Observed and simulated traffic impacts from the 2013 Bay Area Rapid Transit strike

Despite high costs, many cities build public transit to address regional equity, environmental and economic goals. Although public transit accounts for a minority of trips (～5%), the impact is widely felt when service is suspended during a strike through excess road demand and slower journeys. In 2013, Bay Area Rapid Transit (BART) workers participated in two brief strikes, and the resulting traffic conditions illustrate the value of transit to drivers in the San Francisco Bay Area region. This paper tests the impact of rail transit service interruption on freeway traffic conditions using volumes and travel times. During the strike, regional freeway conditions showed negligible change. However, on facilities that parallel BART service, the impacts are as bad as the worst day of a typical week. Conditions on the San Francisco–Oakland Bay Bridge showed significant impacts with travel times and volumes nearly doubling the baseline median values on the worst day.     

A volatile relationship: The effect of changing gasoline prices on public support for mass transit

The determinants of public opinion toward public transit is a little-researched topic, though a better understanding of what makes consumers willing to support transit may reveal which attributes of transit consumers value most. One determinant of people’s willingness to support investments in mass transit may be the price of fuel for transit’s principal competition, the private automobile. In this paper, I examine the relationship between the cost of gasoline and stated willingness to invest public money in mass transit improvements. I hypothesize that fuel price volatility—in addition to price itself—is a determinant of support for more mass transit funding, controlling for other factors. As the price of gasoline becomes more uncertain, the public should, all else equal, support investment in mass transportation, a form of transportation that may provide some measure of protection from the price of fuel. Results suggest a strong effect of price volatility on consumers’ willingness to support transit expenditures.     

Asymmetric responses of highway travel demand to changes in fuel price: An explanation via fuel price uncertainty

Previous research has examined asymmetric effects of fuel price uncertainty on energy demand. If we consider that energy demand is related to travel demand, the changes in fuel prices may have asymmetric effects on highway travel demand via fuel price uncertainty. In other words, when in general fuel price is steadily rising, the highway traffic volume decreases by a small percentage. On the other hand, the highway traffic volume increases by a large percentage when fuel prices are falling. We hypothesize that the uncertainty in fuel prices generates this kind of asymmetric effect on highway traffic volume in Korea. We use the Korean monthly fuel price and highway traffic volume data from 2001 to 2009, and define the intra-month (weekly) fuel price changes as monthly fuel price volatility which is a proxy for monthly fuel price uncertainty. We found that the direction of the change in fuel prices had asymmetric effects on highway travel demand and that the fuel price uncertainty led drivers to respond asymmetrically to the changes in fuel prices.     

Parking subsidies and travel choices: Assessing the evidence

This article reviews empirical studies of how employer-paid parking affects employees' travel choices. A strong effect is found: parking subsidies greatly increase solo driving. When employers reduce or remove parking subsidies, a significant number of solo drivers shift to carpools and/or transit. This conclusion is based on studies of parking subsidies in a variety of circumstances, including central city and suburban areas, private and public employers, and clerical and professional employees. Three measures are developed to compare changes in commute patterns: changes in the share of solo drivers. changes in the number of autos driven to work per 100 employees, and the parking price elasticity of demand for solo driving. The studies reviewed here show that 19 to 81 percent fewer employees drive to work alone when they pay for their own parking. Because 90 percent of American commuters who drive to work receive employer-paid parking, these findings are significant for designing transportation policies to reduce air pollution, traffic congestion, and energy consumption.     

Elasticities of fuel and traffic demand and the direct rebound effects: An econometric estimation in the case of Norway

We estimate the elasticities of fuel and travel demand with respect to fuel prices and income in the case of Norway. Furthermore, we derive the direct rebound effects that explain the degree to which a fuel price increase is “offset” in the form of greater fuel use and/or travel due to improvements in vehicle fuel efficiency. For this purpose, we use and compare two alternative econometric approaches: the error correction model (ECM) and the dynamic model. Our initial assumption is that one should not be indifferent with respect to the approach used to derive elasticities. The data used are for the period 1980–2011. Our results indicate the following: (1) the dynamic model fits the data better than the ECM model does; (2) the estimated elasticities of fuel demand with respect to price and income are −0.26 and 0.06 in the short run and −0.36 and 0.09 in the long run. For travel demand, the respective elasticities are −0.11 and 0.06 in the short run and −0.24 and 0.13 in the long run, implying inelastic demands for fuel and travel demand; and (3) rebound effects indicate that 0.26% and 0.06% of fuel savings as a result of fuel price increase will be offset in the form of more fuel use in the short run and in the long run, respectively, if fuel efficiency increases by 1%. Our policy recommendations are that policies should not be indifferent to the methods used to derive elasticities. We contend that it is crucial to seriously consider rebound effects in policy making because basic elasticity estimates exaggerate the impact of fuel price increases.     

Passengers’ response to transit fare change: an ex post appraisal using smart card data

Fare change is an effective tool for public transit demand management. An automatic fare collection system not only allows the implementation of complex fare policies, but also provides abundant data for impact analysis of fare change. This study proposes an assessment approach for analyzing the influence when substituting a flat-fare policy with a distance-based fare policy, using smart card data. The method can be used to analyze the impact of fare change on demand, riding distances, as well as price elasticity of demand at different time and distance intervals. Taking the fare change of Beijing Metro implemented in 2014 as a case study, we analyze the change of network demand at various levels, riding distances, and demand elasticity of different distances on weekdays and weekends, using the method established and the smart card data a week before and after the fare change. The policy implication of the fare change was also addressed. The results suggest that the fare change had a significant impact on overall demand, but not so much on riding distances. The greatest sensitivity to fare change is shown by weekend passengers, followed by passengers in the evening weekday peak time, while the morning weekday peak time passengers show little sensitivity. A great variety of passengers’ responses to fare change exists at station level because stations serve different types of land usage or generate trips with distinct purposes at different times. Rising fares can greatly increase revenue, and can shift trips to cycling and walking to a certain extent, but not so much as to mitigate overcrowding at morning peak times. The results are compared with those of the ex ante evaluation that used a stated preference survey, and the comparison illustrates that the price elasticity of demand extracted from the stated preference survey significantly exaggerates passengers’ responses to fare increase.     

集聚经济视角下轨道交通投资对城市系统均衡的影响

随着城镇化进程加快,城市规模增加所带来的集聚效应和交通拥堵等负外部性之间的矛盾越来越突出,优化城市交通基础设施建设是缓解该矛盾的重要举措。本文同时考虑了集聚经济和交通拥挤两种外部性,构建并求解了一个两区域城市空间结构模型,分三种情况探究了轨道交通的投资引入和道路容量的优化对城市规模和城市空间结构均衡的影响。结果表明,轨道交通的投资引入能够增加城市人口规模和社会福利,使城市结构更加紧凑。但是,随着集聚经济水平的提高,城市规划者应逐步完善公交配套设施,以降低公交拥挤成本,提高公交出行分担率;还应制定相应的福利政策,避免由于个体效用下降而导致人口流出。     

Net tax incidence for urban public transit subsidies in New Zealand

This paper examines the impact of policy changes in the funding of New Zealand public transit modes.These changes, introduced in 1983, are evaluated in terms of the net incidence of public transit subsidy assistance, taking into account its source of funding and the income class of those commuters benefiting from the subsidy. The general conclusion is that the net incidence of subsidy assistance remains progressive (i.e., a transfer from high to low income commuters) following the introduction of shared funding on the predominant public transit modes (rail and bus), sourced from income tax (central government) and property tax (regional/local government). However, because of the predominance of medium to high income commuters on rail vis-a-vis bus and the traditional source of funding on these modes in terms of income tax (a progressive tax source) and property tax (a regressive tax source), the degree of progressivity previously associated with public transit subsidies has now substantially reduced.The analysis and opinions expressed in this paper are the responsibility of the author alone and do not purport to represent the views of the Ministry of Transport.     

Estimating traffic demand risk – A multiscale analysis

This paper proposes a novel method for estimating the traffic demand risk associated with transportation. Using mathematical properties of wavelets, we develop a statistical measure of traffic demand sensitivity with respect to GDP. This measure can be adapted in a flexible way to capture risk levels relevant for different investment horizons. We demonstrate the timescale decomposition of risk with Swedish traffic demand data for 1950–2005. In general, rail transport shows a stronger co-movement with GDP than road transport. Moreover, we examine the volatility exhibited by traffic demand. Our findings suggest that rail investments are more risky than road investments. Since the findings can be used for optimal investment timing and for choice between public investment alternatives, they are deemed important for public policy in general.     

A study of traveler behavior under traffic information-provided conditions in the Beijing area

ABSTRACT

The quality of traffic information has become one of the most important factors that can affect the distribution of urban and highway traffic flow by changing the travel route, transportation mode, and travel time of travelers and trips. Past research has revealed traveler behavior when traffic information is provided. This paper summarizes the related study achievements from a survey conducted in the Beijing area with a specially designed questionnaire considering traffic conditions and the provision of traffic information services. With the survey data, a Logit model is estimated, and the results indicate that travel time can be considered the most significant factor that affects highway travel mode choice between private vehicles and public transit, whereas trip purpose is the least significant factor for private vehicle usage for both urban and highway travel.     

On the financial viability of mass transit development: the case of Hong Kong

Mass transit projects are often a top contender of many cities to meet their increasing demand for travel. Despite the global trend of privatization, mass transit services, as public goods, remain largely being provided and operated by the public sector. Hong Kong is one of the few exceptions that all mass transit services are commercially operated. Both rail and bus services in Hong Kong are reputable for their quality and profitability, often serving as benchmarks for new projects. In this study, we investigate the factors contributing to this success. In particular, we ascertain the quality of transit service provision by the private sector over the past two decades. Then, we conduct an in-depth analysis of the account books of leading railway and bus operators in Hong Kong so as to shed light on their financial viability. Through this study, we hope to present crucial factors for providing financially viable private transit services.     

Climate change mitigation and co-benefits of feasible transport demand policies in Beijing

Urban car transportation is a cause of climate change but is also associated with additional burdens such as traffic congestion and air pollution. Studies of external costs and potential impacts of travel demand management help to define policy instruments that mitigate the damaging impact of transportation. Here, we analyze different externalities of car transportation in Beijing and show that social costs induced by motorized transportation are equivalent to about 7.5–15.0% of Beijing’s GDP. Congestion and air pollution contribute the most with climate change costs being the most uncertain. We show that a road charge could not only address congestion but also has environmental benefits. The paper investigates the role of demand elasticities and demonstrates that joint demand and supply-side policies provide considerable synergies.     

Passenger rail in North America in the light of developments in Western Europe and Japan

Because of different geo‐demographic and economic conditions, the impact of the new passenger modes (road and air) on rail travel was much larger in North America than in Europe. In 1960s and 1970s, as the railway share of intercity traffic in North America shrunk to a negligible one or two percent, the passenger trains were abandoned by private railway companies and taken over by state organizations, which have continued to operate traditional trains and generate mounting losses. On the technology side, no attempts have been made to improve competitiveness of trains vis‐a‐vis automobiles and airplanes.

In Europe and Japan, the railways responded to the challenge by (i) upgrading the performance (speed) and comfort of traditional trains operating on existing tracks and (ii) developing trains which could, on short and intermediate range distances, compete successfully, in terms of speed and economy, with the road and air modes. The Japanese (Shinkansen trains) and French (TGV trains) experience clearly shows that trains operating on dedicated lines at average speeds of 150 to 200 km/hr provide a superior transportation service and economy on high‐traffic intercity routes of up to about 500 km length. In this paper the factors responsible for the present status of passenger rail in North America are analysed, the current policies in the U.S. and Canada are evaluated in the light of experience to date and developments abroad, and suggestions for a long‐term passenger rail policy are made. This includes examination of (i) the viability of continued subsidization of traditional train services, (ii) the viability of operation of faster trains on existing tracks, (iii) the scope for introduction of modern, fast trains on dedicated lines in high‐density, intercity corridors, (iv) the application of fast trains as access to major airports and integration of airports with fast intercity lines, and (v) the impact of energy (oil) consumption in transportation.

     

Integrated transit services for minimum cost operation considering heterogeneous demand

Abstract

In large metropolitan areas, public transit is a major mode choice of commuters for their daily travel, which has an important role in relieving congestion on transportation corridors. The purpose of this study is to develop a model which optimizes service patterns (SPs) and frequencies that yield minimum cost transit operation. Considering a general transit route with given stops and origin-destination demand, the proposed model consists of an objective total cost function and a set of constraints to ensure frequency conservation and sufficient capacity subject to operable fleet size. A numerical example is provided to demonstrate the effectiveness of the developed model, in which the demand and facility data of a rail transit route were given. Results show that the proposed model can be applied to optimize integrated SPs and headways that significantly reduce the total cost, while the resulting performance indicators are generated.     

Solving network equilibrium problems on multimodal urban transportation networks with multiple user classes

The capacity of the high‐speed train to compete against travel demand in private vehicles is analysed. A hypothetical context analysed as the high‐speed alternative is not yet available for the route studied. In order to model travel demand, experimental designs were applied to obtain stated preference information. Discrete choice logit models were estimated in order to derive the effect of service variables on journey utility. From these empirical demand models, it was possible to predict for different travel contexts and individuals the capacity of the high‐speed train to compete with the car, so determining the impact of the new alternative on modal distribution. Furthermore, individual willingness to pay for travel time saving is derived for different contexts. The results allow us to confirm that the high‐speed train will have a significant impact on the analysed market, with an important shift of passengers to the new rail service being expected. Different transport policy scenarios are derived. The cost of travel appears to a great extent to be a conditioning variable in the modal choice. These results provide additional evidence for the understanding of private vehicle travel demand.     

Testing the limits of TSM: the 1984 Los Angeles Summer Olympics

This paper analyzes the impact of the transportation system management (TSM) program employed during the 1984 Los Angeles Summer Olympics. Two issues are examined. First, the impact of the various elements of the TSM program on transportation system performance is measured by conducting a series of traffic simulation studies. The results show that TSM was an important contributing factor in the favorable traffic conditions experienced during the Olympics. Second, the potential of employing TSM as a long-term transportation policy strategy is assessed. It is concluded that the travel behavior changes that occurred in response to the TSM program were unique and short-term. Under ordinary circumstances, incentives do not exist to induce changes of the magnitude observed during the Olympics.     

Interpreting employee telecommuting adoption: An economics perspective

Travel demand is derived from activities at the trip destination; therefore, media that have the potential to provide services previously only supported by transportation will have a chance to be chosen by passengers. The idea of telecommuting is considered the most promising substitute of work trips and thus a good strategy of transportation demand management. From a microeconomics perspective, demand for goods or services can be interpreted as a function of prices and generalized income. Therefore, telecommuting adoption is viewed as a trade-off among the prices of telecommuting itself, substitutes, and complements, as well as generalized income and situational constrains incurred by the employee. The underlying rationale is interpreted by elasticity analysis of aggregate telecommuting demand, based on an adoption model, with respect to various decision variable. The results indicate that the elasticity with respect to the price that the employee may incur in order to telecommute is the largest one, and the elasticity with respect to the living space at home is the second one. Additionally, all of the elasticities found in the group of employees currently commuting by private transportation are greater than the corresponding ones found in the group of transit riders. These findings are expected to have significant implications of transportation policies. This revised version was published online in June 2006 with corrections to the Cover Date.     

Distinguishing the land use effects of road pricing based on the urban form attributes

This paper studies the effects of road pricing on land use under different development scenarios (business as usual scenario and transit oriented development scenario) by a quantitative method, which combines the integrated land use and transport interaction model (TRANUS model) with the scenario-planning techniques. Moreover, in order to further analyze the differences of the land use effects of road pricing on traffic analysis zones (TAZs) with different urban form attributes, a quantitative classification method combining factor analysis and cluster analysis is then used to quantitatively classify TAZs. The results demonstrate that the effects of road pricing on the land use of a specific region depend on the urban form attributes of the region. The higher the densities of employments and population, and better street design (high densities of street and intersections) and public transportation condition, the less the region is negatively affected by road pricing, and vice versa. More importantly, rail transit can alleviate the negative impact of road pricing on commercial development and population concentration of the region. Therefore, before introducing a road pricing policy, it is necessary to develop public transport system, especially rail transit.     

Heuristic policy analysis of regional land use,transit, and travel pricing scenarios using two urban models

To address some of the uncertainties inherent in large-scale models, two very different urban models, an advanced travel demand model and an integrated land use and transportation model, are applied to evaluate land use, transit, and auto pricing policies in the Sacramento, CA (US), region. The empirical and modeling literature is reviewed to identify effective land use, transit, and pricing policies and optimal combinations of those policies and to provide a comparative context for the results of the simulation. The study illustrates several advantages of this approach for addressing uncertainty in large-scale models. First, as Alonso [Predicting the best with imperfect data, AIP Journal (1968)] asserts, the intersection of two uncertain models produces more robust results than one grand model. Second, the process of operationalizing policy sets exemplifies the theoretical and structural differences in the models. Third, a comparison of the results from multiple models illustrates the implications of the respective models' strengths and weaknesses and may provide some insights into heuristic policy strategies. Some of the key findings in this study are (1) land use and transit policies may reduce vehicle miles traveled (VMT) and emissions by about 5–7%, and the addition of modest auto pricing policies may increase the reduction by about 4–6% compared to a future Base Case scenario for a 20-year time horizon; (2) development taxes and land subsidy policies may not be sufficient to generate effective transit-oriented land uses without strict growth controls elsewhere in the region; and (3) parking pricing should not be imposed in areas served by light rail lines and in areas in which increased densities are promoted with land subsidy policies.     

Estimating fuel demand elasticities to evaluate CO2 emissions: Panel data evidence for the Lisbon Metropolitan Area

This paper estimates fuel demand models for the Lisbon Metropolitan Area (AML) and uses the demand elasticities obtained to predict future levels of road transport CO₂ greenhouse gas emissions. Data for the municipalities constituting the AML and the period 1993–2010 are analysed using static and dynamic panel data models to measure the relative importance of fuel price, income, vehicle stock, the price of public transport, and the availability of urban and suburban rail networks on fuel demand. To the best of our knowledge, this is the first study in the Portuguese context to produce fuel demand elasticities for a specific metropolitan area, as opposed to the estimation of country-level aggregate elasticities. Our findings indicate that the elasticity of fuel demand with respect to fuel price ranges between −0.48 and −0.72 in the short run and between −1.19 and −1.82 in the long run. Income elasticities are found to range between 0.51 and 0.54 in the short run and between 1.26 and 1.37 in the long run. The elasticity of fuel demand with respect to vehicle stock (keeping population constant) is 0.57 in the short run and 1.43 in the long run. There is only weak evidence of a reduction in fuel demand as a result of a decrease in the price of public transport, and no effect of greater availability of rail networks. Based on the elasticities estimated, we predict road transport CO₂ emissions for the AML according to different macroeconomic scenarios. The results indicate that the emissions target is only achieved in the scenario of poor economic performance. In the presence of medium and strong economic growth, fuel prices would need to increase by about 7% and 11% per year respectively in order to meet the emissions target.