bluuebunny/crossref_metadata_2025 huggingface dataset:
Work Site Trip Reduction Model and Manual
Authors: Winters Philip L. , Perez Rafael A. , Joshi Ajay D. , Perone Jennifer
Published: May 2018

Today's transportation professionals often use the ITE Trip Generation Manual and the Parking Generation Manual for estimating future traffic volumes to base off-site transportation improvements and identify parking requirements. But these manuals are inadequate for assessing the claims made by specific transportation demand management (TDM) programs in reducing vehicle trips by a certain amount at particular work sites. This paper presents a work site trip reduction model (WTRM) that can help transportation professionals in assessing those claims. WTRM was built on data from three urban areas in the United States: Los Angeles, California; Tucson, Arizona; and nine counties in Washington State. The data consist of work sites’ employee modal characteristics aggregated at the employer level and a listing of incentives and amenities offered by employers. The dependent variable chosen was the change in vehicle trip rate that correlated with the goals of TDM programs. Two different approaches were used in the model-building process: linear statistical regression and nonlinear neural networks. For performance evaluation the data sets were divided into two disjoint sets: a training set, which was used to build the models, and a validation set, which was used as unseen data to evaluate the models. Because the number of data samples varied from the three areas, two training data sets were formed: one consisted of all training data samples from three areas and the other contained equally sampled training data from the three areas. The best model was the neural net model built on equally sampled training data.
Ecotravel Coordinator Program
Authors: Nakayama Shoichiro , Takayama Jun-ichi
Published: May 2018

This study introduces an ecotravel coordinator program to reduce car use. In this system, ecotravel coordinators are put in charge of several people. They organize ecotravel meetings and are responsible for taking the initiative. During the meetings participants recognize and deepen their understanding of their travel behaviors and devise their own plans for reducing car use. The aim of this study is to examine the validity of the ecotravel coordinator program through an experimental method. One result of the experiments was that the ecocoordinators and the other participants reduced their car travel mileage 54% and 48%, respectively. Nonparticipants, however, almost never reduced their travel mileage (1.4% reduction). Thus, experiment results indicate that the system is fairly effective for reducing car use.
Metering Ramps to Divert Traffic around Bottlenecks
Authors: Banks James H.
Published: May 2018

Three elementary cases, with ramp metering used to reduce delay by diverting traffic around bottlenecks, are analyzed. In these cases ( a) travel times on an alternate route bypassing the bottleneck are insensitive to flow on the alternate route, ( b) the alternate route is undersaturated but travel times are sensitive to flow, and ( c) the alternate route is oversaturated. Travel time equilibria and traffic assignments are relatively straightforward in all cases provided that equilibria in Cases b and c are assumed to be approximate and traffic assignments are based on drivers’ expectations about traffic conditions prevailing at particular times of day. A metering strategy intended to minimize delay is proposed. This strategy is expressed in terms of the order in which metering is initiated at different ramps and is similar to one previously proposed to maximize output to exits upstream of the bottleneck.
Estimating Traffic Stream Space Mean Speed and Reliability from Dual- and Single-Loop Detectors
Authors: Rakha Hesham , Zhang Wang
Published: May 2018

The relationship between time mean speed and space mean speed that was derived by Wardrop and presented in several textbooks is suitable for estimating time mean speeds from space mean speeds. In most cases, however, estimating space mean speed from time mean speed measurements is desired. Consequently, a new formulation utilizes the variance about the time mean speed as opposed to the variance about the space mean speed for the estimation of space mean speeds. It is demonstrated that space mean speeds are estimated within a margin of error from 0% to 1%. Furthermore, a relationship is developed between the space and time mean speed variances and between the space mean speed and the spatial travel time variance.
Evaluating Alternative Truck Management Strategies along Interstate 81
Authors: Rakha Hesham , Flintsch Alejandra Medina , Ahn Kuongho , El-Shawarby Ihab , Arafeh Mazen
Published: May 2018

The study evaluates lane management strategies along one of the most highly traveled sections of Interstate 81 in the state of Virginia by using the INTEGRATION traffic simulation software. The lane management strategies considered include the separation of heavy-duty trucks from light-duty traffic, the restriction of trucks to specific lanes, and the construction of climbing lanes at strategic locations. Overall, the results demonstrate that a physical separation of heavy-duty trucks from the regular traffic offers the maximum benefits and that restricting trucks from the use of the leftmost lane offers the second-highest benefits in terms of efficiency, energy, and environmental impacts.
Methodology for Performance Optimization of Ramp Control Strategies through Microsimulation
Authors: Beegala Adinarayana , Hourdakis John , Michalopoulos Panos G.
Published: May 2018

Freeway ramp control has been successfully implemented since the mid-1960s as an efficient and viable freeway management strategy. However, the effectiveness of any ramp control strategy is largely dependent on site-specific customization and calibration, preferably before its deployment. A general methodology for such performance optimization of ramp control strategies is proposed in a microscopic simulation environment as an alternative to trial-and-error field experimentation. The applicability of the methodology is demonstrated by implementation on Minnesota's new stratified zone metering (SZM). Further, the effect of external factors, such as traffic demand variation and incidents, on SZM control and optimization results was also studied. Results show that the optimization methodology is highly effective depending on the optimization objective, test site characteristics, and demand levels.
Improved Framework and Systematic Calibration for Left-Turn Signal Change Intervals
Authors: Yu Lei , Qiao Fengxiang , Zhang Yusong
Published: May 2018

The use of an appropriate method in determining the left-turn signal change interval (yellow change interval plus red clearance interval) can result in signal timings that improve both safety and efficiency of an intersection. An improved framework for calculating the change interval for the left-turn movement is presented: it incorporates a comprehensive set of parameters, which are identified from a survey. Field data collected from 21 intersections in eight Texas cities were used for the basic calibration of three essential parameters within the improved framework: drivers’ entering driving behavior, drivers’ behavior on left-turn curves, and drivers’ tolerable centrifugal force. After the basic calibration, a sensitivity analysis of the three essential parameters was conducted. Further, a systematic calibration approach was designed to extend the improved framework to a wider range of intersections with different approach speed limits, number of left-turn lanes, control types, and truck percentages. Values of the three essential parameters under different intersection attributes were calculated; they can be of direct reference for practicing engineers. Finally, the effect of intersection attributes on the yellow change and red clearance intervals was analyzed. The research recommends that the change intervals for left turns based on the proposed framework and calibration method be used by practicing engineers, which would improve both safety and efficiency of the intersection.
Evaluation of Lane-by-Lane Vehicle Detection for Actuated Controllers Serving Multilane Approaches
Authors: Smaglik Edward J. , Bullock Darcy M. , Urbanik Thomas
Published: May 2018

A comparison was conducted of traditional vehicle detection, in which all lanes on an approach are connected to an actuated controller through one amplifier card and input, and lane-by-lane detection, in which each lane is interfaced with the controller through separate amplifier cards and inputs. Both detection strategies were evaluated with various extension time values on the same traffic stream. A total of 430 h of data from two separate approaches was evaluated on an hour-by-hour basis. During certain time periods, lane-by-lane detection provided up to a 13% increase in efficiency. For all 930 h of observations, the median increase in efficiency was 5.2% on an approach with 51-ft-long detection zones and 3.5% on an approach with 38-ft-long detection zones. This increased efficiency corresponds to time that could be allocated to other movements or used to reduce the cycle length. The largest improvements associated with lane-by-lane detection occurred during periods with moderate volume-to-capacity ratios, with smaller benefits observed during periods of heavy or light traffic.
Evaluation of the Accuracy of Stop Bar Video Vehicle Detection at Signalized Intersections
Authors: Rhodes Avery , Bullock Darcy M. , Sturdevant James , Clark Zachary , Candey David G.
Published: May 2018

Many U.S. agencies have adopted video vehicle detection technology as an alternative to inductive loops. Although many product evaluations have been performed, the majority of these evaluations concentrated on freeway applications in which speed and volume were the primary evaluation criteria. At an actuated intersection, the metrics of speed and volume do not necessarily represent how well a device will operate as a presence detector. Video detection at signalized intersections was evaluated at a test intersection in Indiana. Cameras on all approaches were located at the optimal camera position recommended by the vendors, approximately 60 ft from the strain pole. Two additional cameras were located on each mast arm at slightly less optimal positions, 36 and 48 ft from the strain pole. Traditional inductive loops were also available at the intersection and were used to provide baseline data to screen for discrepancies. Each time the detectors were not in agreement, a discrepancy was noted. A digital video recording was later viewed by a human observer to determine whether the video detector or the loop detector was in error. An analysis of the data showed that video detection was found to produce statistically significantly more false detections and missed detections than the loop detectors on most phases. A small incremental increase in performance was observed when the camera was mounted at 60 ft rather than 36 ft on two of the approaches, but this marginal improvement likely does not justify the additional expense of mast arm, pole, and pole foundation associated with this camera location.
Advanced Transit Signal Priority Control with Online Microsimulation-Based Transit Prediction Model
Authors: Lee Jinwoo , Shalaby Amer , Greenough John , Bowie Mike , Hung Stanley
Published: May 2018

An advanced transit signal priority (TSP) control method is presented: it provides priority operation in response to real-time traffic and transit conditions. A high-performance online microscopic simulation model was developed for the purpose of predicting transit travel time along an intersection approach. The proposed method was evaluated through application to a hypothetical intersection with a nearside bus stop. The performance of the proposed method was compared with that of normal signal operation without TSP and a conventional signal priority method. The experimental results indicated that the developed method provided efficient and effective priority operation for both transit vehicles and automobiles. The proposed method significantly reduced transit vehicle delays as well as side-street traffic delay compared with conventional active priority control.
Configuration Methodology for Traffic-Responsive Plan Selection
Authors: Abbas Montasir M. , Chaudhary Nadeem A. , Pesti Geza , Sharma Anuj
Published: May 2018

Although several studies have shown the potential great benefits of traffic-responsive plan selection (TRPS) control, time-of-day operation continues to be the primary method used to select patterns for signal control applications. This practice could be largely attributed to the minimal guidelines available on the setup of the TRPS mode. An innovative framework for TRPS system setup is provided, and guidelines for implementing TRPS in a simplified manner are shown. The guidelines, developed at Texas Transportation Institute (TTI), use a comprehensive approach that incorporates a multiobjective evolutionary algorithm and a supervised discriminant analysis. Engineers can directly implement the guidelines presented as an initial design. Hardware-in-the-loop simulation is used to illustrate the performance of TTI's TRPS configuration methodology.
Improved Transit Signal Priority System for Networks with Nearside Bus Stops
Authors: Kim Wonho , Rilett L. R.
Published: May 2018

Transit signal priority (TSP), which has been deployed in many cities in North America and Europe, is a traffic signal enhancement strategy that facilitates efficient movement of transit vehicles through signalized intersections. Most TSP systems, however, do not work well in transit networks with nearside bus stops because of the uncertainty in bus dwell time. Unfortunately, most bus stops on U.S. arterial roadways are nearside ones. In this research, weighted-least-squares regression modeling was used to estimate bus stop dwell time and, more important, the associated prediction interval. An improved TSP algorithm that explicitly considers the prediction interval was developed to reduce the negative impacts of nearside bus stops. The proposed TSP algorithm was tested on a VISSIM model of an urban arterial section of Bellaire Boulevard in Houston, Texas. In general, it was found that the proposed TSP algorithm was more effective than other algorithms because it improved bus operations without statistically significant impacts on signal operations.
Resonant Cycles in Traffic Signal Control
Authors: Shelby Steven G. , Bullock Darcy M. , Gettman Douglas
Published: May 2018

The potential benefits of using resonant cycle times in traffic signal control on an arterial are investigated. Resonant cycles are cycle lengths that result in good arterial progression over a range of traffic flows. The notion of resonant cycle times contrasts with the prevalent adaptive control practice of setting the arterial cycle length in proportion to flow levels at the most congested intersection on the arterial. This research was motivated by the development of appropriate adaptive algorithms for closed-loop system control in the FHWA ACS-Lite project. Simulation experiments with TRANSYT-7F for a four-intersection arterial and additional time–space diagrams demonstrate the characteristics of resonant cycle times and the substantial performance benefits that they may offer. In addition, a systematic method was developed to identify appropriate resonant cycle times and fine-tune a schedule for a time-of-day signal timing strategy.
Analysis of Freeway Improvements for Express Bus Service
Authors: Cherry Christopher R. , Tang Eric , Deakin Elizabeth , Skabardonis Alexander
Published: May 2018

In many urban areas, high-occupancy vehicle (HOV) lanes have been provided to permit carpools and express buses to bypass congestion and offer a significant travel time advantage to commuters willing to share a ride or take transit. In many locations, however, HOV lanes are incomplete because of difficulties in securing right-of-way or funding. In other locations, because existing HOV lanes are underutilized, express buses are undersubscribed, or both, questions about their value arise. In this research it is shown how a PARAMICS microscopic traffic simulation model can be used to analyze proposed HOV lanes and their effects on express bus operation along an urban freeway corridor. A PARAMICS application is developed for Interstate 580 in the San Francisco Bay Area and used to test alternative ways of providing HOV lanes. The performance of the corridor is evaluated under plausible scenarios of traffic growth. Traffic simulation models are usually used for detailed operations management. The case study shows that traffic simulation can be an effective preliminary planning and scenario testing tool for evaluating the likely performance of an infrastructure or operations improvement on express bus service.
Modeling Workers’ Daily Nonwork Activity Participation and Duration
Authors: Chu You-Lian
Published: May 2018

This paper presents a mathematical model used to determine jointly a worker's decision to participate in a nonhome and nonwork activity and the decision on how long to participate. With the household interview survey data from the New York City area, the workers’ participation and duration decisions were estimated for each of five periods in a worker's day: before morning commute, morning commute, midday, evening commute, and after evening commute. To account for the censored nature of the duration data (i.e., a large number of observations clustered at zero), Heckman's sample selection model was used together with the full information maximum likelihood estimation method. To enhance the behavioral basis for the models, extensive statistical tests were given to the model specifications and the assumptions underlying the model structure. The empirical results provide useful insights into the effects of socio-demographics, land use–transportation measures, and activity duration characteristics on workers’ daily scheduling of nonwork activities and travel in a highly urbanized environment. This study also provides exploratory methodologic evidence that could lead to an approach for predicting the change in a worker's nonwork activity patterns (participation and duration) as a result of changes in future demographic conditions and land use–transportation scenarios.
Characterizing Global Activity Schedule Adjustment Behavior by Using a Sequence Alignment Method
Authors: Joh Chang-Hyeon , Polak John W. , Ruiz Tomás
Published: May 2018

Considerable interest has developed recently in the decision-making processes underlying activity schedule adjustment. This paper suggests a method, based on sequence alignment techniques, to measure schedule adjustment behavior and applies the method to develop a model of the factors influencing schedule adjustment, with the use of data from a recent Internet-administered survey. The results indicate that the amount of schedule modification that occurs is largely determined by characteristics of the planned schedule instead of background socioeconomic or activity-related variables. The implications of this finding for future research in this area are considered.
Mixed Logit Model of Activity-Scheduling Time Horizon Incorporating Spatial–Temporal Flexibility Variables
Authors: Mohammadian Abolfazl (Kouros) , Doherty Sean T.
Published: May 2018

Observed travel patterns are the result of an underlying activity-scheduling process. Understanding how individuals plan and sequence their activities and trips over time will offer promise, as researchers are interested in developing models that can predict the sequences in which activities are added to the schedule during a continuous process of schedule construction. In practice, a fixed order by activity type is often assumed, but it ignores the strong interdependencies in activity and travel choices. This study presents the process of developing a mixed logit discrete choice model to predict the choice of the activity-scheduling time horizon. The model classifies activities according to the order in which they were planned (weeks or months ago, same week, same day, or impulsive). A variety of explanatory variables were used to provide a good model fit. Overall, the model demonstrates that activity planning is influenced by a wide variety of explanatory variables, including observable activity types and characteristics, spatial–temporal flexibility, and household and individual characteristics.
How Far in Advance Are Activities Planned?
Authors: Doherty Sean T.
Published: May 2018

The development of simulation models of activity-scheduling behavior has gained momentum over the past decade as a means to forecast travel demands. Of fundamental concern in these models is the process or timing of scheduling decisions–-or planning time horizon. Conceptually, it is understood that activities are planned over varying time horizons, but little empirical evidence exists. One way to explore these issues is to ask people to self-report when they planned their activities. However, this is a difficult question for researchers to formulate and for people to comprehend and recall, because people often plan (and replan) activity attributes over an extended period of time, some without much conscious thought. The objective of this paper is to describe the development of a planning time horizon query that was part of a larger activity scheduling process survey and to provide one of the first empirical analyses based on a random sample of 373 respondents. Included is a detailed examination of activity addition, modification, and trip-planning time horizons as well as analysis of “routine” and “unrecalled” decisions. Results indicate that people have the ability to recall a high level of detail on a planning time horizon, ranging from decisions made long ago that establish an initial skeleton schedule to continued preplanning in the days leading up to the event day and impulsive decisions made the day of the event. The implications of these results for future survey design and development of an activity-scheduling process simulation model are discussed.
Assessing User Benefits with Discrete Choice Models
Authors: Cherchi Elisabetta , Polak John W.
Published: May 2018

Over the past decade, significant advances have been made in the capacity of choice models to accommodate flexible patterns of taste heterogeneity and substitution. However, relatively little research has been done on the implication of these more advanced model structures for the computation of economic welfare and consequent benefit measures. This paper investigates the extent that degradation in model specification affects the welfare changes attributed to a transport policy measure. In particular, the focus is on the random taste heterogeneity, and simulated data are used to analyze how model estimation and assumptions about the specification to taste heterogeneity influence the ability to account for it in the user's benefits. The results indicate that there can be circumstances in which the most commonly used taste distributions cannot provide an adequate representation of the underlying distribution of tastes and that mis-specification can have unpredictable effects on benefit estimates. The implications of these findings are discussed.
Exploratory Analysis of Weekend Activity Patterns in the San Francisco Bay Area, California
Authors: Lockwood Allison M. , Srinivasan Sivaramakrishnan , Bhat Chandra R.
Published: May 2018

Research on travel demand modeling has predominantly focused on weekday activity–travel patterns, with studying the effects of commute travel on peak period traffic congestion as a major objective. Few studies have examined the weekend activity–travel behavior of individuals. However, weekend travel volume has been increasing over time and is comparable to weekday travel volumes. Hence, weekend activity–travel patterns warrant careful attention in transportation planning. This paper focuses on presenting a comprehensive exploratory analysis of weekend activity–travel patterns and contrasting weekday and weekend activity participation characteristics. Data from the 2000 San Francisco Bay Area Travel Survey, California, are used in the analysis. A comparative analysis of several aggregate activity–travel characteristics indicates that, although weekday and weekend travel volumes are comparable, there are several key differences in activity–travel characteristics. Specifically, weekend activity–travel is predominantly leisure oriented and undertaken during the midday period. Average trip distances are longer on weekends. Transit shares are lower but occupancy levels in personal automobiles are higher on weekends. The weekend activity sequencing and trip-chaining characteristics explored in this study provide further insights into individuals’ activity organization patterns on weekend days. This paper highlights the importance of studying weekend activity–travel behavior for transportation planning and air-quality modeling. Insights from this exploratory analysis can form the basis for comprehensive weekend activity–travel modeling efforts.
Modeling the Impact of Travel Information on Activity–Travel Rescheduling Decisions under Conditions of Travel Time Uncertainty
Authors: Sun Zhongwei , Arentze Theo , Timmermans Harry J. P.
Published: May 2018

This study elaborates on a model system developed in earlier papers to predict the perceived value and use of travel information. The value of travel information is conceptualized as the extent to which the information allows the individual to make better activity–travel scheduling decisions at the beginning of the day and during execution of the schedule. By taking the broader schedule context into account, the model is sensitive to the impact of information and decisions on the full activity–travel pattern. Furthermore, the model includes Bayesian mechanisms to make sure that beliefs about travel times, and other uncertain events, and the credibility of the information source are updated each time information is received and the real travel time is experienced. This paper describes the results of numerical simulations conducted to illustrate the system and to derive theoretical implications from the model. The simulations show that the schedule context, learning, and expected information gain in combination determine the perceived value of information and that none of these factors can be ignored in the derivation of estimates of these values. A theoretical analysis further shows how decision trees can be pruned to reduce a potential problem of combinatorics.
Multiagent Learning-Based Approach to Transit Assignment Problem
Authors: Wahba Mohammed , Shalaby Amer
Published: May 2018

This paper presents an operational prototype of an innovative framework for the transit assignment problem, structured in a multiagent way and inspired by a learning-based approach. The proposed framework is based on representing passengers and their learning and decision-making activities explicitly. The underlying hypothesis is that individual passengers are expected to adjust their behavior (i.e., trip choices) according to their experience with transit system performance. A hypothetical transit network, which consists of 22 routes and 194 stops, has been developed within a microsimulation platform (Paramics). A population of 3,000 passengers was generated and synthesized to model the transit assignment process in the morning peak period. Using reinforcement learning to represent passengers’ adaptation and accounting for differences in passengers’ preferences and the dynamics of the transit network, the prototype has demonstrated that the proposed approach can simultaneously predict how passengers will choose their routes and estimate the total passenger travel cost in a congested network as well as loads on different transit routes.
Modeling the Impact of Key Events on Long-Term Transport Mode Choice Decisions
Authors: Verhoeven Marloes , Arentze Theo , Timmermans Harry J. P. , Van Der Waerden Peter
Published: May 2018

This paper describes the first phase of a study of the impact of key events on long-term transport mode choice decisions. The suggested complexity of transport mode choice is modeled with a Bayesian decision network. An Internet-based questionnaire was designed to measure the various conditional probability tables and the conditional utility tables of the Bayesian decision network. Seven key events were implemented in the questionnaire: change in residential location, change in household composition, change in work location, change in study location, change in car availability, change in availability of public transport pass, and change in household income. Data from 554 respondents were used to illustrate how the tables can be constructed on the basis of event history data.
Methodology for Exploratory Analysis of Latent Factors Influencing Drivers’ Behavior
Authors: Prato Carlo Giacomo , Bekhor Shlomo , Pronello Cristina
Published: May 2018

In the context of route choice, modeling the process that generates the set of available alternatives in the mind of the individual is a complex and not fully explored issue. Route choice behavior is influenced by variables that are observable, such as travel time and cost, and unobservable, such as attitudes, perceptions, spatial abilities, and network knowledge. In this study, attitudinal data were collected with a web-based survey addressed to individuals who habitually drive from home to work. The paper proposes a methodology to conduct a proper application of factor analysis to the route choice context and describes the preparation of an appropriate data set through measures of internal consistency and sampling adequacy. The paper shows that, for the data set obtained from the web-based survey, six latent constructs affecting driver behavior were extracted and scores of each driver on each factor were calculated.
Simulation of Daily Activity Patterns Incorporating Interactions within Households
Authors: Přibyl Ondřej , Goulias Konstadinos G.
Published: May 2018

Activity-based approaches to travel demand analysis have gained attention in the past few years and rapidly created the need to develop alternative microsimulation models for comparisons. In this paper, one such example simulates an individual's daily activity–travel patterns and incorporates the interactions among members of households. This model uses several tools to simulate the activity patterns, including a new method to extract activity patterns from data and decision trees to take into account personal and household characteristics. The model outputs are the individuals’ daily activity patterns on a detailed temporal scale. These patterns respect individuals’ constraints, which are implicitly embedded in the simulated activity and travel schedules via the intrahousehold interactions. This model was evaluated with data from 1,500 persons in Centre County, Pennsylvania, collected during fall 2002 and spring 2003.
Investigating the Effect of User Behavior Factors and Transportation Control Measures on Day-to-Day Network Evolution and Trip Time Reliability
Authors: Guo Zhiyong , Srinivasan Karthik K.
Published: May 2018

This paper investigates the day-to-day dynamics in an urban traffic network induced by joint route and departure time switching dynamics in commuter decisions under real-time information. The role of switching inertia, the user's sensitivity to experienced and lagged system attributes, and travel demand management measures on day-to-day evolution are analyzed. A simulation-based day-to-day network analysis framework is developed by incorporating empirically calibrated user behavior models under information. This model can be used to analyze network reliability and stability measures. Because it can model users’ responses to information and experience, this framework permits relaxing the assumption that user behavior remains unchanged. Therefore, it can be used to model the transient effects due to various types of system perturbations and shocks. Computational experiments are used to investigate the effect of the aforementioned factors. The findings suggest that trip time variability and lateness propensity increase under high congestion. Under joint switching dynamics, a significant deviation from equilibrium is observed even after nearly 2 months. Departure time switching behavior appears to exert a greater influence than route switching on day-to-day dynamics, and transportation control measures can improve trip time and network reliability. These results have important implications for congestion mitigation strategies, network reliability assessment, and evaluation of intelligent transportation system technologies.
Analysis of Morning Commute Route Choice Patterns Using Global Positioning System–Based Vehicle Activity Data
Authors: Li Hainan , Guensler Randall , Ogle Jennifer
Published: May 2018

This paper examines morning commute route choices of 182 drivers, with the use of disaggregated Global Positioning System–based vehicle activity data collected during a 10-day period. This paper attempts to describe how these commuters tend to behave in the real world. A binary logit model of morning commuters’ choice between a single commute route and multiple routes was established on the basis of evidence of drivers’ varying valuations of a number of route and trip characteristics as well as commuters’ sociodemographic characteristics. The research results of this paper indicate a strong relationship between the morning commute route choice decision (single versus multiple routes) and commuters’ work schedule flexibility, sociodemographic characteristics, and commute route attributes.
Vehicle Miles Traveled in Multivehicle Households
Authors: Pathomsiri Somchai , Haghani Ali , Schonfeld Paul M.
Published: May 2018

Vehicle miles traveled (VMT) is an important factor in the development of transportation plans, emission mitigation measures, and energy conservation policies. Therefore, estimation of VMT is a crucial task supporting such plans and policies. This research addresses the estimation of VMT in households owning multiple vehicles. This sector is expected to use vehicles differently from single-vehicle households because usage of any vehicle may depend on usage of other vehicles. Previous studies concluded that there is a substitution effect between usages of two vehicles (i.e., greater usage of one vehicle lessens usage of the other). In view of more recent changes in sociodemographic structure, the problem was revisited with the 2001 National Household Travel Survey database. The proposed VMT model is a system of simultaneous equations. Each equation explains the VMT for one of the household's vehicles. The three-stage least-squares method was used to estimate the coefficients. A case study of two-vehicle households was investigated. The resulting model shows that VMT can be explained by variables such as the vehicle's newness, number of potential car users in a household, and household income. Surprisingly, the results show not a substitution effect but a spilling effect. The VMT of the first vehicle does not depend on how much the second vehicle is driven. However, increased use of the first vehicle tends to spill over and increase the use of the second one. Some explanation of this behavior shift is provided.
Home-Based Teleshopping and Shopping Travel
Authors: Ferrell Christopher E.
Published: May 2018

Structural equation modeling techniques were used to explore the tradeoffs that people make when teleshopping from home. Early in the development and growth of online shopping, many assumed that it would become a direct substitute for traditional retail (out-of-home) shopping and thereby reduce shopping trips and vehicle miles traveled. A growing body of research on the interplay between the use of information and communications technologies suggests that people shop and travel for a multitude of reasons that depend on the interplay between lifestyle, availability and convenience of shopping opportunities and the demands of other activities during the day. Using the San Francisco Bay Area Travel Survey 2000 from California, this paper performs an activities analysis to investigate these relationships. Time use variables predict the amount of time each individual spends during the day on work, maintenance, discretionary, and shopping activities both inside and outside the home. These activities are used to predict the amount of shopping travel each person undertook. Results suggest that people substitute home teleshopping time for shopping travel time and that teleshoppers take fewer shopping trips and travel shorter total distances for shopping purposes. Variables constructed to represent the degree to which people are “time-starved” from the demands of their work and maintenance activities revealed that female heads of households tend to teleshop more, make more shopping trips and shopping trip chains, do more out-of-home shopping, and shop travel for longer periods than the rest of the survey population.
Comparison of Emissions from Light Rail Transit and Bus Rapid Transit
Authors: Puchalsky Christopher M.
Published: May 2018

Bus rapid transit (BRT) is an evolving and promising transit mode that has emerged as a low-cost competitor to light rail transit (LRT) in providing medium-capacity semirapid transit. In addition, recent advances in diesel and compressed natural gas technology have caused the truism “electric rail is cleaner than diesel bus” to be revisited. A partial fuel cycle comparison of the regional or urban emissions of carbon monoxide, oxides of nitrogen, and volatile organic compounds from BRT and LRT is presented. The BRT analysis includes tailpipe exhaust emissions and fuel transportation, storage, and distribution emissions. The LRT analysis contains electric power plant emissions and line-loss-induced emissions. The analysis shows that whenever equal levels of technology are compared, LRT consistently performs better than BRT despite recent advances in the BRT mode. The analysis also shows that both modes are cleaner now than in the past.
Using Equivalent Walking Distance to Assess Pedestrian Accessibility to Transit Stations in Singapore
Authors: Olszewski Piotr , Wibowo Sony Sulaksono
Published: May 2018

The study aims to investigate factors that affect passengers’ choice of walking to rail transit and to develop a method of assessing walking conditions in the vicinity of mass rapid transit (MRT) stations in Singapore. The focus is on the analysis of surveys conducted around 11 MRT stations and the development of the concept of equivalent walking distance. Besides interview surveys with passengers at the stations, assessments of more than 200 walking routes were carried out in the field to investigate the actual walking distances and conditions, such as walkway quality, steps, slopes, presence of barriers, and delays at road crossings. About 60% of MRT passengers walked to the stations, and the average walking distance was 608 m. Men were more likely to walk than women. A submodal split model was estimated to investigate factors affecting passengers’ choice of walking or taking a feeder service to access an MRT station. Besides the actual distance, factors that significantly affected the access mode choice were number of road crossings, traffic conflicts, and number of ascending steps. The equivalent walking distance equation is proposed on the basis of the model coefficients; the equation reflects the relative effect of these factors on the generalized walking effort. Because equivalent walking distance represents the extra effort required to overcome obstacles, it can be used as an indicator of the quality of pedestrian facilities. Among the five walkway networks analyzed, the average equivalent walking distance was between 20% and 39% longer than the actual distance.
Activity and Travel Changes of Users of Job Access Transportation Service
Authors: Thakuriah Piyushimita (Vonu) , Sriraj P. S. , Sööt Siim , Liao Yihua , Berman Joost Gideon
Published: May 2018

The Job Access and Reverse Commute (JARC) program of the FTA provides funding to improve the access to and from jobs for welfare recipients and low-income individuals. The objective of the study was to develop a comprehensive profile of JARC service riders on several economic, social, perceptual, and travel-related indicators on the basis of a data set that was collected by the authors from riders of fixed-route and demand-responsive services in 23 locations across the country that were funded by this program. The economic indicators considered include incomes of riders, full-and part-time work status, employment tenure, reported changes in employment status (transitioning from unemployment to employment), and changes in wages incurred after using the service. Social indicators include vehicle ownership, driver's license, and educational attainment. Where possible, JARC service riders were compared with a national sample of automobile and transit users; the data for these measures were obtained from the decennial census. Two measures of perceived service dependency that indicate the importance of the service to the riders are discussed. In addition, a profile of travel-related changes incurred by riders as a result of service use is developed, including changes in mode of travel and travel times. Many of these indicators are differentiated on the basis of type of area and type of service. This analysis brings a user perspective into the discussion about low-income employment transportation services and highlights the diversity of impacts that job access transportation is having on the work and nonwork activities of low-income riders.
Low Income, Public Transit, and Mobility
Authors: Giuliano Genevieve
Published: May 2018

A fundamental justification for transit subsidies in the United States is to provide a basic level of mobility to all persons, especially the transportation disadvantaged: those who are either unwilling or unable to drive or who do not have access to a car. Yet even among the disadvantaged, most travel is by private vehicle. This paper examines the role of transit in the daily travel patterns of low-income households. Public transit is used for only a small portion of travel, and those who use transit regularly have the lowest level of mobility among all population segments. Attitudinal data indicate dissatisfaction with public transit, suggesting that current trends are likely to continue. Retaining existing markets by improving service frequency and quality in high-demand markets, exploring more effective ways of providing transit in low-demand markets, and expanding transit to serve off-peak and off-direction commutes would make transit a more attractive option for everyone.
Performance-Driven Transit Funding Model
Authors: Sousa Paul , Miller Eric J.
Published: May 2018

This paper presents a new funding model for urban transit systems. The model is performance driven in that it captures the performance of transit systems in attracting riders in a cost-effective manner and recognizes that transit system funding needs vary with transit systems’ scale of operations. The model also allocates funding on a weighted per capita basis and thereby addresses equity concerns. Recent data for Canadian transit systems are used to illustrate the application of this funding model to real-world operations.
Contracting Practice in Fixed-Route Transit Service
Authors: Iseki Hiroyuki , Ford Amy , Factor Rachel J.
Published: May 2018

Contracting plays a significant role in U.S. public transit provision, but there is a gap between the majority of quantitative studies that report significant cost savings from contracting and the few qualitative studies that consider the political nature of an agency's decision about contracting. To fill this gap, the authors systematically examined agency decisions about contracting, by interviewing managers and directors at 13 California transit agencies. In interviews with agencies of various sizes and blends of contracted and in-house services, it was found that agencies have responded differently to fiscal pressures and to contracting as a provision strategy. Some have readily adopted contracting to provide all services, while others have used different strategies, such as part-time labor and varying wage scales, to enhance their cost-efficiency. Those responses are a result not just of economic analysis but also of the agency's institutional environment, relationship with its labor union, and the political and economic contexts in which it operates. This study broadens the current understanding of contracting as practiced by transit agencies today–-in particular, why agencies choose to contract or not and how agencies have used both contracting and other means to respond to financial pressure. The findings reemphasize that it is important for an individual transit agency to assess carefully its service lines and various measures of increasing cost-efficiency, and to maintain a cooperative relationship with its unions to determine an appropriate level of contracting for its own operating environment.
After September 11, 2001
Authors: Eder Aaron
Published: May 2018

On September 11, 2001 (9/11), terrorists turned commercial aircraft into missiles and directed them toward high-rise and federal buildings, striking the World Trade Center and the Pentagon. After this tragic event, Congress's attention was naturally focused on airport security, and for good reason: the attacks happened via the aviation system. Yet an equivalent amount of attention was not given to the nation's public transportation system. To address this issue, the FTA, an organization within the U.S. Department of Transportation, began an ambitious five-part security initiative to improve the security of America's public transportation systems and assist their oversight agencies in addressing these new threats. The objectives of this paper are to reveal the vulnerability of America's transit system, identify typical pre–9/11 security planning, and show how the terrorist attacks that occurred on 9/11 have changed the way in which government and transit agencies address security concerns. An analysis of post–9/11 security measures adopted by the FTA; New York City Transit, New York; Washington Metropolitan Area Transit Authority, D.C.; and the San Francisco Bay Area Rapid Transit, California, is provided. A case study of the Tri-County Metropolitan Transportation District of Oregon is included to reveal how this agency in particular has responded to the threats that public transportation agencies face.
Transit Service Integration Practices
Authors: Miller Mark A. , Englisher Larry , Kaplan Bruce , Halvorsen Rick
Published: May 2018

This paper presents the findings of an investigation of transit service integration practices in the United States. A review of industry literature identified the various types of service integration practices that have been and are being implemented, including infrastructure, schedule, fare payment, information, and special events and emergency conditions integration. In addition, the review revealed how the introduction of such practices is part of overall changes in transit properties’ way of conducting business. The research made use of a two-stage survey of transit agencies that have implemented specific practices. An initial survey cast a wide net to identify innovative practices by 96 agencies across the country. A subsequent survey targeted specific examples of each type of practice and addressed the objectives of the practices, agency responsible for promoting integration, effectiveness of the practices, measures of effectiveness, barriers faced by implementers, and lessons learned. While there has been little formal evaluation of these practices by transit agencies, the predominant view is that transit integration supports the overall goals of the transit agency and provides substantial benefits to customers. Data to support impact evaluation are limited; however, several case studies were performed to probe integration practices in more depth. Transit agencies that have implemented integration practices have been able to overcome barriers to coordination and integration and have made a number of trailblazing efforts.