Analytical modeling and sensitivity analysis for travel time estimation on signalized urban networks

This paper presents a model for estimation of average travel time and its variability on signalized urban networks using cumulative plots. The plots are generated based on the availability of data: a) case-D, for detector data only; b) case-DS, for detector data and signal timings; and c) case-DSS, for detector data, signal timings and saturation flow rate. The performance of the model for different degrees of saturation and different detector detection intervals is consistent for case-DSS and case-DS whereas, for case-D the performance is inconsistent. The sensitivity analysis of the model for case-D indicates that it is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

Urban dynamic origin-destination matrices estimation

The aim of this paper is to explore a new approach to obtain better traffic demand (Origin-Destination, OD matrices) for dense urban networks. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified: traffic assignment details for complex urban network and lacks in dynamic approach. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi-level approach will be used, the Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from mesoscopic traffic simulator and the Upper level (matrix adjustment) problem will proceed to an OD estimation using optimization Kalman filtering technique. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First results of the proposed approach and remarks are presented.

Estimation of travel time on urban networks with midlink sources and sinks

This paper presents a methodology for estimation of average travel time on signalized urban networks by integrating cumulative plots and probe data. This integration aims to reduce the relative deviations in the cumulative plots due to midlink sources and sinks. During undersaturated traffic conditions, the concept of a virtual probe is introduced, and therefore, accurate travel time can be obtained when a real probe is unavailable. For oversaturated traffic conditions, only one probe per travel time estimation interval—360 s or 3% of vehicles traversing the link as a probe—has the potential to provide accurate travel time.

Safety-restraint use rate as function of law enforcement and other factors : preliminary analysis

Persistent use of safety restraints prevents deaths and reduces the severity and number of injuries resulting from motor vehicle crashes. However, safety-restraint use rates in the United States have been below those of other nations with safety-restraint enforcement laws. With a better understanding of the relationship between safety-restraint law enforcement and safety-restraint use, programs can be implemented to decrease the number of deaths and injuries resulting from motor vehicle crashes. Does safety-restraint use increase as enforcement increases? Do motorists increase their safety-restraint use in response to the general presence of law enforcement or to targeted law enforcement efforts? Does a relationship between enforcement and restraint use exist at the countywide level? A logistic regression model was estimated by using county-level safety-restraint use data and traffic citation statistics collected in 13 counties within the state of Florida in 1997. The model results suggest that safety-restraint use is positively correlated with enforcement intensity, is negatively correlated with safety-restraint enforcement coverage (in lanemiles of enforcement coverage), and is greater in urban than rural areas. The quantification of these relationships may assist Florida and other law enforcement agencies in raising safety-restraint use rates by allocating limited funds more efficiently either by allocating additional time for enforcement activities of the existing force or by increasing enforcement staff. In addition, the research supports a commonsense notion that enforcement activities do result in behavioral response.

Macular function in tilted disc syndrome

Tilted disc syndrome can cause visual field defects due to an optic disc anomaly. Recent electrophysiological findings demonstrate reduced central outer retinal function with ophthalmoscopically normal maculae. We measured macular sensitivity with the microperimeter and performed psychophysical assessment of mesopic rod and cone luminance temporal sensitivity (critical fusion frequency)in a 52-year-old male patient with tilted disc syndrome and ophthalmoscopically normal maculae. We found a marked reduction of sensitivity in the central 20 degrees and reduced rod- and cone-mediated mesopic visual function. Our findings extend previous electrophysiological data that suggest an outer retinal involvement of cone pathways and present a case with rod and cone impairment mediated via the magnocellular pathway in uncomplicated tilted disc syndrome.

Prevalence of upper-body symptoms following breast cancer and its relationship with upper-body function and lymphoedema

This investigation describes the prevalence of upper-body symptoms in a population-based sample of women with breast cancer (BC) and examines their relationships with upper-body function (UBF) and lymphoedema, as two clinically important sequelae. Australian women (n=287) with unilateral BC were assessed at three-monthly intervals, from six to 18 months post-surgery (PS). Participants reported the presence and intensity of upper-body symptoms on the treated side. Objective and self-reported UBF and lymphoedema (bioimpedance spectroscopy) were also assessed. Approximately 50% of women reported at least one moderate-to-extreme symptom at 6- and at 18-months PS. There was a significant relationship between symptoms and function (p<0.01), whereby perceived and objective function declined with increasing number of symptoms present. Those with lymphoedema were more likely to report multiple symptoms and presence of symptoms at baseline increased risk of lymphoedema (ORs>1.3, p=0.02). Although, presence of symptoms explained only 5.5% of the variation in the odds of lymphoedema. Upper-body symptoms are common and persistent following breast cancer and are associated with clinical ramifications, including reduced UBF and increased risk of developing lymphoedema. However, using the presence of symptoms as a diagnostic indicator of lymphoedema is limited.

Estimation of WGEN Weather Generation Parameters in Arid Climates

This research discusses some of the issues encountered while developing a set of WGEN parameters for Chile and advice for others interested in developing WGEN parameters for arid climates. The WGEN program is a commonly used and a valuable research tool; however, it has specific limitations in arid climates that need careful consideration. These limitations are analysed in the context of generating a set of WGEN parameters for Chile. Fourteen to 26 years of precipitation data are used to calculate precipitation parameters for 18 locations in Chile, and 3–8 years of temperature and solar radiation data are analysed to generate parameters for seven of these locations. Results indicate that weather generation parameters in arid regions are sensitive to erroneous or missing precipitation data. Research shows that the WGEN-estimated gamma distribution shape parameter (α) for daily precipitation in arid zones will tend to cluster around discrete values of 0 or 1, masking the high sensitivity of these parameters to additional data. Rather than focus on the length in years when assessing the adequacy of a data record for estimation of precipitation parameters, researchers should focus on the number of wet days in dry months in a data set. Analysis of the WGEN routines for the estimation of temperature and solar radiation parameters indicates that errors can occur when individual ‘months’ have fewer than two wet days in the data set. Recommendations are provided to improve methods for estimation of WGEN parameters in arid climates.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites