Development and evaluation of a statistically reliable traffic counting program

This paper reviews the existing procedures to compute the seasonal factors, growth factors, and the number of automatic traffic recorder stations (ATRs) for developing a statistically reliable traffic counting program. The review is based on, (i) theoretical evaluation of the procedures, (ii) analysis of the results obtained from applying these procedures to extensive real life data, and (iii) experience of past researchers with these methods. The paper primarily deals with existing statistical procedures for determining seasonal factors, since it is believed that these factors play the most important role in estimating Annual Average Daily Traffic (AADTs) from short counts. The procedure of cluster analysis (which is most commonly used to determine seasonal factors) is critically reviewed. The shortcomings of this method motivated the development of a different statistical procedure, based on regression analysis, to determine seasonal factors. It is shown that this newly developed method gives better results than the cluster analysis techniques. Furthermore, separate sections are dedicated to a thorough analysis of determination of number of ATR stations and computation of growth factors.     

Empirical analysis of short period traffic counts and their efficiency: the case of Indian traffic

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India.     

Analysing queueing at toll plazas using a coupled,multiple-queue,queueing system model: application to toll plaza design

A vehicle approaching a toll plaza observes the queues at each of the available toll-lanes before choosing which to join. This choice process, the arrival process of vehicles and the service characteristics of the toll-booths, affect the queues and delay the drivers. In this paper, queueing at a toll plaza is modelled as a multiple-queue queueing system where the arrival process to a queue (toll-lane) is dependent on the state of all the queues. In the past, such systems have been modelled mathematically only for two queues and are not applicable for toll plazas with three or more toll-lanes. The proposed model determines the steady-state probability density function (pdf) for the queues at large toll plazas. This study is used to determine the number of toll-lanes or the length of the upstream queueing area required to achieve certain user-specified levels-of-service. Expected delay and maximum queue length are used as level-of-service measures. Indicative design charts are also provided.     

Quantification of surrogate safety measure to predict severity of road crashes at median openings

Traffic safety assessment is an integral part of transportation engineering. In a developing country like India, it is observed that in every four second, one person gets injured in road crashes. Moreover, at median openings which are usually uncontrolled in India, the severity of road crashes increase many fold. This is due to the fact that neither lane discipline nor priority rule is followed at the median openings. Conventionally, road crash data reports were used to study and analyze traffic safety. However, the drawback of this traditional method is that a lot of accidents need to be recorded for analysis and to draw any conclusions and take necessary corrective measures. In developing countries like India, available accident data are based on reports submitted by the police department of respective state governments. The accuracy of these accident data details is highly questionable. Therefore, in the recent times surrogate traffic safety measures are being used to analyze traffic safety. Various surrogate traffic measures like Deceleration Time (DT), Time to Collision (TTC), Post Encroachment Time (PET), etc. are being used to examine road safety. These values are based on the temporal and spatial proximity between road-users during possible conflict situation. Among all the traffic safety measures, PET is regarded as the most reliable and most commonly used indicator. Therefore, in this study, PET across different traffic volume levels at median opening area is calculated. A critical safe ratio has been introduced to better analyze the traffic safety at median opening based on minimum stopping sight distance (SSD) as per IRC: 66–1976 and speed to PET ratio. Finally clustering technique has been used to define various severity indices for probable road crashes at median opening area. For this study, data has been collected from different median openings located on six-lane divided urban roads.     

Comprehensive pavement maintenance strategies for road networks through optimal allocation of resources

In order to maintain a growing road infrastructure at some minimum level of service, substantial resources are required on a recurrent basis. Of late, the available resources can no longer meet all the maintenance and rehabilitation demand even in wealthy nations. Hence, there is a need to develop a tool which will optimally allocate these resources in order to keep the road infrastructure as ‘healthy’ as possible. Further, this tool must acknowledge that maintenance needs are not only restricted to structural aspects but also extend to the functional- and safety-related aspects of a road. Here, such a comprehensive optimization tool is developed which when used will optimally allocate resources in order to maintain a healthy (from structural, functional, and safety standpoints) road network. The problem of determining the optimum maintenance and rehabilitation activities for individual road sections is formulated as a linear integer programming problem. Results from a case study using the proposed method show that the suggested maintenance and rehabilitation plans make sense from engineering and economic considerations.     

Microscopic Analysis of Cellular Automata Based Traffic Flow Models and an Improved Model

Abstract

A large number of cellular automata (CA) based traffic flow models have been proposed in the recent past. Often, the speed‐flow‐density relations obtained from these models are only presented and their apparent similarities with observed relations are cited as reasons for considering them as valid models of traffic flow. Hardly any attempt has been made to comprehensively study the microscopic properties (like time‐headway distribution, acceleration noise, stability in car‐following situations, etc.) of the simulated streams. This article proposes a framework for such evaluations. The article also presents the results from the evaluation of six existing CA‐based models. The results show that none of them satisfy all the properties. A new model proposed by the authors to overcome these shortcomings is briefly presented, and results supporting the improved performance of the proposed model are also provided.