Pedestrian perception-based level-of-service model at signalized intersection crosswalks

"jats:p"Pedestrian level of service (PLOS) is an important measure of performance in the analysis of existing pedestrian crosswalk conditions. Many researchers have developed PLOS models based on pedestrian delay, turning vehicle effect, etc., using the conventional regression method. However, these factors may not effectively reflect the pedestrians’ perception of safety while crossing the crosswalk. The conventional regression method has failed to estimate accurate PLOS because of the primary assumption of an arbitrary probability distribution and vagueness in the input data. Moreover, PLOS categories in existing studies are based on rigid threshold values and the boundaries that are not well defined. Therefore, it is an important attempt to develop a PLOS model with respect to pedestrian safety, convenience, and efficiency at signalized intersections. For this purpose, a video-graphic and user perception surveys were conducted at selected nine signalized intersections in Mumbai, India. The data such as pedestrian, traffic, and geometric characteristics were extracted, and significant variables were identified using Pearson correlation analysis. A consistent and statistically calibrated PLOS model was developed using fuzzy linear regression analysis. PLOS was categorized into six levels ("jats:italic"A"/jats:italic"–"jats:italic"F"/jats:italic") based on the predicted user perception score, and threshold values for each level were estimated using the fuzzy "jats:italic"c"/jats:italic"-means clustering technique. The developed PLOS model and threshold values were validated with the field-observed data. Statistical performance tests were conducted and the results provided more accurate and reliable solutions. In conclusion, this study provides a feasible alternative to measure pedestrian perception-based level of service at signalized intersections. The developed PLOS model and threshold values would be useful for planning and designing pedestrian facilities and also in evaluating and improving the existing conditions of pedestrian facilities at signalized intersections. Document type: Articl

Bus Priority on Roads Carrying Heterogeneous Traffic: a Study using Computer Simulation

The desirable goal in passenger transportation is moving more people in fewer vehicles. This goal, in respect of road transport, can be attained by encouraging public transport modes like buses by assigning priority. This paper is concerned with application of micro simulation technique to study the impact of provision of reserved bus lanes on the flow of highly heterogeneous traffic on urban roads. The specific objectives of this paper are (i) to modify and validate a newly developed model of heterogeneous traffic flow using field observed data and (ii) to apply the validated simulation model to study the impact of exclusive bus lanes introduced on urban arterials for a wide range of traffic volume levels. The impact of introduction of an exclusive bus lane is measured in terms of the reduction in speed of other categories of motor vehicles, due to the consequent reduction in road space, over a wide range of traffic volume. The main finding of this paper is, that if an exclusive bus lane is provided under highly heterogeneous traffic conditions,(prevailing in Indian cities), then, the maximum permissible volume to capacity ratio that will ensure a level of service of C for the traffic stream comprising all the motor vehicles, except the buses, is about 0.53

Influence of Basin Geometry on Coagulation-flocculation�

Environmental Engineerin

Pedestrian safety evaluation of signalized intersections using surrogate safety measures

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections

A new approach to estimate pedestrian delay at signalized intersections

Enhancing pedestrian safety and improving the design standards of pedestrian facilities at signalized intersection requires a clear understanding of pedestrian delay model and pedestrian crossing behaviours under mixed traffic condition. The existing delay models do not consider the behavioural constrains of pedestrians. This research has been undertaken with the aim of developing a suitable pedestrian delay model for signalized intersection crosswalks, based on considering actual pedestrian crossing behaviours. The required model parameters were extracted from the video-graphic survey conducted for the selected four signalized intersections in Mumbai (India). Crossing behaviours of pedestrians were examined through field data in terms of pedestrian arrival pattern, crossing speed, compliance behaviour and pedestrian–vehicular interactions. Based on pedestrian crossing behaviour analysis results, two new pedestrian delay estimation models were developed and the models were validated by comparing with field and existing model values. The performance level of the proposed models is showing more precise and reliable solutions. The first pedestrian delay model is developed on the basis of compliance behaviour, has two components, such as waiting time delay and crossing time delay. This model can be used to evaluate pedestrian Level Of Service (LOS) and signal timing optimization. The second developed pedestrian delay model is based on noncompliance behaviour, has three components, such as waiting time delay, crossing time delay, and pedestrian–vehicular interaction delay. This model can also be used to evaluate the quality of pedestrian flow, estimating accurate pedestrian delay and LOS for local conditions, which is representative of the prevailing pedestrian condition. First published online 29 March 201

Modelling Modal Shift from Personal Vehicles to Bus on Introduction of Bus Priority Measure

Abstract: This study is concerned with estimation of the probable shift of personal vehicle users to bus due to the increase in its level of service as a result of the provision of exclusive bus lanes on Indian city roads. The quantum of increase in level of service of bus due to introduction of exclusive bus lanes was determined using a recently developed simulation model for heterogeneous traffic flow. The data on the other factors (variables) that might cause modal shift from personal vehicles to bus were collected through home-interview survey using a stated preference approach. Mode-choice models to explain the shift behaviour of the users of motorised two-wheelers, auto-rickshaws, and cars to buses are developed. Modal shift probability curves are also developed to serve as a user friendly tool to analyze the probable modal shift for a wide range of the variables

PyEvolve: a toolkit for statistical modelling of molecular evolution

BACKGROUND: Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences – ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation. RESULTS: Here we describe the implementation of PyEvolve, a toolkit for the application of existing, and development of new, statistical methods for molecular evolution. We present the object architecture and design schema of PyEvolve, which includes an adaptable multi-level parallelisation schema. The approach for defining new methods is illustrated by implementing a novel dinucleotide model of substitution that includes a parameter for mutation of methylated CpG's, which required 8 lines of standard Python code to define. Benchmarking was performed using either a dinucleotide or codon substitution model applied to an alignment of BRCA1 sequences from 20 mammals, or a 10 species subset. Up to five-fold parallel performance gains over serial were recorded. Compared to leading alternative software, PyEvolve exhibited significantly better real world performance for parameter rich models with a large data set, reducing the time required for optimisation from ~10 days to ~6 hours. CONCLUSION: PyEvolve provides flexible functionality that can be used either for statistical modelling of molecular evolution, or the development of new methods in the field. The toolkit can be used interactively or by writing and executing scripts. The toolkit uses efficient processes for specifying the parameterisation of statistical models, and implements numerous optimisations that make highly parameter rich likelihood functions solvable within hours on multi-cpu hardware. PyEvolve can be readily adapted in response to changing computational demands and hardware configurations to maximise performance. PyEvolve is released under the GPL and can be downloaded from http://cbis.anu.edu.au/software webcite

Driver behaviour modelling of vehicles at signalized intersection with heterogeneous traffic

Roads network is composed of mid-blocks and intersections. The part where two roads cross is called an intersection whereas the straight sections without intersection or any other interuptions is called mid-block. It can be observed that the vehicles on the mid-blocks tend to achieve their free-flow speeds while those at the intersections are forced to decelerate. Modelling of these sections needs to separate the intersections from mid-block. Further, drivers behave differently at these two locations. Present study attempts to separate the intersection zone of influence (IZOI) and mid-block using the manoeuvring characteristics of drivers in terms of acceleration/deceleration. These were captured through a global positioning system (GPS) device in the vehicle after sighting a red signal at the intersection. Further, this study also tried to observe whether different classes of drivers such as aggressive, normal or timid drivers, based on acceleration/deceleration behaviour exists. A junction with 1-km straight stretch in R. K. Puram New Delhi (India) was chosen for the study to find the IZOI. After identifying IZOI a video data was collected in Mumbai (India) for a stretch more than 200-m long near intersection where the red signal was visible; This enabled observing the driver behaviour more closely. Around 900 drivers of different modes were analysed to understand their behaviour. It was found that cars start reducing its speed at 160 m, motorized three-wheelers at 124 m and buses start reducing their speeds at 98 m distance from the intersection. The driver behaviours were distinct in each of the mode (Bus, Car and motorized-there-wheelers), but it emerges that the drivers cannot be classified into finite number of clusters based on the fitted normal distribution. Thus it can be seen that there are no clearly demcarcated driver behaviours irrespective of the vehicle type, such as aggressive, normal and timid categories as the intersection approaches. A normal distribution model can classify the drivers satisfactorily

Do High Visibility Crosswalks Improve Pedestrian Safety? A Correlated Grouped Random Parameters Approach Using Naturalistic Driving Study Data

In this study, the effectiveness of High-Visibility Crosswalks (HVCs) in improving pedestrian safety at urban settings is assessed using SHRP2 (Second Strategic Highway Research Program) Naturalistic Driving Study (NDS) data. Various HVCs located at different positions on the roadway segment (mid-block vs end-of-block) and featuring different HVC marking designs (continental, bar-pair, and ladder) were selected for the assessment. As no pedestrian-vehicle crashes or conflicts were identified from the forward-facing videos and time series information of the SHRP2 Naturalistic Driving Study data, crash surrogate measures (i.e., speed; acceleration; throttle pedal actuation; and brake application) were employed to identify and analyze modifications in driving behavior at or near the HVCs.The surrogate measures were statistically modeled using a correlated grouped random parameters estimation framework. This can account for panel effects arising from multiple traversals undertaken by each participant, for the effect of unobserved characteristics, as well as for their unobserved correlations, which constitute possible misspecification issues of statistical modeling. The results of the analysis showed that the presence of HVC modifies driving behavior, thus reducing the risk of motor vehicle – pedestrian conflicts. Apart from the presence of HVC, the HVC type (ladder, continental or bar-pair), the HVC location (mid-block or end-of-block) and various driver, roadway and trip characteristics were found to affect the vehicle speed, acceleration, throttle pedal actuation, and brake application