Demand management in suburban settings

This paper provides findings from a review of employer based demand management strategies for reducing traffic congestion in several areas of the United States. The research was carried out by K.T. Analytics, Inc. in 1989 under a contract with the Federal Department of Transportation, Transportation Systems Center. Relying on a review of employer based programs in 26 sites, as well as selected literature, the paper draws conclusions about the effectiveness of employer based transportation systems management (programs to encourage carpooling, transit, biking, cycling, walking and flextime) and parking management (preferential parking for carpoolers, removal of parking subsidies, and other measures) aimed at reducing solo driving and peak period commuting.Several conclusions are offered for local planners and policy makers. Demand Management programs can be effective in reducing traffic congestion, provided they are targeted to larger employment centers, accompanied by transit development, high occupancy vehicle incentives and parking management strategies, especially pricing. Flextime should not be encouraged without careful evaluation as it may discourage ridesharing. Guaranteed ride home services appear promising and deserve attention. With all strategies, long term vigilance will be necessary as programs are susceptible to change over time. Stringent public policies do not appear necessary for development of effective programs. Ordinances should require plans not specific strategies, as it is difficult estimating the probable effectiveness of particular strategies. Ordinances should contain sanctions for employers not carrying out agreed to plans, and should include fees and financing to support public sector review of plans and on-going monitoring.     

Integrating parking behaviour in activity-based travel demand modelling: Investigation of the relationship between parking type choice and activity scheduling process

Traditionally, the parking choice/option is considered to be an important factor in only in the mode choice component of a four-stage travel demand modelling system. However, travel demand modelling has been undergoing a paradigm shift from the traditional trip-based approach to an activity-based approach. The activity-based approach is intended to capture the influences of different policy variables at various stages of activity-travel decision making processes. Parking is a key policy variable that captures land use and transportation interactions in urban areas. It is important that the influences of parking choice on activity scheduling behaviour be identified fully. This paper investigates this issue using a sample data set collected in Montreal, Canada. Parking type choice and activity scheduling decision (start time choice) are modelled jointly in order to identify the effects of parking type choice on activity scheduling behaviour. Empirical investigation gives strong evidence that parking type choice influences activity scheduling process. The empirical findings of this investigation challenge the validity of the traditional conception which considers parking choice as exogenous variable only in the mode choice component of travel demand models.     

Stochastic optimization approach for the car placement problem in ridesharing systems

With the increasing fuel prices and the pressure towards greener modes of transportation, ridesharing has emerged as an alternative to private car ownership and public transportation. In this paper, we focus on a common destination ridesharing system which is of interest in large organizations such as companies and government offices. Particularly, such organizations are looking at using company owned vehicles to offer a ridesharing service by which employees carpool to work thus leading to several benefits that include decreasing pressure on on-campus parking spaces, lowering localized on-campus congestion, in addition to offering a greener transportation mode while lowering transportation costs for employees. Based on discussions with our industry partners, optimizing the distribution of limited number of company vehicles while insuring robustness against unlikely vehicle unavailability is of critical importance. Thus in this paper, we present a stochastic mixed integer programming model to optimize the allocation of shared vehicles to employees while taking into account the unforeseen event of vehicle unavailability which would require some participants to take own vehicles or rerouting of existing vehicles. Since solving the proposed model to optimality is computationally challenging for problems of large sizes, we also propose a heuristic that is capable of finding good quality solutions in limited computational time. The proposed model and heuristic are tested on several instances of varying sizes showing the computational performance. Finally, a test case based on the city of Rome, Italy is presented and insights related to vehicle distribution and travel time savings are discussed.     

Campus parking supply impacts on transportation mode choice

Parking demand is a significant land-use problem in campus planning. The parking policies of universities and large corporations with facilities located in small urban areas shape the character of their campuses. These facilities will benefit from a simplified methodology to study the effects of parking availability on transportation mode mix and impacts on recruitment and staffing policies. This paper, based on a case study of North Dakota State University in the United States, introduces an analytical framework to provide planners with insights about how parking supply and demand affects campus transportation mode choice. The methodology relies only on aggregate mode choice data for the special generator zone and the average aggregate volume/capacity ratio projections for all external routes that access the zone. This reduced data requirement significantly lowers analysis cost and obviates the need for specialized modelling software and spatial network analysis tools. Results illustrate that the framework is effective for analysing mode choice changes under different scenarios of parking supply and population growth.     

Raising commuter parking prices — An empirical study

Recently, management of parking rates has been proposed as an effective policy option to ameliorate the adverse impacts of excessive commuter automobile use in urban areas. Parking price strategies have the potential for significantly altering travel behavior in favor of high occupancy vehicles, as well as reducing congestion, energy consumption and pollution. Unfortunately, however, a paucity of empirical evidence exists regarding the impacts of parking pricing policies on travel patterns. The recent attempt aimed at eliminating federal employee parking subsidies provided a unique opportunity to take a careful look at the impacts of commuter parking price increases.In November 1979, federal employees at many government facilities in Washington, DC, and other major cities began to pay one-half of nearby commercial parking rates for government-controlled parking spaces. This paper presents the impacts of the parking price increases on commuting behavior at a sample of 15 worksites in metropolitan Washington, DC, and discusses their short term planning and policy implications. A before and after with control group survey design monitored the effects on modal shifts, automobile occupancy, and parking behavior. The results showed that removing free parking and raising parking rates (from $10 to $32 per month) influenced some significant shifts to higher-occupancy modes, but that the shifts were not uniform in direction or magnitude across the sites. In addition, the study examined how locational, travel, and employee factors influenced the modal shifts.     

Distributed work and travel behaviour: The dynamics of interactive agency choices between employers and employees

This paper develops a framework within which multiple agents make discrete choices in respect of a common objective – the determination of participation in distributed work, especially the opportunities and constraints associated with telecommuting. Ideas in discrete choice theory and game theory are combined to define a set of choice experiments in which employees and employers interact in arriving at a choice path in a distributed work context. A state choice experiment with offers and feedback, known as an interactive agency choice experiment (IACE), is empirically investigated in the context of telecommuting options with an exploratory sample of employees and employers in Sydney, Australia. The approach highlights the role of information and negotiation in breaking down the barriers to more flexible work activity, to deliver potential benefits to the transport system such as reduced traffic congestion and environmental sustainability. The paper identifies the types of incentives that an employee/er has to offer the employer/employee in securing effective telecommuting. This revised version was published online in June 2006 with corrections to the Cover Date.     

Parking policies in large cities in Germany

This article deals with highly motorized large West German cities of about 200,000 inhabitants and more, which usually provide reasonable public transport systems. Illegal parking with shares of about 40 to 50% of the total parking is widespread in the parking problem areas of those cities, especially in the inner-city residential and mixed-use areas. Parking spaces are demanded by residents, employees, customers and visitors, and by delivery and service traffic. The different characteristics of parking demands by different user groups are discussed. The total parking supply consists of public and private spaces. The share of private spaces is about 40 to 50% of the total parking spaces in German cities. The amount of car traffic generated by a parking space depends on parking duration and parking turnover, as well as on search traffic. So the change of a space from long-duration use of an employee to short-duration of customers — as often discussed in parking concepts — generates at least five-fold car traffic. The measurements and effects of parking control of public spaces as well as the parking regulations in zoning ordinances, restrictions on the construction of new private parking spaces and park-and-ride are discussed. Finally, a parking concept methodology — using the example of Frankfurt am Main — is discussed.     

Flexible parking requirements for office developments: New support for public parking and ridesharing

The author examines new, flexible parking requirements in several U.S. cities and Canada. Flexible requirements provide relaxations in zoning code specifications for off-street parking in return for developer commitments to ridesharing measures, support of transit or in-lieu fees for public parking. Issues examined include whether developers take advantage of flexible requirements, whether agreements with developers lead to agreed-upon action, and whether actions lead to desired results. Based on experiences of several cities, implications and cautions are drawn for local planners. The first caution relates to cities using flexible requirements to collect in-lieu fees in support of public parking. Where cities delay providing parking, inflation may make it difficult to provide the desired parking supply. Or, developers may not choose to pay the fee, such as in the case where cities grant relaxations for other measures more attractive than paying the fees.Other implications relate to flexible requirements in support of ridesharing or transit. Developers will not necessarily take advantage of relaxations tied to support of these modes. Generally, developers will take the least-cost ways to gain relaxations. They may choose to provide the parking where transit or ridesharing measures are too costly or complex. Or, they may take relaxations easier to obtain than those for ridesharing and transit. Finally, even where developers do agree to ridesharing measures, the measures may not be effective. On the other hand, developer-sponsored actions have proven effective in some cities where tight or expensive parking prevails, or where neighborhood residents have organized against office commuters parking on neighborhood streets, or where other economic or community variables favor ridesharing and transit.     

A modeling approach for matching ridesharing trips within macroscopic travel demand models

State of the art travel demand models for urban areas typically distinguish four or five main modes: walking, cycling, public transport and car. The mode car can be further split into car-driver and car-passenger. As the importance of ridesharing may increase in the coming years, ridesharing should be addressed as an additional sub or main mode in travel demand modeling. This requires an algorithm for matching the trips of suppliers (typically car drivers) and demanders (travelers of non-car modes). The paper presents a matching algorithm, which can be integrated in existing travel demand models. The algorithm works likewise with integer demand, which is typical for agent-based microscopic models, and with non-integer demand occurring in travel demand matrices of a macroscopic model. The algorithm compares two path sets of suppliers and demanders. The representation of a path in the road network is reduced from a sequence of links to a sequence of zones. The zones act as a buffer along the path, where demanders can be picked up. The travel demand model of the Stuttgart Region serves as an application example. The study estimates that the entire travel demand of all motorized modes in the Stuttgart Region could be transported by 7% of the current car fleet with 65% of the current vehicle distance traveled, if all travelers were willing to either use ridesharing vehicles with 6 seats or traditional rail.     

An analysis of university employee car-sharers in Los Angeles

This paper analyzes personal and car-sharing characteristics of commuters at university in Los Angeles, California. These commuters do not hold an on-campus parking permit and commute by an alternative mode other than driving alone. Each month, the university offers them 8 h free use of shared vehicles across the campus. University employee car-sharers’ housing distribution is significantly different from that of their counterparts who drive to work. Commuter benefits influence not only the participation rate of a car-sharing program but also the program participants’ frequency, time and quantity of car-sharing consumption. Car-sharing is most popular among bus commuters, university students and female employees.     

Parking policy and urban goals: Linking strategy to needs

Parking management strategies have traditionally been used as a means of accommodating traffic demand, with little or no effort made to identify how such strategies might relate to other urban objectives. In this paper, parking management strategies are classified according to the control they exert over the amount of aggregate parking supply, access to parking, spatial distribution of parking supply, or dollar price of parking. Six general categories of urban policy objectives are identified, and the relationship between parking strategies and these objectives analyzed. The parking program in Baltimore is used to illustrate some of the relationships identified in this analysis. This paper concludes that the linkage between parking and the attainment of some urban objectives is potentially quite strong, and that further empirical research is needed to fully establish this relationship. Several different directions for further research are also identified.     

Ridesharing in North America: Past,Present, and Future

Since the late 1990s, numerous ridematching programmes have integrated the Internet, mobile phones, and social networking into their services. Online ridematching systems are employing a range of new strategies to create “critical mass”: (1) regional and large employer partnerships, (2) financial incentives, (3) social networking to younger populations, and (4) real-time ridematching services that employ “smartphones” and automated ridematching software. Enhanced casual carpooling approaches, which focus on “meeting places”, are also being explored. Today, ridesharing represents approximately 8–11% of the transportation modal share in Canada and the USA, respectively. There are approximately 638 ridematching programmes in North America. Ridesharing's evolution can be categorized into five phases: (1) World War II car-sharing (or carpooling) clubs; (2) major responses to the 1970s energy crises; (3) early organized ridesharing schemes; (4) reliable ridesharing systems; and (5) technology-enabled ridematching. While ridesharing's future growth and direction are uncertain, the next decade is likely to include greater interoperability among services, technology integration, and stronger policy support. In light of growing concerns about climate change, congestion, and oil dependency, more research is needed to better understand ridesharing's impacts on infrastructure, congestion, and energy/emissions.     

Commuting-related fringe benefits in the Netherlands: Interrelationships and company,employee and location characteristics

Mobility management measures taken by firms could potentially result in more sustainable transport choices and hence reduce traffic congestion and emissions. Fringe benefits offered to employees are a means to implement those measures. This paper explores the most common commuting-related fringe benefits currently provided by employers in the Netherlands, namely telework, flextime and allowance types like public transport passes, bicycle contribution, company cars and general financial compensation. By using the Dutch National Time Use Survey (TBO) 2005/2006, interrelationships among fringe benefits and correlations between company, employee, and (home and work) location characteristics and those employee benefits could be investigated. Logistic regressions and Tobit models are used for several estimations indicating the provision and the use of fringe benefits. The results show that relationships among fringe benefits exist, mainly between telework and flextime, but also between those flexible work arrangements and some types of commuting allowance. Furthermore, numerous job, person and geographical variables affect the probability of receiving and using the fringe benefits. For example, in the non-profit and the public sector sustainable commuting benefits are more often provided, the use of fringe benefits is strongly influenced by household composition and several allowance types show a significant correlation with the number of cars in the household. Moreover, firm location, in particular firm density, is highly related to mobility management measures taken by firms.     

Evaluating employer programs encouraging the use of alternate transportation modes: Two studies

Since 1976, major Denver metropolitan area firms have been required to encourage employees to use mass transit, carpooling, bicycling, and other alternate transportation modes to commute to work. The encouragement programs of 36 firms were clearly associated with greater use of alternate transportation modes, with the portion of variance in alternate transportation use explained by differences in employer programs of approximately 15%. The effects of the programs on deterring alternate mode users from returning to solo driving are consistently weaker than their effects on persuading drivers to try alternate transportation modes initially. Recommendations for the conduct of alternate transportation encouragement programs are made, based on these and other results. In addition, two recommendations are made concerning the evaluation of encouragement programs: that aggregate percentage change in alternate transportation use should not be used as the sole measure of success, and that environmental variables such as the availability of and pressure for use of alternate transportation modes should be measured and controlled.     

Decisions on truck parking place and time on expressways: an analysis using digital tachograph data

With the objective of deriving useful insights into measures against traffic congestion at service areas (SAs) and parking areas (PAs) on expressways and ensuring efficient use of SAs/PAs, this study investigated the decisions on where a truck is parked (i.e., choice of an SA or a PA), how long it is parked (i.e., parking time), and their influential factors. To this end, this study used the trajectory data of 1600 trucks recorded in 6-min intervals by in-vehicle digital tachographs on the Sanyo and Chugoku Expressways in Japan from October 2013 to March 2014. First, the aspect of repeated choice of each truck (i.e., habitual behavior) toward a specific SA/PA was clarified. Next, a multilevel discrete–continuous model (Type II Tobit model) was developed to reveal the factors affecting the above decisions. The modeling results confirmed the existence of habitual behavior and showed that trucks were more likely to be parked a longer time at an SA/PA when it is closer to the destination. It appears that truck drivers may adjust their time at the SA/PA close to the destination to comply with the arrival time, which is often predetermined by the owner of the transported goods. Furthermore, the availability of restaurants and shops, and the number of parking spaces available for trucks and trailers are important determinants of parking time, whereas the existence of a convenience store is important to the choice of the SA/PA. Parking experience has an extremely strong positive effect on the parking choice and use. Moreover, increasing the number of parking lots may induce its longer use.

     

Choice of parking: Stated preference approach

Over recent years, parking policy has become a key element of transport policy in many countries. Parking policy measures can affect many different dimensions of travel behaviour but are likely to be most significant in terms of travellers' choice of parking type and location. This dimension of travel choice has, to date, received comparatively little attention, yet is of vital importance if we are to properly understand and predict the effects of parking policy measures.This paper presents two studies addressing this issue carried out in the United Kingdom and Germany. Both studies used a stated preference approach in order to collect disaggregate data on travellers responses to changes in parking attributes and used these data to build simple logit models of parking type choice. The studies were designed in order to allow comparable choice models to be estimated from the two datasets. The results obtained strongly indicate the need to separately identify the costs associated with different components of the parking activity (e.g., general in-vehicle time, parking search time, egress time) and also point to the existence of significant differences in the relative valuation of these components across different journey purposes. Where possible, the results of the choice modelling exercises are also compared with existing revealed and stated preference results and are found to be generally in line with prior expectations.     

A traffic assignment model for a ridesharing transportation market

A nascent ridesharing industry is being enabled by new communication technologies and motivated by the many possible benefits, such as reduction in travel cost, pollution, and congestion. Understanding the complex relations between ridesharing and traffic congestion is a critical step in the evaluation of a ridesharing enterprise or of the convenience of regulatory policies or incentives to promote ridesharing. In this work, we propose a new traffic assignment model that explicitly represents ridesharing as a mode of transportation. The objective is to analyze how ridesharing impacts traffic congestion, how people can be motivated to participate in ridesharing, and, conversely, how congestion influences ridesharing, including ridesharing prices and the number of drivers and passengers. This model is built by combining a ridesharing market model with a classic elastic demand Wardrop traffic equilibrium model. Our computational results show that (i) the ridesharing base price influences the congestion level, (ii) within a certain price range, an increase in price may reduce the traffic congestion, and (iii) the utilization of ridesharing increases as the congestion increases. Copyright © 2014 John Wiley & Sons, Ltd.     

Meeting points in ridesharing: A privacy-preserving approach

Nowadays, problems of congestion in urban areas due to the massive usage of cars, last-minute travel needs and progress in information and communication technologies have fostered the rise of new transportation modes such as ridesharing. In a ridesharing service, a car owner shares empty seats of his car with other travelers. Recent ridesharing approaches help to identify interesting meeting points to improve the efficiency of the ridesharing service (i.e., the best pick-up and drop-off points so that the travel cost is competitive for both driver and rider). In particular, ridesharing services, such as Blablacar or Carma, have become a good mobility alternative for users in their daily life. However, this success has come at the cost of user privacy. Indeed in current’s ridesharing services, users are not in control of their own data and have to trust the ridesharing operators with the management of their data.In this paper, we aim at developing a privacy-preserving service to compute meeting points in ridesharing, such that each user remains in control of his location data. More precisely, we propose a decentralized architecture that provides strong security and privacy guarantees without sacrificing the usability of ridesharing services. In particular, our approach protects the privacy of location data of users. Following the privacy-by-design principle, we have integrated existing privacy enhancing technologies and multimodal shortest path algorithms to privately compute mutually interesting meeting points for both drivers and riders in ridesharing. In addition, we have built a prototype implementation of the proposed approach. The experiments, conducted on a real transportation network, have demonstrated that it is possible to reach a trade-off in which both the privacy and utility levels are satisfactory.     

The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste,Italy

Universities, like other types of public and private institutions, when located in a city, have both positive and negative impacts on the area where they are situated. On the one hand, they contribute to the prestige of the area; on the other hand, they are large generators/attractors of traffic. The ability to successfully balance the pros and cons of the urban location of these large traffic-generating institutions is crucial for their success and for the livability of the city. In this paper this issue has been analyzed selecting as a representative case the University of Trieste.The aim of the research is to understand: (a) how mode choice decisions are made by the teaching and administrative staff and by the students at the various locations where academic activities take place, and (b) how they would be affected by 8 different transport management policies. It is found that changing the parking regulations (via the annual permit cost, the hourly parking fee, the number of parking spaces and the location of the parking lots) greatly influences mode choice in favor of bus use, especially for teaching and administrative staff and in the suburban locations. The students would be impacted by such changes only if an hourly parking tariff is introduced. The alternative approach of fully subsidizing the bus services would also have a large impact on bus ridership, affecting the mode choice in particular of the teaching staff and in the main university suburban sites.Since the implementation of these bus-favoring policies could face the opposition either of the university staff or of the bus company, two more balanced policy mixes were tested: the first one, increasing parking price and imposing new parking restrictions, would increase bus ridership by 19%; the second one, reducing both bus and parking subsidies, would increase bus ridership by 13%.     

Determinants of bicycle commuting in the Washington,DC region: The role of bicycle parking,cyclist showers,and free car parking at work

This article examines the role of bicycle parking, cyclist showers, free car parking and transit benefits as determinants of cycling to work. The analysis is based on commute data of workers in the Washington, DC area. Results of rare events logistic regressions indicate that bicycle parking and cyclist showers are related to higher levels of bicycle commuting—even when controlling for other explanatory variables. The odds for cycling to work are greater for employees with access to both cyclist showers and bike parking at work compared to those with just bike parking, but no showers at work. Free car parking at work is associated with 70% smaller odds for bike commuting. Employer provided transit commuter benefits appear to be unrelated to bike commuting. Regression coefficients for control variables have expected signs, but not all are statistically significant.