs best. When the proportion is over 0.3, CCGM or CCMM should be chosen. CCGC is best when the occupancy rate is 0.9. And according to average speed, GGGG, CCGG, MGGC, CCGM perform better than the others.
Investigating the Impact of Tolling System on I-66 Inside the Capital Beltway
Sara Zahedian, University of Maryland, College ParkShow Abstract
Amir Nohekhan, University of Maryland, College Park
Kaveh Sadabadi, University of Maryland
This paper investigates the impacts of the tolling policy on Interstate 66 and its alternative routes in the immediate impact areas. I-66 inside the Capital Beltway (I-495) is a major corridor connecting Northern Virginia to downtown Washington, D.C. All lanes on this stretch of I-66 are tolled in the direction of peak traffic during rush hours. Toll amounts are set dynamically according to congestion levels and high occupancy vehicles (two people and more) are exempt from the toll. This study provides a before-after study to evaluate the effectiveness of this tolling policy in combating congestion and improving travel time reliability along the corridor. Additionally, using historic data, various models are trained and tested to predict toll range, speed, flow rate, and travel time difference between I-66 and its alternative routes.
Calculation method on the capacity of left-turn traffic at intersections in setting reverse variable lane
Fei Lin, Shandong University of TechnologyShow Abstract
Feng Sun, Shandong University of Technology
Rongji Zhang, Shandong University of Technology
Xiaolong Ma, Zhejiang University
Fulu Wei, Shandong University of Technology
Chenchen Li, Shandong University of Technology
The reverse variable lane is described as one of the most effective methods of increasing rush-hour capacity of existing streets under the proper conditions. To effectively alleviate the traffic congestion caused by over-saturation of left-turn movement, the reverse variable lane has been applied at intersections in some cities. At present, it is impossible to determine how much left-turn traffic capacity can be improved by the setting of reverse variable lane, resulting in a lack of effective basis for determining the signal timing of intersection management and control. Therefore, through in-depth research and analysis of the current intersection's reverse variable lane operation characteristics, we propose a calculation method on the capacity of left-turn traffic at intersections in setting reverse variable lane, which provides a basis for the design of reverse variable lane control schemes. So, it’s necessary to study a method to maximize the intersection performance which setting reverse variable lane, and verify the accuracy of the calculation method through real examples. In the first step, we will analyze the driving characteristics of vehicles in reverse variable lane. Based on these characteristics, then in the second step, calculating the left turn traffic capacity in setting Reversible Lane at Intersections. Finally, we take the setting of intersections with reverse variable lanes in Zibo as examples to validate, which can provide a theoretical basis for urban traffic signal control and management.
Surrogate-based Optimization for Two-region Coordinated Congestion Toll Design
yifan chen, Monash UniversityShow Abstract
Hai Vu, Monash University
NAN ZHENG, Monash University
Ziyuan Gu, University of New South Wales
Nam Hoang, Monash University
Congestion pricing is one of the efficient travel demand management (TDM) strategies. Many existing researches focus on dealing with the toll optimization problem for a single area. However, the urban network is composed of several administrative regions where the regional authorities manage their own subnetworks. As a result, the centric pricing scheme may not be applicable. This paper aims to design a coordinated dynamic pricing scheme for two adjacent areas which experience an overlapping congested period. Unlike the traditional approach centered on the bi-level mathematical programming, we adopt the surrogate models to estimate the input-output mapping, thus searching for the near-optimal solution in the toll design problem. Two types of surrogate models, namely, the radial basis function (RBF) model, and the Kriging model are compared based on the leave-one-out cross validation. The results show that the Kriging model performs much better than the RBF model. Furthermore, using the proposed optimal solution obtained from the Kriging model, the coordinated scheme can reduce the average travel time of the two pricing zones by 15.1% and 19.7% respectively.
Analysis of Complex Weaves in Managed Lanes
Bikram Wadhawan, Hanson Professional ServicesShow Abstract
Amy Causseaux, Florida Department of Transportation
Maria Overton, CTS Engineering, Inc.
Kavita Parikh, Hanson Professional Services
Express lanes are a type of managed lane strategy that use congestion pricing by varying the toll amount to maintain a performance threshold and provide a more reliable travel time. The aim of this study was to develop an analysis methodology to assess the complex or multiple weave segments formed in express lane projects due to the placement of access points. Various scenarios were tested using the Highway Capacity Software (HCS) and VISSIM microsimulation to estimate the capacity of such complex weave segments. The study recommended reporting results from HCS and volume-to-capacity (V/C) ratio obtained from microsimulation to estimate the adequate capacity of complex weave segments. This study also found that there is value in dividing the critical segment into merge, basic freeway and diverge sections for analysis. The speed differential between weaving and non-weaving volumes was found to be minimal, if adequate length was provided and no congestion was observed.
DISCLAIMER: All information shared in the TRB Annual Meeting Online Program is subject to change without notice. Changes, if necessary, will be updated in the Online Program and this page is the final authority on schedule information.