Majid Sarvi

Using Automatic Vehicle Identification Data to Gain Insight into Travel Time Variability and Its Causes

Unreliable transport systems cause stress and anxiety for travelers and create difficulties for authorities managing network operations, This study conducted a comprehensive investigation of travel time distributions in terms of various time windows based on extensive automatic vehicle identification data collected from the CityLink Tollway in Melbourne, Australia. The study also examines the components of travel time variability and explores their relationships. Given the number of factors affecting travel time variability and their interaction effects, multiple regression analysis is used to quantify the contribution of the various sources to the variability in travel time. Application of the methodology to two groups of data—namely, travel times in morning peak and afternoon peak—demonstrates that they have distinctive sources of variability. Morning peak travel times vary mostly because of driver-related factors, specifically lane choice decisions, whereas 25% of the variability of travel times in the...

Enhancing the safety of pedestrians during emergency egress: Can we learn from biological entities?

It may be possible to use nonhuman biological entities for empirical study of pedestrian crowds under emergency conditions. A literature review is used to examine how the study of mass movement of organisms might enhance the safety of pedestrians during emergency egress. Recent findings from experiments with panicking ants are presented as examples, with two scenarios, of how such experiments can be used as a basis for the design of solutions to ensure safe egress of pedestrians in emergencies. Although the experiments are still in progress and it is too early to draw definitive conclusions with statistical significance, some preliminary results show promise in using ants to test models for pedestrian traffic in emergency conditions. Because of the lack of complementary data during emergency or panic-inducing situations, experiments such as these with ants provide alternate empirical ways to test whether designs developed by means of mathematical models may actually be efficacious and improve the safety of pedestrians.

Microsimulation of Freeway Ramp Merging Processes Under Congested Traffic Conditions

This paper describes a microsimulation program developed to study freeway ramp merging phenomena under congested traffic conditions. The results of extensive macroscopic and microscopic studies are used to establish a model for the behavior of merging drivers. A theoretical framework for modeling the ramp and freeway lag driver acceleration-deceleration behavior guided the model development. This methodology uses the stimuli-response psychophysical concept as a fundamental rule and is formulated as a modified form of the conventional car-following models. Data collected at the two merging points are used to calibrate the hypothesized ramp and freeway lag vehicle acceleration models. Drawing on this behavioral model, the freeway merging capacity simulation program (FMCSP) is developed to simulate actual traffic conditions. This model evaluates the capacity of a merging section for a given geometric design and flow condition. Validation of FMCSP is performed using the observed flow, vehicle trajectories, and lane-changing maneuvers. The simulation model is applied to investigate a variety of merging strategies. The results indicated that the FMCSP is capable of simulating the actual traffic conditions of congested freeway ramp merging sections and will aid in the development of traffic management strategies for complex freeway ramp merging areas.

Simulation of safety: A review of the state of the art in road safety simulation modelling

Recent decades have seen considerable growth in computer capabilities, data collection technology and communication mediums. This growth has had considerable impact on our ability to replicate driver behaviour and understand the processes involved in failures in the traffic system. From time to time it is necessary to assess the level of development as a basis of determining how far we have come. This paper sets out to assess the state of the art in the use of computer models to simulate and assess the level of safety in existing and future traffic systems. It reviews developments in the area of road safety simulation models. In particular, it reviews computer models of driver and vehicle behaviour within a road context. It focuses on stochastic numerical models of traffic behaviour and how reliable these are in estimating levels of safety on the traffic network. Models of this type are commonly used in the assessment of traffic systems for capacity, delay and general performance. Adding safety to this assessment regime may allow more comprehensive assessment of future traffic systems. To date the models have focused primarily on vehicular traffic that is, cars and heavy vehicles. It has been shown that these models have potential in measuring the level of conflict on parts of the network and the measure of conflict correlated well with crash statistics. Interest in the prediction of crashes and crash severity is growing and new models are focusing on the continuum of general traffic conditions, conflict, severe conflict, crash and severe crashes. The paper also explores the general data types used to develop, calibrate and validate these models. Recent technological development in in-vehicle data collection, driver simulators and machine learning offers considerable potential for improving the behavioural base, rigour and application of road safety simulation models. The paper closes with some indication of areas of future development.

Nest architecture and traffic flow: Large potential effects from small structural features

1. Research on human pedestrian dynamics predicts that seemingly small architectural features of the surroundings can have large effects on the behaviour of crowds and the flow of pedestrian traffic, particularly when a crowd is panicked. This theoretical framework might usefully be applied to the study of collective movement within subterranean nests of social insects.

An Integrated Framework to Predict Bus Travel Time and Its Variability Using Traffic Flow Data

Information about bus travel time and its variability is a key indicator of service performance, and it is valued by passengers and operators. Despite the important effect of traffic flow on bus travel time, previous predictive approaches have not fully considered a traffic measure making their predictions unresponsive to the dynamic changes in traffic congestion. In addition, existing methodologies have primarily concerned predicting average travel time given a certain set of input values. However, predicting travel-time variability has not received sufficient attention in previous research. This article proposes an integrated framework to predict bus average travel time and its variability on the basis of a range of input variables including traffic flow data. The framework is applied using GPS-based travel-time data for a bus route in Melbourne, Australia, in conjunction with dynamic traffic flow data collected by the Sydney Coordinated Adaptive Traffic Systems loop detectors and a measure of schedule adherence. Central to the framework are two artificial neural networks that are used to predict the average and variance of travel times for a certain set of input values. The outcomes are then used to construct a prediction interval corresponding to each input value set. The article demonstrates the ability of the proposed framework to provide robust prediction intervals. The article also explores the value that traffic flow data can provide to the accuracy of travel-time predictions compared with when either temporal variables or scheduled travel times are the base for prediction. While the use of scheduled travel times results in the poorest prediction performance, incorporating traffic flow data yields minor improvements in prediction accuracy compared with when temporal variables are used.

New Methodology for Optimizing Transit Priority at the Network Level

A new methodology for optimizing transit road space priority at the network level is proposed. Transit vehicles carry large numbers of passengers within congested road space efficiently. This aids justification of transit priority. Almost all studies that have investigated transit priority lanes focus at a link or an arterial road level, and no study has investigated road space allocation for priority from a network perspective. The aim of the proposed approach is to find the optimum combination of exclusive lanes in an existing operational transport network. Mode share is assumed variable, and an assignment is performed for both private and transit traffic. The problem is formulated by using bilevel programming, which minimizes the total travel time. The approach is applied to an example network and the results are discussed. The approach can identify the optimal combination of transit priority lanes and achieve the global optimum of the objective function. Areas for further development are discussed.

Evaluating the Congestion Relief Impacts of Public Transport in Monetary Terms

Traffic congestion is a major urban transport problem. Efficient public transport (PT) can be one of the potential solutions to the problem of urban road traffic congestion. Public transport systems can carry a significant amount of trips during congested hours, improving overall transportation capacity, and can release the burden of excess demand on congested road networks. This paper presents a comparative assessment of international research valuing the congestion relief impacts of PT. It explores previous research valuing congestion relief impacts and examines secondary evidence demonstrating changes in mode split associated with changes in public transport. The research establishes a framework for estimating the monetary value of the congestion reduction impacts of public transport. Congestion relief impacts are valued at between 4.4 and 151.4 cents (Aus

Biologically Inspired Modeling Approach for Collective Pedestrian Dynamics Under Emergency Conditions

, 2008) per marginal vehicle km of travel, with an average of 45.0 cents. Valuations are higher for circumstances with greater degrees of traffic congestion and also where both travel time and vehicle operating cost savings are considered. A simplified congestion relief valuation model is presented to estimate the congestion relief benefits of PT based on readily -available transport data. Using the average congestion valuation and mode shift evidence, the model has been applied to a number of cities to estimate the monetary value of the congestion relief impact of public transport. Overall, the analysis presents a simplified method to investigate the impact of public transport on traffic congestion.

Using ITS to Improve the Capacity of Freeway Merging Sections by Transferring Freight Vehicles

An interesting aspect of collective dynamics of various biological entities is that they are emergent systems. A literature review examines how the fundamental principles of emergent systems can be applied to model collective pedestrian dynamics. A simulation model is then proposed on the basis of modifications of collective animal dynamics. Recent findings from experiments with panicking Argentine ants are presented to illustrate how such experiments can be used to study collective pedestrian traffic. Despite the difference in speed, size, and other biological details of the panicking individuals, the model proved capable of explaining the collective dynamics. The models robustness is demonstrated by comparing its ability to simulate the collective traffic of panicking ants as well as collective human traffic. The lack of complementary data during emergency and panic situations is a challenge for model development. Empirical data from biological organisms can play a valuable role in the development of pedestrian traffic models from a theoretical perspective and in instances in which model validation is based on empirical data collected by video. Such a novel framework, which is based on complementary expertise, can be used as a basis for the design of solutions for the safe egress of pedestrians.