Robert Cornelius Hampshire

University of Michigan | U-M · Transportation Research Institute

In many different settings, requests for service can arrive in near or true simultaneity with one another. This creates batches of arrivals to the underlying queueing system. In this paper, we study the staffing problem for the batch arrival queue. We show that batches place a dangerous and deceptive stress on services, requiring a high amount of r...

The worldwide outbreak of the coronavirus was first identified in 2019 in Wuhan, China. Since then, the disease has spread worldwide. As it is currently spreading in the United States, policy makers, public health officials and citizens are racing to understand the impact of this virus on the United States healthcare system. They fear a rapid influ...

We develop new techniques involving group symmetries and complex analysis to obtain exact solutions for the transition probabilities of the M/M/1/k queueing process. These methods are based on the underlying Markovian structure of these random processes and do not involve any generating functions, Laplace transforms, or advanced special functions....

The Erlang A model--an M/M/s queue with exponential abandonment--is often used to represent a service system with impatient customers. For this system, the popular square-root staffing rule determines the necessary staffing level to achieve the desirable QED (quality-and-efficiency-driven) service regime; however, the rule also implies that propert...

We analyze GPS traces of 5,316 trips that are cruising for parking in San Francisco and Ann Arbor, and use cluster analysis to develop a typology of five distinct types of search strategy. Our most striking finding is that most cruising trips do not involve circling. Partly because most drivers are able to find a space relatively quickly, a more ty...

The excessive search for parking, known as cruising, generates pollution and congestion. Cities are looking for approaches that will reduce the negative impact associated with searching for parking. However, adequately measuring the number of vehicles in search of parking is difficult and requires sensing technologies. In this paper, we develop an...

Mobility-on-Demand Transit (MoDT) is a suitable solution for linking packed urban centers to low-demand suburban areas. Meanwhile, micromobility services, including dockless bikesharing and electric scooters, are growing exponentially worldwide, providing a low-cost, low-emission travel mode for short home-based trips. We propose an intermodal netw...

The COVID-19 pandemic has exposed some of the underlying inequities in our society. Vulnerable and low-income communities who have typically struggled with food insecurity have been further impacted by the COVID-19 pandemic. To make matters worse, transit dependent households in the City of Detroit that rely on SNAP benefits from the government hav...

This paper presents a method for determining parking search behavior using GPS traces. The research takes advantage of a GPS based household travel survey, an extensive dataset of GPS with video, and a commercially purchased set of trip segments. Strategies for data cleaning, matching traces to digitized networks, assessing the probability that a t...

Using publicly available microdata sets, we show how estimates for online delivery purchases can be generated for small geographic areas defined in our study as micro analysis zones (MAZ) and how these estimates vary across the MAZs that featured in our study. With a focus on Miami-Dade County, we use both the national household travel survey (NHTS...

By adopting and extending lessons from the air traffic control system, we argue that a nationwide remote monitoring system for driverless vehicles could increase safety dramatically, speed these vehicles’ deployment, and provide employment. It is becoming clear that fully driverless vehicles will not be able to handle “edge” cases in the near futur...

The worldwide outbreak of the coronavirus was first identified in 2019 in Wuhan, China. Since then, the disease has spread worldwide. As it currently spreading in the United States, policy makers, public health officials and citizens are racing to understand the impact of this virus on the United States healthcare system. They fear that the rapid i...

Vacant taxi drivers’ passenger seeking process in a road network generates additional vehicle miles traveled, adding congestion and pollution into the road network and the environment. This paper aims to employ a Markov Decision Process (MDP) to model idle e-hailing drivers’ optimal sequential decisions in passenger-seeking. Transportation network...

Cruising for parking has long been perceived as a major source of congestion and emissions in urban areas, but recent empirical work suggests that parking may not be as onerous as folklore suggests, and that the amount of vehicle travel attributable to cruising is minimal. In this paper, we reconcile these perspectives through a dynamic programming...

We develop a more nuanced understanding of commuters’ travel mode choices by generating detailed profiles that capture the travel behavior of commuters in the Pacific states of the continental US. These profiles are created by utilizing the US Census Public Use Microdata Sample (PUMS) data. The microdata sample set allows for the estimation of fine...

Driverless vehicles promise a host of societal benefits including dramatically improved safety, increased accessibility, greater productivity, and higher quality of life. As this new technology approaches widespread deployment, both industry and government are making provisions for teleoperations systems in which remote human agents provide assista...

Global Positioning System (GPS) data have become ubiquitous in many areas of transportation planning and research. The usefulness of GPS data often depends on the points being matched to the true sequence of edges on the underlying street network – a process known as ‘map matching.’ This paper presents a new map-matching algorithm that is designed...

Vacant taxi drivers' passenger seeking process in a road network generates additional vehicle miles traveled, adding congestion and pollution into the road network and the environment. This paper aims to employ a Markov Decision Process (MDP) to model idle e-hailing drivers' optimal sequential decisions in passenger-seeking. Transportation network...

In May 2016, Uber and Lyft suspended services following the defeat of Proposition 1 in Austin, TX. In response, several ridesourcing services entered the market. This paper provides information on the individuals most likely to switch back to Uber or Lyft after service restoration using estimated indifference bands. We hypothesize that people will...

Markov chain (MC) decomposition methods comprise two main steps: (1) a procedure to decompose the full MC, and (2) a procedure to aggregate the solutions of decomposed subsets. While a variety of unique techniques have been applied to accomplish the first step, a normalization procedure is almost always used in the second step. The normalization do...

We propose a new way to measure the share of traffic that is cruising for parking: observe how many cars pass a newly vacated space before a driver parks in it. This statistical method provides a quick, cheap and approximate way to estimate what share of traffic is cruising. Using 876 observations of newly vacated on-street parking spaces in centra...

This guide describes scalable risk assessment methods for pedestrians and bicyclists, wherein risk is a measure of the probability of a crash to occur given exposure to potential crash events. This guide outlines eight sequential steps to develop risk values at various desired geographic scales, and describes the scope and nature of each step, incl...

Predicting the drivers movement in a spatial network accurately and promptly is essential for the ride dispatching and dynamic pricing algorithms for ride-hailing services. In this paper, we construct a data-driven model based on recurrent neural networks. We test the performance of our model using real-world trajectory database and the result (74...

This paper demonstrates a unique and promising approach to study driver-bicyclist interactions from a driver's perspective by using in-vehicle sensory data from naturalistic driving studies. A total of 4789 events of drivers overtaking bicyclists were extracted from an existing naturalistic driving study in Michigan, United States. The vehicle late...

In an effort to reduce circling and cruising in cities’ central business districts (CBDs), a number of cities have begun implementing pricing programs that modify parking rates based on observed occupancy levels. We improve on this pricing mechanism by developing a forward-looking policy instrument. The instrument employs a two-stage panel data reg...

Multimodal transportation systems are the foundation for mobility-as-a-service. Ride-hailing and bikesharing are complementary modes of transport because the latter one serves long-distance trips and the latter one is suitable for first-last-mile trips. Regarding transport supply, the popularity of dockless bikeshare nowadays can also fulfill exces...

Using the United States Census Public Use Microdata Sample (PUMS) dataset, we documented the severity of the disparity in commuting pattern across the contiguous US. The analysis was complemented by a more granular analysis with the Greater Pittsburgh area as the geographic area of focus. In addition to the locational variation in travel mode obtai...

Over 400 cities around the world have deployed or have plans to deploy a bike sharing system. However, the factors that drive their usage and the amount of rebalancing they require are not known precisely. A knowledge of these factors would allow cities to design or modify their systems to increase usage while lowering rebalancing costs. We collect...

This report summarizes the variety of methods used to estimate and evaluate exposure to risk in pedestrian and bicyclist safety analyses. In the literature, the most common definition of risk was a measure of the probability of a crash to occur given exposure to potential crash events. There was also consensus on a theoretical definition of exposur...

The number of cars searching for parking, also known as “cruising,” is a risk factor linked to increased pollution and congestion and decreased road safety. Although the detrimental effects of cruising are known, the actual amount of cruising is unknown. A novel video data set of naturalistic driving is shown to provide reliable estimates of cruisi...

Real-time parking occupancy information is critical for a parking management system to facilitate drivers to park more efficiently. Recent advances in connected and automated vehicle technologies enable sensor-equipped cars (probe cars) to detect and broadcast available parking spaces when driving through parking lots. In this paper, we evaluate th...

Real-time parking occupancy information is valuable for guiding drivers' searching for parking spaces. However, in previous practice, data acquisition requires costly infrastructure upgrades especially including installing cameras or sensors on site. In this paper, we proposed a Sensor-based Intelligent Parking System (SIPS) which is able to detect...

Advanced Driver Assistance System (ADAS) have been developed and implemented in the market as a type of new automobile technology in recent years. We are interested in predicting its market share in the next decade with very limited information, which means Time series analysis will fail. Bass Diffusion Model is a well-studied growth model proposed...

To better guide drivers to parking, real-time parking occupancy data is critical. One solution we proposed and tested is leveraging on the sensors embedded in Advanced Driver Assistance Systems (ADAS) and collect information when cars are driving through a parking lot or passing by on-street parking. In order to predict the penetration of sensors e...

Over 400 cities around the world have deployed or have plans to deploy a bike sharing system. However, the factors that drive their usage and the amount of rebalancing they require are not known precisely. A knowledge of these factors would allow cities to design or modify their systems to increase usage while lower rebalancing costs. We collect st...

(Presentation on Youtube) https://www.youtube.com/watch?v=PTuTB3G2yVk&feature=youtu.be The city of San Francisco is undertaking a large-scale controlled parking pricing experiment. San Francisco has adopted a performance goal of 60–80% occupancy for its metered parking. The goal represents an heuristic performance measure intended to reduce double...

ParkPGH is a novel parking application that provides real-time and predictive information on the availability of garage parking spaces within Pittsburgh’s Cultural District. The core of the application is a module that collects real-time parking information from the garages by tapping into their gate counts. The real-time component is complemented...

The city of San Francisco is undertaking a large-scale controlled parking pricing experiment. San Francisco has adopted a performance goal of 60–80% occupancy for its metered parking. The goal represents an heuristic performance measure intended to reduce double parking and cruising for parking, and improve the driver experience; it follows a wave...

This paper documents the methodological approach and findings of an evaluation process for a smart parking application that provides real-time information on parking availability. The initiative is in response to the increased demand for parking spaces in the Pittsburgh, Pennsylvania, Cultural District and the desire to improve patrons' parking exp...

Adam Millard-Ball, Rachel Weinberger, and Robert Hampshire critically comment on Pierce and Shoup's article 'Evaluating the Impacts of Performance-Based Parking'. In principle, a performance-based parking system such as SFpark, which adjusts prices in a bid to achieve target occupancy for curb parking, is an excellent way to reduce congestion and t...

Bike sharing systems have been installed in many cities around the world and are increasing in popularity. A major operational cost driver in these systems is rebalancing the bikes over time such that the appropriate number of bikes and open docks are available to users. We combine two aspects that have previously been handled separately in the lit...

A quantitative analysis of the pioneering large-scale bicycle sharing system, Vélib' in Paris, France is presented. This system involves a fleet of bicycles strategically located across the network. Users are free to check out a bicycle from close to their origin and drop it off close to their destination to complete their trip. The analysis provid...

Many studies show that carsharing reduces transportation costs for a large segment of the population. Carsharing also reduces the number of private vehicles on the road because carshare members do not purchase their own cars. However, the traditional carsharing business model is difficult to scale geographically to neighborhoods with lower populati...

Many studies have shown that carsharing reduces environmental pollution and the transportation costs for a large segment of the population. Car sharing also reduces the number of private vehicles on the road because members do not purchase their own car. However, the traditional carsharing business model is difficult to scale geographically to neig...

Person-to-Person (P2P) car sharing allows car owners to convert their personal vehicles into share cars which can be rented to other drivers on a short-term basis. Using data from the Longitudinal Employment Dynamics (LED) program and the US Census, we develop a methodology to assess the market feasibility of, and economic incentives, P2P car shari...

This tutorial presents recent developments in the management of communications services and applies broadly to services involving the leasing of shared resources. These problems are more realistically modeled by queues with time-varying rates or more simply, dynamic rate queues. We first provide a review and summary of relevant results for various...

Online peer-to-peer (P2P) lending organizations enable an individual to obtain an unsecured loan from a collection of individuals without the participation of a bank. Previous research has addressed the use of reputation systems to reduce information asymmetry based on individual history within online markets. Within the last few years one of the m...

In this note we identify a phenomenon for processor sharing queues that is unique to ones with time-varying rates. This property was discovered while correcting a proof in Hampshire, Harchol-Balter and Massey (5). If the arrival rate for processor sharing queue has unbounded growth over time, then it is possible for the number of customers in a pro...

Numerous examples of real time services arise in the service industry that can be modeled as loss systems. These include agent staffing for call centers, provisioning bandwidth for private line services, making rooms available for hotel reservations and congestion pricing for parking spaces. Given that arriving customers make their deci-sion to joi...

We consider a multiserver delay queue with finite additional waiting spaces and time-varying arrival rates, where the customers waiting in the buffer may abandon. These are features that arise naturally from the study of service systems such as call centers. Moreover, we assume rewards for successful service completions and cost rates for service r...

Person-to-person lending (P2PL) on the Internet is a relatively new credit market. The success of these markets hinges on their ability to provide both borrowers and lenders the chance to improve on the opportunities available in traditional intermediated credit markets. In essence, P2PL must create a more competitive market. Empirical observations...

We provide an approximate analysis of the transient sojourn time for a processor sharing queue with time varying arrival and service rates, where the load can vary over time, including periods of overload. Using the same asymptotic technique as uniform acceleration as demonstrated in [12] and [13], we obtain fluid and diffusion limits for the sojou...

According to Koole and Mandelbauin (2001), almost 60 to 70 percent of the total costs for operating a call center involve wage and benefit expenses for personnel. It follows that determining the optimal amount of call center agents is of great interest to call center managers. This paper addresses both the staffing of agents and the provisioning of...

Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g. , pa...

Customers of bandwidth services can be divided into two distinct groups: those customers requesting bandwidth for the future and those desiring bandwidth im-mediately. We develop a dynamic network provisioning methodology that mini-mally satisfies the QoS (blocking probability) requirements for the 'on-demand' customers. Our method is sufficiently...

We develop a dynamic network provisioning methodology that minimally satisfies the QoS (blocking probability) requirements for the 'on-demand' customers. Our method is sufficiently general and captures time varying trends in the demand for services as well as different bandwidth requests for the multiple classes of customers. This allows a network...

rest areunchanged. This allows us to construct our multi-class optimization solution in terms of the simplermethods applied to the Erlang loss model for an individual class.References