Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

In-use measurement of the activity, fuel use, and emissions of eight cement mixer trucks operated on each of petroleum diesel and soy-based B20 biodiesel

In-use micro-scale fuel use and emission rates were measured for eight cement mixer trucks using a portable emission measurement system. Each vehicle was tested on petroleum diesel and B20 biodiesel. Average fuel use and emission rates increase monotonically versus engine manifold absolute pressure. A typical duty cycle includes loading at a cement plant, transit while loaded from the cement plant to work site, creeping in a queue of vehicles at the worksite, unloading, and transit without load from the site to the plant. For B20 versus petroleum diesel, there is no significant change in the rate of fuel use, CO₂ emissions, and NO emissions, and significant decreases in emissions for CO, hydrocarbons, and particulate matter. For loaded versus unloaded onroad travel, fuel use and CO₂ emissions rates are approximately 60% higher and the rates for other pollutants are approximately 30–50% higher. A substantial portion of cycle emissions occurred at the work site. Inter-vehicle and intra-cycle variability are also quantified using the micro-scale methodology.     

Fuzzy-logic-based incident detection for signalized diamond interchanges

This paper documents a fuzzy-logic-based incident detection algorithm for signalized urban diamond interchanges. The model is capable of detecting lane-blocking incidents whose effects are manifested by patterns of deterioration in traffic conditions that require adjustments in signal control strategies. As a component of a real-time traffic adaptive control system for signalized diamond interchanges, the algorithm feeds an incident report (i.e., the time, location, and severity of the incident) to the system's optimization manager, which uses that information to determine the appropriate signal control strategy.The performance of the model was studied using a simulation of an actual diamond interchange. The simulation study evaluated the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy-logic-based approach is considered promising.     

Induced traffic and economic appraisal

Economic appraisal of major roads in the UK is based on a set of standard procedures and conventions. A central assumption has been that the volume and pattern of traffic in any given year is independent of the quality of service offered by the network — the fixed trip matrix assumption. Failing to consider induced traffic can have serious consequences for the accuracy and robustness of the measured traffic benefits from road improvements. Assessment of the wider economic benefits of roads, which is an important political imperative for road investment, is also made more difficult. Two conclusions are reached. Variable trip matrix methods need to be introduced for the appraisal of major road schemes, and scheme appraisal needs to be complemented by a more strategic area-wide approach to evaluation. In responding to its advisory committee (SACTRA), the UK Department of Transport has accepted the first of these conclusions and is cautiously favourable to the second.     

Link choice proportions from trip distribution and assignment models: An overview and comparison

A number of estimation procedures have been suggested for the situation where a prior estimate of an origin-destination matrix is to be updated on the basis of recently-acquired traffic counts. These procedures assume that both the link flows and the proportionate usage of each link made by each origin-destination flow (referred to collectively as the link choice proportions) are known. This paper examines the possibility and methods for estimating the link choice proportions. Three methods are presented: (1) using ad hoc iteration between trip distribution and traffic assignment; (2) combining trip distribution and assignment in one step; (3) solving a new optimization problem in which the path flows are directly considered as variables and its optimal solution is governed by a logit type formula. The algorithms, covergencies and computational efficiencies of these methods are investigated. Results of testing the three methods on example networks are discussed.     

A stated preference examination of time of travel choice for a recreational trip

A stated preference experiment was performed in Calgary in Canada to examine how people are influenced in the selection of a departure time for a hypothetical trip to see a movie. A total of 635 complete observations were obtained. In each observation the respondent was presented with a set of possible departure time scenarios and asked to indicate the order of preference for these scenarios. Each scenario was described by specifying the automobile travel time, the expected arrival time relative to the movie start time, the parking cost, the probability of being at least ten minutes late for the movie and the length of time the movie had been running. This forced the respondent to trade off between conditions regarding these attributes. Age, gender and frequency of movie attendance were also recorded. The observations thus obtained were used to estimate the parameter values for a range of alternative utility functions in logit models representing this choice behaviour. The results indicate that all of the attributes included have significant effects on departure time choice in the situation being considered. They also indicate that travellers are prepared to arrive roughly two minutes early for each minute of travel time saved; that the money value of driving time for trips to recreational activities is about half that for trips to work; that one additional percent in the probability of arriving late is equivalent to roughly 0.20 Canadian dollars or 1.93 minutes drive time; and that there is a preference for a non-zero expected early arrival time regardless of the associated probability of arriving late. Some of these results are novel and others are consistent with findings for work trips in work done by others, which is seen to add credence to the approach being used here.     

Strava Metro data for bicycle monitoring: a literature review

ABSTRACT

Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality.     

Reported household gasoline purchasing experience: June 1979

A sample of 1000 households completed a questionnaire regarding difficulties encountered purchasing gasoline during the week 4–10 June 1979 and whether difficulties encountered purchasing gasoline affected household automobile tripmaking. Results of this survey were analyzed and it was found that the frequency of reporting purchasing difficulties varied directly with household income and inversely with the age of the household. The frequency of reporting that purchasing difficulties affected automobile trip-making varied directly with household income and inversely with the number of adults in the household. Further, although individual household response was highly sensitive to socioeconomic characteristics, the overall response to the survey would not have differed significantly had the socioeconomic mix of households been different.     

Junction interactions and monotonicity in traffic assignment

We consider the traffic equilibrium problem when the travel demand is inelastic and stationary in time. Junction interactions, which abound in urban road networks, are permitted. We prove that the set of equilibria (solutions to the assignment problem) is convex when certain monotonicity and continuity conditions are statisfied at each junction.     

TRAMS: Transit route animation and modelling by simulation

Public transport managers and operators face increasingly difficult problems in providing adequate levels of service at reasonable social and financial costs. A greater demand exists for analytical techniques which allow them to evaluate changes in operational strategies before committing themselves to implementation in the field. This paper describes the development of a discrete event simulation model for the analysis of on-street transit routes. The structure of the model is described and details are provided of the types of events which are explicitly modelled in the TRAMS package. The input requirements are described, and the modular nature of the simulation model is highlighted. The various options for output format are described, including the use of a computer graphics real-time animation option. The range of output performance measures are then discussed, and some comments on areas of application conclude the paper.