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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Development of Demand Estimation Models for the Virginia Department of Transportation’s Park and Ride Facilities</title>
      <link>https://trid.trb.org/View/1860948</link>
      <description><![CDATA[The construction and maintenance of park and ride lots represents a substantial public investment that if used judiciously can reduce congestion and emissions through the use of transit or the sharing of vehicle trips. With 297 lots scattered throughout Virginia, the Virginia Department of Transportation (VDOT) needs an approach for forecasting demand for these lots so that investments can be made wisely. Unfortunately, direct application of an existing approach yielded absolute differences (between forecast occupancy and observed occupancy) that depending on the VDOT district were 14 to 141 times larger than the observed occupancy. Calibrating an existing approach to Virginia-specific traffic volumes for the roadway serving the lot and the highest volume roadway within 2.5 miles of the lot reduced the scale of this error but still yielded forecasts where the mean testing error exceeded the mean occupancy for a majority of models. Accordingly, 19 Virginia-specific models were developed that reflected distinct regions in Virginia. These models followed VDOT district boundaries for three of VDOT’s nine districts (Lynchburg, Richmond, and Northern Virginia); planning district commission (PDC) or metropolitan planning organization (MPO) boundaries for four VDOT districts (Bristol, Culpeper, Salem, and Staunton); and urban/rural categorizations for two VDOT districts (Fredericksburg and Hampton Roads). A key finding was that determinants of occupancy varied by location. Statistically significant determinants included residents with a commute of 50+ miles (used in four models affecting 10% of Virginia’s lots, such as those in the Lenowisco PDC in the Bristol District); the availability of transit service or the number of commuters who choose transit (used as a positive factor in seven models affecting more than one-half [151] of Virginia’s lots, such as those in the urbanized portion of the Culpeper District); amenities such as lighting (a variable in two models reflecting 15% of Virginia’s lots such as those in the low population density areas of the Fredericksburg District); traffic volume (a factor in five models representing 46% of Virginia’s lots, such as those in the Lynchburg District); and the provision of bicycle spaces (a factor in the model for 78 of the Northern Virginia District lots, or about 26% of the statewide total). Thus, the models can help forecast how key changes (such as an increase in traffic, the introduction of transit service, or the addition of lighting) may influence demand at an existing lot. The median-adjusted R-squared value (coefficient of determination) for the 19 models was 87%. The Richmond District was representative: a model based on the average 24-hour traffic volume of all facilities within 2.5 miles of the lot and the nearest peak hour expansion factor explained 86.7% of the variation in occupancy for the 11 lots in that district. When the models were tested on a dataset not used to build the models, the median ratio of mean testing error to mean occupancy was 56%. A typical model in this regard was for the lots in the Roanoke Valley-Alleghany Regional Commission (in the Salem District) where occupancy was based on the presence of transit service and the proportion of nearby residents with commutes of 25 to 50 miles: the mean testing error was 14 compared to a mean lot occupancy of 25, for a ratio of 56%. The models thus explained a portion of the variation in demand and can inform forecasts for new lots, although these results demonstrated that additional site-specific factors not included in each model also influenced demand.]]></description>
      <pubDate>Mon, 26 Jul 2021 17:59:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/1860948</guid>
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    <item>
      <title>Optimal Sitting and Sizing of the Remote Park-and-Ride Scheme in the Multimodal Transport Network</title>
      <link>https://trid.trb.org/View/1495115</link>
      <description><![CDATA[Existing Park-and-ride (P&R) sites usually locate near a train/bus station where construction and operation cost is considerably high. Thus, this paper proposes a new P&R service mode, “Remote P&R (RPR)”, where a car park locates in a suburban area with lower land value. Dedicated express bus service is used to connect this site to nearby train station. To evaluate the impacts of RPR in the network flows quantitatively, a combined modal split and traffic assignment model (CMSTA) is developed where a cross nest logit (CNL) model is adopted to cope with the mode similarity. The problem is solved by Evans algorithm. Taking the CMSTA as the lower level and multimodal stochastic system optimum (MSSO) as the objective, the authors further develop a model employing mathematical programming with equilibrium constraints (MPEC) for the optimal network design of RPR, which is solved by a meta-heuristics. Numerical examples demonstrate that optimal sitting and sizing of RPR scheme can significantly influence network users’ travel decisions, promote the usage of public transportation and mitigate traffic congestion in the congested area of metropolitan cities.]]></description>
      <pubDate>Tue, 20 Feb 2018 09:28:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1495115</guid>
    </item>
    <item>
      <title>Central city and valley (and fringe) parking study (1982/83) project no 203, being part of the background study programme for development plan ii (1984-1989)</title>
      <link>https://trid.trb.org/View/1193181</link>
      <description><![CDATA[This study was designed to provide the metropolitan transit authority (mta) with current detailed data on parking demand by type and trip purpose for the Brisbane central business district (CBD) and on parking supply by type. Included are details of alternative behaviour with restricted parking; analysis of parking charge rates; availability of commercial parking.  The study concludes that its results establish that prime off street parking locations in the city are dominated by long term commuter parking and that present under provision of priority off street short term parking does not seem to support Brisbane city council's policy of encouraging shopping and thereby keeping the CBD alive.]]></description>
      <pubDate>Fri, 24 Aug 2012 13:10:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1193181</guid>
    </item>
    <item>
      <title>Applications Manual for Logit Modes of Express Bus-Fringe Parking Choices</title>
      <link>https://trid.trb.org/View/1105692</link>
      <description><![CDATA[Manual computations and computerized applications of logit. models are described. The models demonstrated reflect travel behavior concerning express bus-fringe parking transit. The specific travel issues addressed include the basic automobile vs. express bus transit choice, model, transferability, between two study areas, submodal split, and n-dimensional choice modeling. A series of curves derived from th:e mathematical models are presented in the appendices to simplify computations. A FORTRAN subroutine for using these models within the Urban Transportation Planning System (UTPS) battery of computer programs for transportation planning is provided.]]></description>
      <pubDate>Wed, 20 Jul 2011 07:24:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1105692</guid>
    </item>
    <item>
      <title>Planning Criteria for Express Bus-Fringe Parking Operations. Volume I of Express Bus-Fringe Parking Planning Methodology</title>
      <link>https://trid.trb.org/View/1105330</link>
      <description><![CDATA[Tripmaker reactions to two recent express bus-fringe parking operations in Richmond and Norfolk-Virginia Beach, Virginia, are examined. This travel behavior is interpreted to establish planning and design guidelines for locating and designing fringe lots and establishing operational policy for associated bus services. A market area for each service is defined in view of residential accessibility to the terminal. The primary improvements to the service that were suggested by automobile travelers who were surveyed related to the level of service provided; specific improvements here included expansion of the service area and hours of operation. The transit riders cited comfort and system design features for upgrading the service to their standards as their primary recommendations.]]></description>
      <pubDate>Wed, 20 Jul 2011 07:24:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/1105330</guid>
    </item>
    <item>
      <title>Express Bus-Fringe Parking Planning Methodology</title>
      <link>https://trid.trb.org/View/1103874</link>
      <description><![CDATA[The conception, calibration, and evaluation of alternative disaggregate behavioral models of the express bus-fringe parking travel choice situation are described. Survey data collected for the Parham Express Service in Richmond, Virginia, are used to define the service market area and to construct binary and n-dimensional choice models. The performance of these models is tested using a set of comprehensive evaluation criteria. Finally, the Parham Express model is applied to another fringe parking service (Princess Anne Plaza in Virginia Beach, Virginia) to evaluate the transferability of such models for planning applications. It is concluded that a model calibrated for a given urban subarea can be transferred and applied only to other areas which exhibit similar population, service, and urban development characteristics. The requirements of a generalized model are described.]]></description>
      <pubDate>Thu, 23 Jun 2011 09:07:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1103874</guid>
    </item>
    <item>
      <title>Evaluation of the Greenwood Drive fringe parking facility</title>
      <link>https://trid.trb.org/View/886577</link>
      <description><![CDATA[The application of a procedural method for planning express bus-fringe parking transit to determine why the Greenwood Drive service in Portsmouth, Virginia, failed to attract more riders than it did is described. The analysis of the study area revealed that many of the conditions which have been shown to prevail where the majority of successful express bus-fringe parking services have been implemented do not exist in the Portsmouth-Norfolk area. An analysis of the demand for the service indicated that the low levels of patronage that have been experienced could be expected. It was determined that when the Greenwood Drive service was originally planned, a competing subscription bus service was not properly considered. It was also shown that the methodology employed improves the general capability for developing successful park and ride transit operations.]]></description>
      <pubDate>Tue, 31 Mar 2009 13:34:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/886577</guid>
    </item>
    <item>
      <title>A procedural method for express bus-fringe parking transit planning</title>
      <link>https://trid.trb.org/View/880062</link>
      <description><![CDATA[The report illustrates a procedural method for planning express bus-fringe parking transit services - a method built upon the findings from previous research, including disaggregate travel choice models and planning guidelines.  The methodology addresses the tasks of site selection, demand analysis, and site evaluation.  The appropriateness of this subarea planning process is demonstrated in an application to Southside Richmond.  The case study is documented so that transportation planners can use it as a guide for employing the procedure.]]></description>
      <pubDate>Wed, 28 Jan 2009 17:40:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/880062</guid>
    </item>
    <item>
      <title>APPLICATIONS MANUAL FOR LOGIT MODELS OF EXPRESS BUS-FRINGE PARKING CHOICES. FINAL REPORT--IMPLEMENTATION</title>
      <link>https://trid.trb.org/View/275661</link>
      <description><![CDATA[Manual computations and computerized applications of logit models are described.  The models demonstrated reflect travel behavior concerning express bus-fringe parking transit.  The specific travel issues addressed include the basic automobile vs. express bus transit choice, model transferability between two study areas, submodal split, and n-dimensional choice modeling.  A series of curves derived from the mathematical models are presented in the appendices to simplify computations.  A FORTRAN subroutine for using these models within the UTPS battery of computer programs for transportation planning is provided.]]></description>
      <pubDate>Sat, 28 Aug 2004 04:41:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/275661</guid>
    </item>
    <item>
      <title>SIMPLIFIED AIDS FOR TRANSPORTATION ANALYSIS: FRINGE PARKING SITE REQUIREMENTS</title>
      <link>https://trid.trb.org/View/89483</link>
      <description><![CDATA[This is one of a series of six reports describing simplified aids to improve transportation decisions without resorting to computers or extensive data collection. The analytical aid described in this report provides a method to: (1) identify candidate sites for change-of-mode fringe parking facilities; (2) estimate specific parking facility requirements at these candidate sites; and (3) estimate highway access requirements for the sites.]]></description>
      <pubDate>Thu, 19 Dec 2002 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/89483</guid>
    </item>
    <item>
      <title>FRINGE PARKING</title>
      <link>https://trid.trb.org/View/692357</link>
      <description><![CDATA[Traffic congestion is the number one problem in cities; parking is a corollary problem produced by increased use of automobiles and traffic congestion.  A possible solution to the congestion problem in central business districts is proposed in the article.  The city of Cleveland has used fringe parking lots, served by buses between the lots and the central business district.  Freeways that avoid the congestion of the central business district serve the lots.  The program is a success in Cleveland.]]></description>
      <pubDate>Tue, 21 Aug 2001 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/692357</guid>
    </item>
    <item>
      <title>ELECTRIC SHUTTLES LINK FRINGE PARKING LOTS, STRASBOURG CBD</title>
      <link>https://trid.trb.org/View/503846</link>
      <description><![CDATA[To connect its major fringe parking lot with the heart of the pedestrianized downtown, the city of Strasbourg, France, has instituted an electric low-floor minibus shuttle service that is free to users of the parking lot.  Others pay Fr2 (40 cents) a trip to use the 2.3 km loop line, which has five stops, four of them inside the pedestrian zone.  The two initial Neoplan buses that provide the service can carry 35 passengers (15 seated) each and have a low-floor throughout.  They are equipped with two battery packs and cost the equivalent of $400 each.  The battery pack is changed twice a day at the end of the line, an operation that takes less than 10 minutes.]]></description>
      <pubDate>Tue, 08 Jun 1999 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/503846</guid>
    </item>
    <item>
      <title>FRINGE PARKING AS AN ALTERNATIVE..</title>
      <link>https://trid.trb.org/View/570075</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Fri, 20 Feb 1998 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/570075</guid>
    </item>
    <item>
      <title>FRINGE PARKING ADVANTAGES IN THE OSLO REGION..</title>
      <link>https://trid.trb.org/View/634322</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Thu, 20 Mar 1997 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/634322</guid>
    </item>
    <item>
      <title>PROCEDURE FOR ESTIMATING DEMAND FOR REGIONAL FRINGE PARKING FACILITIES</title>
      <link>https://trid.trb.org/View/79870</link>
      <description><![CDATA[Purpose of this study was to determine the best location and the optimum feasible quantity of additional parking spaces that would effectively serve potential demand for change-of-mode parking at the interface between highway and passenger rail systems.  Selection criteria, such as available land, accessibility to highway system, current rail ridership, and current parking demand, were used to identify 20 potential fringe parking sites.  Future demand for parking spaces at the selected sites was determined in four steps.  The first step dealt with trip interchanges. All future trip makers who reside in the influence area of each of the potential sites, and whose trip destinations lie in the distribution service area of the passenger rail system were identified and quantified.  In the second step, the market share of each mode was calculated by using a disutility mode-choice model.  Disutility rates for the automobile and rail modes were computed for each of the trip origin areas, and the percentage of passenger rail trips was derived from diversion curves.  In the third step, the proportion of projected commuter rail patrons demanding parking spaces at each site was established by using a relationship between the distances patrons travel to the station and their access modes to the station.  Finally, additional parking spaces over and above the number of spaces already existing or planned were calculated for each site. /Author/]]></description>
      <pubDate>Thu, 03 Dec 1981 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/79870</guid>
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