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

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

Study on pedestrian crossing behavior at signalized intersections

A clear understanding of pedestrian crossing behavior under mixed traffic conditions is needed for providing necessary infrastructure and also for enhancing pedestrian safety at signalized intersections. This paper attempts to analyze the crossing behavior of pedestrians like crossing speed, compliance with signal, and pedestrian-vehicular interaction under mixed traffic conditions and to identify the influencing factors based on statistical tests. 775 pedestrian samples were observed from three signalized intersections in Mumbai, India for analyzing crossing behaviors and the significant factors affecting traffic signal compliance by pedestrians were identified by conducting Pearson’s correlation coefficient test, ANOVA test, and Student t test. Factors influencing pedestrian crossing speed had been studied and a design crossing speed had been determined for old and adult pedestrians at 0.95 m/s and 1.12 m/s respectively. Logistic regression models had been developed in which the odds of pedestrian violation and interactions were modeled and verified. This study can help researchers and practitioners to understand pedestrian crossing behavior at signalized intersections and develop pedestrian delay models under mixed traffic conditions

Multivariate analysis of following and filtering manoeuvres of Motorized Two Wheelers in mixed traffic conditions

Mixed traffic conditions present a complex problem for analysis by transportation engineers and policymakers, due to the inherent heterogeneity and lane indiscipline. The chaotic arrangements make it difficult to identify and analyze basic riding behaviour such as following and filtering. Moreover, the smaller lateral dimensions of Motorized Two Wheelers (MTWs) and their higher manoeuvreability add to the difficulty. Presence of different types of vehicles in traffic mix, following the leader with or without obliqueness, filtering through tight pores between leader vehicles, etc. are some of the aspects that require special attention. In this respect, this study is aimed at investigating the attributes related to following and filtering manoeuvres of MTWs in such disordered traffic conditions. Real world data from two Indian cities was used for the analysis, which showed that the behaviour of MTWs is heavily influenced by the type of leader vehicle(s), Clear Lateral Gap (CLG), speed, etc. Safety analysis carried out using Time-To-Collision (TTC) showed that about 8.2% of the interactions were risky. Support Vector Machine (SVM) technique was used to investigate the choice of filtering based on Clear Lateral Gap (CLG) and relative speed. Moreover, analysis of the observed parameters was conducted to obtain their specific distributions based on leader vehicle type, following regime and choice of filtering. The analysis will give directions for further research on developing driving behaviour models of MTWs in mixed traffic. The results will also find potential application in traffic flow theories, safety studies, microsimulation, implementation of MTW infrastructure, etc

Evaluation of pedestrian mid-block road crossing behaviour using artificial neural network

Pedestrians usually cross the road at mid-block locations in India because of the ease and convenience to reach their destination as compared to intersection locations. It is important to evaluate the pedestrian gap acceptance behavior at mid-block locations because of inadequate vehicular gaps under mixed traffic condition, which translates into the pedestrian road crossing behavior. The present study examines the pedestrian gap acceptance behaviour by employing an artificial neural network (ANN) model for understanding the decision making process of pedestrians, i.e., acceptance or rejection of vehicular gaps at a mid-block location. From the results it has been found that the pedestrian rolling gap, frequency of attempt, vehicular gap size, pedestrian speed change condition and vehicle speed have major role in pedestrian gap acceptance. These results can lead to a better design of pedestrian crossing facilities where adequate gaps are not available in vehicular flow at mid-block crosswalk locations

Modeling over speeding behavior of vehicles using a random parameter negative binomial approach: A case study of Mumbai, India

Over speeding is one of the most common factors contributing to road accidents leading to traffic-related injuries and deaths. Understanding determinants of over speeding behavior is an important step toward enhancing road safety and developing robust intervention strategies. Moreover, there is a need to extend this knowledge with respect to developing countries, where there is a significant variation in the operating speeds of the vehicles owing to the heterogeneous traffic conditions. The present study captured the speeding behavior of the vehicles in Mumbai, India, during the years 2017 and 2018 using roadside observational surveys along with the spatial and temporal attributes of the selected locations. This study investigates the combined effect of temporal and spatial attributes on the over speeding frequency. A random parameter negative binomial model is developed utilizing the observational data to explain the over speeding behavior of the vehicles at the selected count locations. The developed model accounts for unobserved heterogeneity across the over speeding count locations based on temporal, road geometric, and built environment attributes. The study results confirm the presence of heterogeneity in the over speeding behavior of the vehicles at the count locations. In terms of policy implications, results suggest that temporary speed calming strategies could be adopted during the non-peak hours and on weekends. Similarly, deploying speed humps, rumble strips, or adopting law enforcement strategies can circumvent over speeding behavior on arterial roads. Lastly, developing well-connected roads with frequent presence of intersections and traffic signals can be another strategy applicable for such behavior

Modelling modal shift due to the enhanced level of bus service

This study is concerned with the estimation of the probable shift of auto-rickshaw (three wheeled motorized para-transit vehicle) users to the bus due to an increase in its level of service after providing exclusive bus lanes on Indian city roads carrying heterogeneous traffic. The quantum of an increase in the level of bus service due to the introduction of an exclusive bus lane was determined using a recently developed simulation model of heterogeneous traffic flow. The data on other factors (variables) that might cause modal shift from the auto-rickshaw to the bus was collected conducting a home-interview survey based on the stated preference approach. A binary logit model of mode-choice was then calibrated using the collected data and the model was also validated using a holdout sample. A mode-choice probability curve to depict the possible shift of auto-rickshaw users to the bus is developed taking difference in the travel times of two-modes as the basis to serve as a user friendly tool to analyze the possible modal shift for a wide range of the values of the involved variables