Local transit

This report proposes and evaluates two ideas for improving efficiency and service quality of paratransit operations. For carrying out this analysis, the authors use data from Metro Mobility, the agency responsible for providing ADA-mandated transportation services in the Twin Cities. However, the underlying principles, mathematical models, and algorithms are applicable to a variety of similar transportation operations in urban and rural areas. The first idea is to re-optimize routes developed by Metro Mobility's route-building software (a commercial product named Trapeze) at the end of each day of booking operations to reduce the total time it takes to serve booked trips. The second idea evaluates the selective use of non-dedicated vehicles and service providers (e.g. taxi services) for lowering operational costs. Mathematical models and computer algorithms are developed for each of these approaches. These are then tested on actual operational data obtained from Metro Mobility. The report shows that a conservative estimate of savings from re-optimization would be 5% of Metro Mobility's operating costs. Additional savings from the use of taxi service would be in the hundreds of dollars per day. The actual magnitude of these savings would depend on the proportion of customers who agree to travel by taxi.

The widespread implementation of automated vehicle location systems and automatic passenger counters in the transit industry has opened new venues in transit operations and system monitoring. Metro Transit, the primary transit agency in the Twin Cities, Minnesota region, has been testing various intelligent transportation systems (ITS) since 1999. In 2005, they fully implemented an AVL system and partially implemented an APC system. To date, however, there has been little effort to employ such data to evaluate different aspects of performance. This research capitalizes on the availability of such data to better assess performance issues of one particular route in the Metro Transit system. We employ the archived data from the location systems of buses running on an example cross-town route to conduct a microscopic analysis to understand reasons for performance and reliability issues. We generate a series of analytical models to predict run time, schedule adherence and reliability of the transit route at two scales: the time point segment and the route level. The methodology includes multiple approaches to display ITS data within a GIS environment to allow visual identification of problem areas along routes. The methodology also uses statistical models generated at the time point segment and bus route level of analysis to demonstrate ways of identifying reliability issues and what causes them. The analytical models show that while headways are being maintained, schedule revisions are needed to in order to improve run time. Finally, the analysis suggests that many scheduled stops along this route are underutilized and recommends consolidation them.

The functioning of the system of land use and travel networks in a region can be encapsulated into measures of the ease of reaching destinations from various locations, often referred to as accessibility measures. Regardless of the form used to specify accessibility, all measures require as inputs travel times between the zones of a region. For most transportation planning purposes, these travel time calculations are limited to motorized modes (auto and public transit), since these modes carry the bulk of all urban travel. In this research study, attention is focused on developing methods for calculating travel times by non-auto modes, including walking, bicycling and public transit. Unique networks for each mode are developed, accounting for the presence of special facilities such as pedestrian or bicycle trails and on-street bike lanes. A statistical model is estimated to identify the influence of special bicycle facilities on travel speeds, using GPS data collected from bicyclists in a real-world setting. These methods are demonstrated with an application to a section of the Twin Cities metropolitan region encompassing parts of the cities of Minneapolis, St. Paul and Bloomington. The output of the application of these methods are a set of maps depicting travel sheds from various locations within the study area. The data are displayed for three points in time: 1995, 2000 and 2005. Changes to these travel sheds over time are demonstrated with maps that show the difference in travel time between each set of origins and destinations for each pair of years. The research concludes with some suggestions about the uses of the travel time data, such as the calculation of multimodal, multipurpose measures of accessibility.

"What would it take to build our way out of congestion in the Twin Cities?" was the question posed by researchers five years ago. This previous study solved a roads-only network design problem (NDP) for the Twin Cities of Minnesota. Building on that work, another network design problem is examined for the Twin Cities metropolitan area of 3 million, to examine the tradeoff between demand side reductions and the limited access capacity expansion necessary to achieve desired levels of service. The problem is simplified by pre-determining a mode split, which allows for incorporating decreasing demand directly as an input rather than in the model formulation. The problem is solved using Sequential Linear Expansion (SLIE), a modified method of successive averages (MSA). Computation time for the large network is decreased to a reasonable length using another modification, the MSA with decreasing re-initialization (MSADR). A typical personal computer can solve this large-sized problem within 24 hours. For forecasted travel demand for 2030, it was found that if the number of trips were reduced by 20%, lanemiles needed to achieve LOS D decreases by up to 43%.

In 2003, the State and Local Policy Program (SLPP) at the University of Minnesota's Humphrey Institute of Public Affairs began research into how Intelligent Transportation System (ITS) technologies can be used to deliver transportation services to an increasingly diverse population in Minnesota. The research objective was to identify the nature of the gap between the emerging needs and existing services, and to propose ways of using technology to bridge the gap, both in terms of providing better transportation options and in reducing the cost of these options. Using the information obtained from emerging demographic data, the 2003 study focused on identifying transportation challenges and opportunities for several different populations, with a particular focus on those that do not or cannot drive. This project continues this general theme through a series of analyses of ITS applications that appear most promising to improve mobility and access for Minnesota's increasingly diverse population. These applications include technologically advanced Community-Based Transit, Car Sharing, use of ITS to implement Value Pricing through conversion of an HOV lane to a High-Occupancy/Toll (HOT) lane, and evaluation of web-based Advanced Traveler Information Systems (ATIS).

A burgeoning population seeking relatively affordable housing is placing high demands on outlying, auto-dependent residential markets. Simultaneously, public policies addressing housing, transportation, and land use aim to increase homeownership, decrease drive-alone travel, and harness outlying development. A relatively new mortgage lending procedure aims to address each of these public policy aims synergistically by allowing low- and moderate-income households the opportunity to purchase homes in transit-accessible neighborhoods that would otherwise be unobtainable because of cost. The goal of this research is to evaluate this initiative, as well as position it within the broader goals of smart growth, describe its application, and comment on its prospects. This report constitutes a primer of the current state of knowledge about these unique loan programs.