Congestion tolls and parking fees: A comparison of the potential effect on travel behavior

This paper presents a comparison of attitudes towards congestion and parking tolls and explores their effect on travel behavior. The findings indicate that drivers are sensitive mainly to congestion tolls and are willing to change their travel habits to avoid these tolls. The major effect of a congestion toll is the shifting of the time of the journey. High levels of demand elasticity (−1.8 for congestion tolls and −1.2 for parking fees) were found. The readiness to pay parking fees is greater; thus, the effectiveness of congestion tolls in reducing demand is higher during the times the tolls apply.     

Flat versus spatially variable tolling: A case study in Fresno,California

A number of studies have examined the feasibility of temporal variations in tolls. However, spatial variation in tolls has not received much attention, especially in practice. Spatial variation could effectively reduce congestion and increase profits. To fill this gap, we conduct an empirical application on 3 different road segments using the Fresno, California's transportation planning model. Our modeling results in a number of interesting insights. First, the derived optimal flat toll values are very close to the average variable tolls, but the effects of applying spatially variable tolls on improving total revenues (from 4% to 24%) and total improved travel time (from 18% to 1083%) measures are significant. Second, spatially variable tolls are more effective, but more costly, particularly for arterials, which can be attributed to the higher number of access points for arterials. Third, spatial variations in tolls are more effective for peak hours than for off-peak hours and for social optimization than for profit maximization. Fourth, to improve throughputs for both profit maximization and social optimization, the prevalent tolling pattern along a corridor induces lower final volumes per capacity (V/Cs) (after pricing) at the mainline flow sections and relatively higher final V/Cs at the entrance and exit (boundary) points. Finally, optimal toll patterns are not dependent on vehicle miles traveled (VMTs) or volumes but, rather, are related to targeted V/Cs. Therefore, flow-dependent charges along a corridor should be based on V/Cs rather than on volumes or VMTs.     

Optimal distance tolls under congestion pricing and continuously distributed value of time

This paper addresses the optimal distance-based toll design problem for cordon-based congestion pricing schemes. The optimal distance tolls are determined by a positive and non-decreasing toll-charge function with respect to the travel distance. Each feasible toll-charge function is evaluated by a probit-based SUE (Stochastic User Equilibrium) problem with elastic demand, asymmetric link travel time functions, and continuously distributed VOT, solved by a convergent Cost Averaging (CA) method. The toll design problem is formulated as a mixed-integer mathematical programming with equilibrium constraints (MPEC) model, which is solved by a Hybrid GA (Genetic Algorithm)–CA method. Finally, the proposed models and algorithms are assessed by two numerical examples.     

Modelling and evaluation of road pricing in Paris

This article describes the impacts of road pricing in Ile-de-France, a region that includes Paris. The morning peak is studied using METROPOLIS: a dynamic network simulator that treats endogenously travellers' mode, departure time and route-choice decisions. Time-independent tolls on selected links, time-varying cordon tolls, and a network-wide toll proportional to travel time are considered. Welfare gains from the link and cordon tolls are relatively small. The comprehensive travel-time-based toll yields much higher benefits. In all cases, benefits to users amount to a large fraction of toll revenues and exceed the monetised value of reductions in noise, accidents and vehicle emissions.     

Segmenting travellers based on day-to-day variability in work-related travel behaviour

Travel needs for commute and business trips are complex and choices are not made based on the characteristics of individual trips, but instead based on the needs over weeks and months. For example, the cost per trip of commuting by bus varies depending upon the frequency of travel, and the cost of a monthly subway pass depends upon the number of zones visited during that period. Intrapersonal variability, namely the variation in an individual's travel behaviour from day to day, therefore shapes our transport choices and should influence service provision. Changes in working patterns such as increases in part time working, self-employment and tele-commuting challenge the traditionally held assumptions that work activities are fixed in time and space, thus making intrapersonal variability increasingly relevant. This research uses a data-driven approach to segment workers based on their work-related travel behaviour, including frequency of travel and both spatial and time of day intrapersonal variability. The analysis uses survey and seven day travel diary data for over 110,000 people collected over a 19 year period in England. Four groups of workers were identified: infrequent, spatially variable, temporally variable and regular travellers. These groups do not align closely with self-reported working arrangements such as self-employment or part time working. The group of regular travellers has decreased in size between 1998 and 2016 but remains the largest group, containing just under 60% of workers in 2016. Both the infrequent and spatially variable groups have grown over the same period. For a small but growing group of workers, a seven day diary is insufficient to understand their work-related transport needs as little or no work travel is recorded. These findings have implications for the design of public transport ticketing, the design of mobility as a service packages and the appraisal of congestion charging schemes.     

Toll financing in Norway: The success,the failures and perspectives for the future

Public funds for road investments have been subjected to constraints in many countries over the past three decades. Many governments have therefore resorted to financing road infrastructure using tolls. This article investigates what the future may offer with respect to toll financing in Norway. The changing environment in which transport planning takes place requires adaptations such as transforming tolls into congestion pricing schemes. Lessons from Norway may be useful for decision makers in Europe and elsewhere who are concerned with toll financing.     

Estimating congestion toll by using traffic count data — Singapore's area licensing scheme

There are many studies on the Area Licensing Scheme in Singapore. One of the debatable issues is whether or not the congestion toll of $3 is too high. The main objective of this paper is to develop a simple method for estimating the congestion toll by directly using the commonly available traffic count data. In our sensitivity analysis, we use three different scenarios on the choice of the value of travel time savings and four different measures of average wage rates (the national average wage rate the average wage rate for car owners with or without taking into consideration of employment benefits, and the average wage rate per car derived from the average occupancy per car). The sensitivity analyses led to a general conclusion that by 1990, the $3 fee was not too high. We also highlight the fact that it is possible to iterate to the optimal congestion toll by comparing the theoretical congestion toll with the actual toll even when the demand curve is unknown. ©     

Pay to drive in my bus lane: A stated choice analysis for the proposed Lincoln Tunnel HOT lane into Manhattan

This paper presents the findings from a stated choice (SC) analysis conducted in the context of proposed changes to the lane system in use for the Lincoln Tunnel crossing into Manhattan. Currently, the approach road (NJ 495) to the Lincoln Tunnel has six lanes, with three in each direction. During the weekday morning peak period, The Port Authority of New York and New Jersey (PANYNJ) operates a 2.5 miles exclusive bus lane (XBL) for traffic bound for Manhattan. The PANYNJ is considering creating, from existing lanes, a second XBL with the option for passenger vehicles to use it in return for an additional toll, in effect turning it into a high occupancy toll (HOT) lane. Such an approach to increase capacity and reduce congestion is unique nationally and this study looks at drivers' choices between using standard lanes, paying extra to drive on a HOT lane (the new XBL lane), switch to earlier or later departure times, or change their mode of travel. The analysis shows significant differences in the valuation of travel time savings between different population groups and also different departure time periods. The models also reveal a reluctance to change to other crossings, accept changes in departure time or switch to alternative modes.     

A model for time of day and mode choice using error components logit

The severity of road congestion not only depends on the relation between traffic volumes and network capacity, but also on the distribution of car traffic among different time periods during the day. A new error components logit model for the joint choice of time of day and mode is presented, estimated on stated preference data for car and train travellers in The Netherlands. The results indicate that time of day choice in The Netherlands is sensitive to changes in peak travel time and cost and that policies that increase these peak attributes will lead to peak spreading.     

How large is the gap between present and efficient transport prices in Europe?

In this paper, we analyse the gap between present transport prices and efficient transport prices. Efficient transport prices are those prices that maximise economic welfare, including external costs (congestion, air pollution, accidents). The methodology is applied to six urban and interregional case studies using one common optimal pricing model. The case studies cover passenger as well as freight transport and cover all modes. We find that prices need to be raised most for peak urban passenger car transport and to a lesser extent for interregional road transport. Optimal pricing results for public transport are more mixed. We show that current external costs on congested roads are a bad guide for optimal taxes and tolls: the optimal toll that takes into account the reaction of demand is often less than one third of the present marginal external cost.     

The multi-class, multi-criterion traffic equilibrium and the efficiency of congestion pricing

We consider the effect of the so-called second-best tolls on the price of anarchy of the traffic equilibrium problem where there are multiple classes of users with a discrete set of values of time. We derive several bounds of the price of anarchy for this problem when the tolls are considered and not considered as part of the system cost, with the time-based criterion and the cost-based criterion, respectively. All the bounds give us useful information on the effect of the tolls, which can be used to design network toll schemes.     

Modelling new pricing strategies for the Santiago Metro

After twenty years of operation the Santiago Metro decided to start a new strategy of price differences by period in order to decrease congestion in the morning peak and to postpone the acquisition of new equipment. In this paper we report the results of a model specifically designed to test the impact of different price levels on patronage by period. Stated preference (SP) data was collected, focusing on three aspects: change in time of travel, price differences and comfort improvements. A goods-leisure microeconomics framework was adopted to decide on users segmentation and model specification. Two methodological aspects were explored, the non-linear marginal valuation of time displacements and the different known ways to analyse SP rating experiments. In this quest, models were calibrated both with a standard and an optimal probabilistic interpretation of the semantic scale and with the ordinal probit and binary logit models. Comparisons were made and conclusions reached about the more appropriate approach.Finally, the current time-of-day pricing strategy of the Santiago Metro, which commenced operation in February 1994, was simulated using the best models reported in the paper. This was done in order to test their validity against an observed reality.     

Credit-based congestion pricing: A Dallas-Fort Worth application

Under a credit-based congestion pricing policy, net revenues are distributed uniformly among qualifying travelers, to partially offset toll payments. This work predicts the traffic impacts, air-quality changes, welfare effects, and system implementation costs of such a policy, as applied to the Dallas-Fort Worth (DFW) region of Texas. Joint destination-mode choice models were estimated and applied. The status quo and two marginal cost pricing (MCP) scenarios were simulated for the short and long terms, with full feedback of trip costs and times. Monetarized logsum differences suggest that marginal cost pricing of congested freeways in this urban region, followed by travel credit distribution to all workers, is welfare improving for the great majority of such travelers. Moreover, high levels of recurring congestion (V/C ratios exceeding 1.5) are predicted to practically disappear.     

The political calculus of congestion pricing

The political feasibility of using prices to mitigate congestion depends on who receives the toll revenue. We argue that congestion pricing on freeways will have the greatest chance of political success if the revenue is distributed to cities, and particularly to cities through which the freeways pass. In contrast to a number of previous proposals, we argue that cities are stronger claimants for the revenue than either individual drivers or regional authorities. We draw on theory from behavioral economics and political science to explain our proposal, and illustrate it with data from several metropolitan areas. In Los Angeles, where potential congestion toll revenues are estimated to be almost $5 billion a year, distributing toll revenues to cities with freeways could be politically effective and highly progressive.     

A time-period choice model for road freight transport in Flanders based on stated preference data

This paper presents one of the first models explaining the choice of time-period in road freight transport. Policies that would shift some fraction of the trucks from peak to earlier and later periods will contribute to the reduction of congestion. Therefore there is an increasing interest in modelling the time-period sensitivity of road freight transport to changes in travel time and cost by period. The model developed here is based on a stated preference survey amongst receivers of goods in Flanders and was implemented in the strategic freight transport model of the Flemish authorities.     

Changes in the frequency of shopping trips in response to a congestion charge

This paper presents an analysis of shopping trips into London's central shopping district (Oxford Street area) before and after the introduction of the congestion charging scheme in February 2003. In collaboration with a major department store, three surveys have been conducted in order to understand the changes in shopping frequency and the reasons for so doing. The analysis is based on tabulations of the raw data, binary logit models to analyse which customer groups have reduced their shopping frequency and ordered logit models to analyse which groups have reduced their shopping more than others. The outcome shows that within the sample surveyed the congestion charging scheme has caused a significant number to shop less often in central London and only a few to shop more often in the Oxford Street area. Negative experiences with the congestion charging scheme or a generally bad perception of the scheme are the main reasons for this. Other events, such as the Central Line closure or terrorist threats occurring at the same time also have a temporary influence on the shopping frequency in central London. Evidence from other travel demand measures on city centre shopping activities suggest that the long-term effects of the congestion charge could be more positive.     

Dynamic accessibility: Incorporating day-to-day travel time reliability into accessibility measurement

Travel times and hence accessibility in urban areas are susceptible to traffic disruption caused by events such as congestion, roadworks and traffic accidents. Being highly valued by travellers, travel time reliability affects their participation in activities and thus, plays a decisive role in accessibility. The aim of the study was to develop an approach to integrate travel time reliability into the measurement of accessibility. To achieve this, we extended a commonly-used accessibility indicator to include day-to-day variability in travel times. In a case study of the accessibility to the newly-built Queen Elizabeth University Hospital (QEUH) in Glasgow, we used real-time travel times with high temporal resolution collected over a long period of time to demonstrate the applicability and the utility value of this approach compared to the standard accessibility measurement. Our results revealed that travel time reliability varied both temporally and spatially, and zones experienced relatively high levels of accessibility loss due to higher travel time variability. The proposed approach provides a more realistic representation of actual network performance, allows for assessing the effect of travel time reliability on accessibility throughout the day and will help transport planners to trace equity impacts on accessibility due to travel time unreliability.     

Expanding the positive utility of travel through weeklong tracking: Within-person and multi-environment variability of ideal travel time

Travel has been found to have a positive utility—often measured as a desire for non-zero travel time. Although past studies have found that desired travel time varies by trip attributes, they often focused on a single trip purpose (e.g., commute) or single time point (e.g., peak period of one day) and rarely captured variation within individuals and across multiple travel environments. To address these limitations, we employed a smartphone-based travel behavior survey of 186 users making 4397 trips in the Washington, DC, and Blacksburg, VA metropolitan areas. For each user, multiple trips were recorded and the user was asked to repeatedly report on the ideal travel time for each trip. We found that desired travel time varied across different trip environmental characteristics and purposes. Ideal travel time was longer for active travel trips, leisure trips, weekend trips, and when the user conducted activities during trips (e.g., talking, using the phone, looking at the landscape) and traveled with companions. Our study suggests the need for more realistic estimation of the value of travel time savings and the need for quantifying the effect of multitasking during travel on people's willingness to reduce travel time. Practitioners should also consider providing better urban infrastructure for pedestrians and bicyclists to fulfill their trips, as their ideal travel times closely match actual travel times.     

The determinants of mode of transport to work in the Greater Dublin Area

Rapid economic and demographic change in the Greater Dublin Area over the period 1996–2006, with associated increases in car dependence and congestion, has focused policy on encouraging more sustainable forms of travel. In this context, knowledge of current travel patterns and their determinants is crucial. Here we concentrate on travel for a specific journey purpose, namely the journey to work. Using data on the full population of working individuals from the 2006 Census of Population, we analyse the influence of travel and supply-side characteristics, as well as demographic and socio-economic characteristics on the choice of mode of transport to work in the Greater Dublin Area. The results indicate that household composition, public transport availability, journey time and work location are particularly significant in explaining the choice of mode of transport to work.     

A multi-objective approach to scheduling joint participation with variable space and time preferences and opportunities

Activity scheduling supports activity-based analysis in travel demand management and promotes a potentially popular traveler assistance service. A multi-objective approach is proposed to schedule joint participation of multiple individuals, in which the candidate space-time opportunities for joint participation are identified by a concept of time-varying network-based prisms, and optimal opportunities for joint participation are determined by the non-dominated sorting genetic algorithm-II (NSGA-II) with four objectives (i) minimizing cost for congestion charges, (ii) maximizing participation desirability of time-of-day, (iii) minimizing total travel distance and (iv) time in the trips of multiple individuals. A scenario of joint participation among four people is designed and implemented to demonstrate the feasibility of this approach. The results suggest that this approach has the ability to schedule activities within real situations.