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.

Quantitative PCR assay of sewage-associated Bacteroides markers to assess sewage pollution in an urban lake in Dhaka, Bangladesh

This paper aimed to assess the magnitude of sewage pollution in an urban lake in Dhaka, Bangladesh by using Quantitative PCR (qPCR) of sewage-associated Bacteroides HF183 markers. PCR was also used for the quantitative detection of ruminant wastewater-associated CF128 markers along with the enumeration of traditional fecal indicator bacteria, namely, enterococci. The number of enterococci in lake water samples ranged from 1.1 x 104 to 1.9 x 105 CFU/100 ml of water. From the 20 water samples tested, 14 (70%) and 7 (35%) were PCR positive for the HF183 and CF128 markers, respectively. The numbers of the HF183 and CF128 markers in lake water samples were 3.9 x 104 to 6.3 × 107 and 9.3 x 103 to 6.3 x 105 genomic units (GU)/100 ml of water, respectively. The high numbers of enterococci and the HF183 markers indicate sewage pollution and potential health risks to those who use the lake water for non-potable purposes such as bathing and washing clothes. This is the first study that investigated the presence of microbial source tracking (MST) markers in Dhaka, Bangladesh where diarrhoeal diseases is one of the major causes of childhood mortality. The molecular assay as used in this study can provide valuable information on the extent of sewage pollution, thus facilitating the development of robust strategies to minimise potential health risks.