Mesoscopic simulation for transit operations

This paper presents a transit simulation model designed to support evaluation of operations, planning and control, especially in the context of Advanced Public Transportation Systems (APTS). Examples of potential applications include frequency determination, evaluation of real-time control strategies for schedule maintenance and assessing the effects of vehicle scheduling on the level of service. Unlike most previous efforts in this area, the simulation model is built on a platform of a mesoscopic traffic simulation model, which allows modeling of the operation dynamics of large-scale transit systems taking into account the stochasticity due to interactions with road traffic. The capabilities of Mezzo as an evaluation tool of transit operations are demonstrated with an application to a real-world high-demand bus line in the Tel-Aviv metropolitan area under various scenarios. The headway distributions at two stops are compared with field observations and show good consistency between simulated and observed data.     

Polycentricity and transit service

This paper focuses on the two related issues of employment distribution and access to transit services. Using the 2001 census tract level economic activities and transit routes within the county, a number of analyses were performed to determine the location of major employment centers in Los Angeles County and how these localities may be understood within the context of a transit service operation in a polycentric metropolitan area. The identified economic subcenters contain one-third of the county employment and its firms, collectively. While these economic nodes are networked by the existing bus routes, the connection between employees and their place of work appears to be inadequate. This has created a less than optimal condition in many sections of the metropolitan area. This paper suggests methodologies for encountering this shortcoming.     

Economic and service comparison of conventional bus and automated transit—a case study

Three origin‐destination matrices of inter‐zonal person trips for a section of the Los Angeles metropolitan region are analyzed using principal component analysis. The matrices represent total person trips, journey‐to‐work trips, and shopping trips. This allows for the identification of a number of sub‐regional travel fields or functional regions within the area. The composition of and interrelationships between these fields and the spatial coincidence of fields defined for different travel purposes are compared with existing and proposed public transit facilities.     

Freight Data Assembling and Modeling: Methodologies and Practice

Abstract

In comparison to personal travel, freight movements within large metropolitan areas are much less studied. Most conventional transportation models and planning analysis that disregarded freight flows have been criticized on the plausibility of their results and conclusions. To alleviate these problems, this study proposes a non-survey based approach to assemble and process freight data in a systematic way. A freight origin–destination (OD) matrix of freight flows can be developed using secondary data sources. The estimated freight flows can be loaded together with conventional passenger flows onto the regional highway network of a large metropolitan area. As a case study, this non-survey based approach was applied to build a freight OD and study the traffic flows in Los Angeles. It concluded that this approach can be used to analyze urban freight movement in a low-cost way in which planning agencies can overcome the common omission of freight flow information in their transportation plans.     

Improving the resolution of gridded-hourly mobile emissions: incorporating spatial variability and handling missing data

To more accurately predict hourly running stabilized link volumes for emissions modeling, a new method was recently developed that disaggregates the period-based model link volumes into hourly volumes using observed traffic count data and multivariate multiple regression (MMR). This paper extends the MMR methodology with clustering and classification analyses to account for spatial variability and to accommodate model links that do not have matching observed traffic count data. The methodology was applied to data collected in the South Air Basin. The spatial analysis resulted in identifying five clusters (or 24-h profiles) for San Diego and two clusters for Los Angeles. The MMR models were then estimated with and without clustering. For San Diego, the disaggregated model volumes with clustering were much closer to the observed volumes than those without clustering, with the exception of the a.m. period. For most hours in Los Angeles, the predicted volumes with clustering were only slightly closer to the observed volumes than those predicted without clustering, suggesting that spatial effects are minimal in Los Angeles (i.e., that 24-h volume profiles are fairly similar throughout the region) and clustering is not necessary. Finally, two classification models, one for San Diego and one for Los Angeles were developed and tested for network link data that does not have matching observed count data. The results indicate the procedure is relatively good at predicting a cluster assignment for the unmatched location for Los Angeles but less accurate for San Diego.     

ITS applications for work zones

The use of Intelligent Transportation Systems (ITS) in construction work zones to disseminate traffic information has increased significantly in recent years, mainly with the use of Variable Message Signs (VMS). VMS are used based on the assumption that informed drivers will make better travel decisions, thereby reducing congestion. However, the extent of change in driver behavior is difficult to predict prior to ITS deployment. This difficulty leads to the larger problem of justifying investment in ITS. This article proposes an ITS deployment decision support tool using micro‐simulation. The approach determines the required diversion effectiveness of a work zone ITS deployment using VMS. The methodology was tested using the Glenmore Trail/Elbow Drive/5^th Street interchange project (GE5) in Calgary, Canada. The results indicate that the proposed approach will assist agencies in justifying ITS investment by exhibiting the potential resultant societal benefits.     

Regulating traffic by controlling land use The Southern California experience

In Los Angeles emphasis in transportation planning has recently shifted from facility construction to transportation system management and the control of land use with the goal of slowing the growth in traffic congestion. This paper critically examines several recent transportation growth management strategies in Los Angeles, and concludes that though they were well intentioned, they might not lead to the intended consequences.     

The impact of rush hour traffic and mix on the ozone weekend effect in southern California

The ozone weekend effect refers to the counterintuitive observations showing weekend ozone concentrations frequently to be higher than or comparable to those observed on weekdays. Ozone dynamics are closely linked to the timing, magnitude and fleet mix of transportation activities, primary sources of ozone precursor emissions. To examine the effects of traffic activity on the ozone weekend effect, a statistical analysis was conducted of the weekly patterns of time dependent light-duty vehicle and heavy-duty truck volumes observed at 27 weigh-in-motion stations in southern California. The results show statistically significant variations in traffic flows by day of week, by vehicle type, and by location with respect to the Los Angeles metropolitan area. These variations in traffic, when converted to variations in running exhaust emissions, tend to support four of the seven California Air Resources Board’s ozone weekend effect hypotheses.     

Incident characteristics,frequency, and duration on a high volume urban freeway

Rapidly deteriorating travel conditions in U.S. metropolitan areas have led to renewed interest in more effectively managing nonrecurrent congestion. Effective incident management requires an understanding of incident patterns, frequency, and duration. However, such information is limited. This paper presents an analysis of incidents using data from a major Los Angeles, California freeway. Incident patterns are described, and duration is analyzed as a function of incident characteristics. Results indicate that accidents make up a very small proportion of all incidents, but account for a relatively greater share of all incident duration. Major explanatory factors of incident duration include incident type, time of day, truck involvement, and lane closures. The paper concludes with a discussion of alternative approaches to reducing the congestion impacts of incidents.     

Assessing traveler responsiveness to land and location based accessibility and mobility solutions

In this paper, a joint multinomial logit (MNL) model of residential location and vehicle availability choice is formulated and estimated using a sample of households from the San Francisco, CA area Metropolitan Transportation Commission's 1990 household travel survey. Subsequently, models of travel intensity (number of daily household trips and vehicle-miles traveled) are estimated as a function of household characteristics and of attributes derived from the joint residential location and auto availability choice model (number of vehicles, percent land developed). A policy test shows that reducing the cost of locating in the densest areas of the metropolitan area is likely to have only marginal impact on vehicle availability and household trip making.     

Job accessibility and employment outcomes: which income groups benefit the most?

Improving job accessibility can increase the probability for individual persons to be employed and reduce their commutes. Empirical research suggests that the relationship between job accessibility and employment outcomes differ across income groups, but no research has investigated the difference or explored which income groups benefit the most from job accessibility improvements. This research fills the gap by examining six income groups in the Los Angeles metropolitan area. Results show that job accessibility affects the employment status of medium-to-low income groups (household income between US$25,000 and US$75,000). For the lowest-income group (household income lower than US$25,000), owning a car significantly improves their chances to be employed, but job accessibility has no effect. On the other hand, higher job accessibility is associated with shorter commuting distance for the other five income groups, but not for the lowest-income group. These results suggest that transportation and land use policies need to address the specific needs of distinct population groups and underscore the importance of spatial access for the middle-class, which tends to be overlooked in the literature on transportation equity.     

A private matter: the implications of privacy regulations for intelligent transportation systems

The rapid development and deployment of Intelligent Transportation Systems (ITS) that utilize data on the movement of vehicles can greatly benefit transportation network operations and safety, but may test the limits of personal privacy. In this paper we survey the current state of legal and industry-led privacy protections related to ITS and find that the lack of existing standards, rules, and laws governing the collection, storage, and use of such information could both raise troubling privacy questions and potentially hinder implementation of useful ITS technologies. We then offer practical recommendations for addressing ITS-related privacy concerns though both privacy-by-design solutions (that build privacy protections into data collection systems), and privacy-by-policy solutions (that provide guidelines for data collection and treatment) including limiting the scope of data collection and use, assuring confidentially of data storage, and other ways to build trust and foster consumer consent.     

Do parking requirements significantly increase the area dedicated to parking? A test of the effect of parking requirements values in Los Angeles County

Minimum parking requirements (MPRs) are the norm for urban and suburban development in the United States (Davidson et al., 2002). The justification for MPRs is that overflow parking will occupy nearby street or off-street parking. Shoup (1999a) and Willson (1995) provide cases where there is reason to believe that parking space requirements have forced parcel developers to place more parking than they would in the absence of parking requirements. However, to our knowledge the existing literature does not test the effect of parking minimums on the amount of lot space devoted to parking beyond a few case studies. This paper tests the hypothesis that MPRs bind for most land uses using data on suburban office, commercial, industrial and retail property sales from Los Angeles County using both direct and indirect approaches. Our indirect test of the effects of parking requirements is similar to the one used by Glaeser and Gyourko (2003). A simple theoretical model shows that the marginal value of additional parking to the sale price of a building should be equal to the cost of land plus the cost of parking construction. We estimate the marginal values of parking and lot area with spatial methods using a large data set from the Los Angeles area non-residential property sales and find that for most of the property types the marginal value of parking is significantly below that of the parcel area. In addition, we directly examine required and supplied parking and find that on average parking supplied is quite close to the required amount.     

Bus travel time prediction using a time-space discretization approach

The accuracy of travel time information given to passengers plays a key role in the success of any Advanced Public Transportation Systems (APTS) application. In order to improve the accuracy of such applications, one should carefully develop a prediction method. A majority of the available prediction methods considered the variation in travel time either spatially or temporally. The present study developed a prediction method that considers both temporal and spatial variations in travel time. The conservation of vehicles equation in terms of flow and density was first re-written in terms of speed in the form of a partial differential equation using traffic stream models. Then, the developed speed based equation was discretized using the Godunov scheme and used in the prediction scheme that was based on the Kalman filter. From the results, it was found that the proposed method was able to perform better than historical average, regression, and ANN methods and the methods that considered either temporal or spatial variations alone. Finally, a formulation was developed to check the effect of side roads on prediction accuracy and it was found that the additional requirement in terms of location based data did not result in an appreciable change in the prediction accuracy. This clearly demonstrated that the proposed approach based on using vehicle tracking data is good enough for the considered application of bus travel time prediction.     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

Structure and influencing factors of CO2 emissions from transport sector in three major metropolitan regions of China: estimation and decomposition

Transportation - The three metropolitan regions, including Jing-Jin-Ji (JJJ), Yangtze River Delta (YRD) and Pearl River Delta (PRD), are the most developed regions of China. This study focuses on...     

Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data

This paper studies electric vehicle charger location problems and analyzes the impact of public charging infrastructure deployment on increasing electric miles traveled, thus promoting battery electric vehicle (BEV) market penetration. An activity-based assessment method is proposed to evaluate BEV feasibility for the heterogeneous traveling population in the real world driving context. Genetic algorithm is applied to find (sub)optimal locations for siting public charging stations. A case study using the GPS-based travel survey data collected in the greater Seattle metropolitan area shows that electric miles and trips could be significantly increased by installing public chargers at popular destinations, with a reasonable infrastructure investment.     

Environmental justice and hazmat transport: A spatial analysis in southern California

This paper explores whether the risk of a toxic release during transport is greater in poor and minority neighborhoods using a combination of mapping and statistical methods. Cluster analysis is used to examine the density of facilities and transport spill events as well as test for the spatial covariance between facilities and spills. Strong clustering of transport spills is evident, as well as clustering between factory sites and transport spills. A spatial model demonstrates raised rates of transport spills surrounding clusters of toxic firms. Most spills in Los Angeles occurred within 2 km of an intermodal facility. The last step of the analysis compares risk and facility clustering between neighborhoods and socio-economic groups, finding that hazmat spills during transport disproportionately occur in Latino neighborhoods in Los Angeles. The results clarify the spatial distribution of risk and nuisance from freight in urban landscapes.     

Intrazonal or interzonal? Improving intrazonal travel forecast in a four-step travel demand model

Transportation - Conventional four-step travel demand models, used by most metropolitan planning organizations (MPOs), state departments of transportation, and local planning agencies, are the...     

Demand responsive transit and the integration of D/R systems with traditional transit

This paper provides a background of the development of demand-responsive transit in small communities in the U.S.A. It also backgrounds traditional transit in metropolitan areas of the United States and outlines its deficiencies in terms of today's urban sprawl and in terms of today's society in metropolitan areas. Urban sprawl has developed city-like areas around big cities, but with lower population densities. Highways and roads were built. Cars were mass-produced. These new populations have never had an alternative to the private car. Today's society includes an ever-increasing number of senior citizens and handicapped persons. Senior citizens find it difficult to get to fixed-route bus stops; handicapped persons have difficulty in boarding regular buses and wheelchair persons cannot even get on board. Particular emphasis is placed upon the examination of the development of demand-responsive transit in metropolitan Rochester, U.S.A. and a Demonstration Project, sponsored by the Urban Mass Transportation Administration of the United States Department of Transportation. The paper also examines and makes reference to the results of integrated transit in Regina, Saskatchewan, Canada. The Demonstration Project has several key objectives, the principal one of which is the integration of demand-responsive transit with the fixed-route element of traditional transit. Other important objectives of the demonstration are the balancing of peak and off-peak service so as to improve the overall utilization of resources, increase transit coverage, regular (not special) service for the elderly and the handicapped, the utilization of a computer in dispatching, digital communications, and marketing and promotional techniques.