Congestion pricing is of increasing interest to transportation agencies interested in better managing demand for limited transportation infrastructure. It is well established in many European and Asian cities and is likely to be implemented in several North American cities in the near future. This session will cover recent research on congestion pricing covering a range of topics including new technologies, modeling approaches, implementations.
Geofencing to Enable Differentiated Road User Charging
Petter Arnesen, SINTEFShow Abstract
Hanne Seter, SINTEF
Ørjan Tveit, Statens vegvesen
Mats Bjerke, Q-Free
Tolling has normally a dual purpose in Norway. The first goal is to finance a project or a change in the public appearance in an area, for instance extended public transport. The second goal is to change travel behaviour for travellers by private cars to other more environmentally friendly modes. Today, this tolling system is based on fixed points on the road network, not necessarily able to capture all usage of the roads evenly. Within the research project GeoSUM (Geofencing for Smart Urban Mobility) a solution where the driver instead of tolling perceives road user charging as a direct cost as a function of how much and how the road network is piloted. The key technology for this system is geofencing.
Techonologies For Congestion Pricing
Lewis Clements, University of Texas, AustinShow Abstract
Kara M. Kockelman (firstname.lastname@example.org), University of Texas, Austin
William Alexander, University of Texas, Austin
Congestion pricing of high-demand roadways seeks to influence travelers’ route choices, trip timing, modes, and destination choices, to keep vehicles moving and avoid excessive congestion. This paper describes the use of various technologies to enable more advanced and cost-effective congestion pricing applications, and a credit-based policy to ensure equitable network access for all travelers. Video-based systems require cameras to capture the state of traffic, plus some form of communication back to users. Both DSRC and cellular-based systems use GPS data to price roads and toll users based on traffic conditions. DSRC employs roadside units (RSUs) to receive and send messages to in-vehicle DSRC units. A cellular-based system could use communications from cellular towers in combination with a smartphone, on-board diagnostics port (OBD-II), or pre-installed cellular chip. DSRC is a valuable technology to pilot congestion pricing at highly congested locations, such as bridges and major highways, while cellular communications enable congestion pricing across entire networks. VMT taxes can be relatively simple, or variable in space and time, facilitating transportation-agency cost recovery. A next step for roadway management is congestion pricing (CP), to better reflect the marginal delay costs of one’s travel choices. When coupled with travel credits, CP can better ensure welfare gains for most travelers.
Quantifying responses to changes in the jurisdiction of a congestion charge: A study of the London Western Extension
Laila AitBihiOuali (email@example.com), Imperial College LondonShow Abstract
Davis Musuuga, Imperial College London
Daniel Graham, Imperial College London
This paper assesses and quantifies responses to changes in the area over which the congestion charge is applied, with a successive focus on (i) an extension and (ii) a reduction in the size of the zone. We exploit the unanticipated nature of both the implementation and removal of London's Western Expansion Zone (WEZ) as quasi-natural experiments. We use the UK Department of Transport Annual Average Daily Flow (AADF) data, which records traffic flows for seven transport modes (including cars, buses, bicycles, heavy and light goods vehicles). Using a difference-in-differences approach, we find that the introduction of the WEZ led to a 4.9% decline in road traffic volume. HGVs traffic did not significantly change post-WEZ, which indicates that their road demand is price inelastic. The removal of the WEZ led to no significant variations in traffic. This result suggests that unanticipated financial constraints may have a lasting effect in the formation of new habits and that there may be inertia in individual behavior.
Variable Congestion Tolling and Shared Mobility: A Match Worth Making?
Patrick DeCorla-Souza, Federal Highway Administration (FHWA)Show Abstract
Paul Minett, Trip Convergence Ltd.
This paper presents an innovative travel demand management concept involving variable congestion pricing and incentives synergistically combined with shared mobility. With this concept, variable congestion-based charges would be imposed during peak periods on the entire urban freeway network. To address equity concerns while limiting diversion to alternative toll-free routes and increasing public acceptability of new charges, travelers would be presented with three attractive new travel choices: (1) using a mobile app, drivers could find and pick up a passenger heading to a convergent destination and thereby earn fares that could be used to pay congestion charges; (2) drivers could leave their cars at home and get rides at a nominal fare with someone who wishes to drive, whilst receiving an incentive for traveling as a passenger; and (3) those who don’t currently drive could thus also have an additional travel option to enhance their mobility. The concept could have significant impacts on challenges related to urban mobility, congestion, and air pollution; and could delay or avoid expensive expansion of freeways. The paper presents results from a sketch-planning financial evaluation of the concept which suggests that it could be financially viable and potentially generate surplus revenues that could help address transportation funding gaps.
A Validated Multi-Agent Simulation Test Bed to Evaluate Congestion Pricing Policies on Population Segments by Time-Of-Day in New York City
Yueshuai He (firstname.lastname@example.org), University of California, Los AngelesShow Abstract
Jinkai Zhou, New York University
Ziyi Ma, New York University
Ding Wang, New York University
Di Sha, New York University
Mina Lee, New York University
Joseph Chow, New York University
Kaan Ozbay, New York University
Emerging transportation technologies differ from other engineering innovations because they require careful testing and evaluation between prototyping and deployment to avoid high public costs and safety risks. This is especially the case for New York City, the largest megacity in the U.S., with an unprecedented simultaneous emergence of policies and technologies. Evaluation of the demand for emerging transportation technologies and policies can vary by time of day due to spillbacks on roadways, rescheduling of travelers’ activity patterns, and shifting to other modes that affect the level of congestion. These effects are not well-captured with static travel demand models. We calibrate and validate the first open-source multi-agent simulation model for New York City, called MATSim-NYC, to support agencies in evaluating policies such as congestion pricing. The simulation-based virtual test bed is loaded with an 8M+ synthetic 2016 population calibrated in a prior study to fit ride-hail services and bike-share. The road network is calibrated to INRIX speed data and average annual daily traffic for a screenline along the East River crossings. The model was used to evaluate a congestion pricing plan proposed by the Regional Plan Association and suggested a much higher (127K) car trip reduction compared to their report (59K). The pricing policy would impact the population segment making trips within Manhattan differently from the population segment of trips outside Manhattan: benefits from congestion reduction benefit the former by about 50% more than the latter, which has implications for redistribution of congestion pricing revenues.
Exploratory Evaluation of a Concept Combining On-Demand Ridesharing with Congestion Pricing
Patrick DeCorla-Souza, Federal Highway Administration (FHWA)Show Abstract
This paper presents an innovative travel demand management concept involving congestion pricing synergistically combined with on-demand ridesharing. An exploratory evaluation of the concept was undertaken using sketch-planning tools developed by the Federal Highway Administration. The analysis suggests that the concept could be financially viable, achieve significant economic benefits, and potentially generate surplus revenues that could be sufficient to address transportation funding gaps.
A "LITE" ACTIVITY-BASED MODELING APPROACH FOR CONGESTION PRICING IN SAN FRANCISCO
Drew Cooper, San Francisco County Transportation Authority (SFCTA)Show Abstract
Joe Castiglione, San Francisco County Transportation Authority (SFCTA)
David Long, Instituicao de Ensino Sao Francisco
Colin Dentel-Post, Alameda County Transportation Commission
Rachel Hiatt, San Francisco County Transportation Authority (SFCTA)
Bhargava Sana, San Francisco County Transportation Authority (SFCTA)
Daniel Tischler, San Francisco County Transportation Authority (SFCTA)
This paper describes the development and application of a “lite” version of an activity-based travel demand model for a congestion pricing study in San Francisco. The “lite” model concept was inspired by the study’s needs to explore a wide range of pricing scenarios with the ability to represent prices that differ by user class and analyze equity outcomes, while minimizing model runtime. The approach uses skims generated by a limited set of full model runs to generate a large set of skims representing other alternatives.
Incorporating Travel Time Reliability In Equitable Congestion Pricing Schemes For Heterogeneous Users And Bimodal Networks
Fatemeh Fakhrmoosavi, Michigan State UniversityShow Abstract
Ali Zockaie (email@example.com), Michigan State University
Khaled Abdelghany, Southern Methodist University
Congestion pricing is proposed as an effective travel demand management strategy to circumvent the congestion problem and generate revenue to finance developmental projects. There are several studies focusing on optimal pricing strategies to minimize the congestion level or maximize the revenue of the system. However, due to equity issues, benefiting only users with higher value of times is claimed to be the main factor that prevents implementation of such policies in practice. While many studies aimed to tackle the equity issues by certain welfare analyses, most of these studies fail to fully consider realistic features of users’ behavior and the uncertainty in link travel times. Given the variability of travel time in real-world networks and the impacts of pricing policies on path travel time distributions, it is important to consider the users’ reliability valuations, in addition to their travel time valuations. Thus, the goal in this study is to find an equitable pricing scheme that minimizes the total travel time of auto users in a general bimodal network considering heterogeneous users with different values of time and reliability. A particle swarm optimization algorithm is proposed to find self-funded and Pareto-improving optimal toll values. A reliability-based user equilibrium algorithm is embedded into this optimization algorithm to assign travelers to the equilibrated paths for different user classes given toll values. The proposed approach is successfully applied to a modified Sioux Falls network to explore impacts of subsidization strategy, congestion level, and considering travel time reliability on the pricing strategy and its effectiveness.
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