Ata M. Khan

Modelling urban transportation emissions: role of GIS

In the development of methodology that can assist the decision-making process for reducing vehicle emissions in urban areas, the benefit of using geographic information systems (GIS) in enhancing the reliability of data is indeed significant. There are other positive features that could be used to enhance analyses and to prepare information in support of decision-making. These include: visualization of analysis results, improved communication with decision-makers, new analytical tools for testing transport technology innovations and investigating travel behaviour. This paper reports the methodological framework that is required for analysing the emission implications of measures that are intended to reduce vehicle emissions in urban transportation. A case study of the National Capital Region (NCR) Canada is used for illustration purposes. The overall framework for urban transportation planning, including emissions estimation, is introduced. The role of GIS is highlighted in terms of enhancing the reliability of data. Methodologies are noted that serve as an interface between travel analysis and emissions estimation. An emissions calculator is described that enables the estimation of air quality pollutants and greenhouse gas emissions. Finally, results of selected scenarios are presented.

The effects of telecommuting and intelligent transportation systems on urban development

This study examines the state of knowledge on the effects of telecommuting and intelligent transportation systems on location decisions of households and businesses and it defines the policy and planning implications for metropolitan areas. The study suggests an increased trend toward multinucleated urban structure where a number of urban satellite nodes, containing mixed business and residential land uses are located at some distance from the central core and along transportation corridors.

Bus running time prediction using a statistical pattern recognition technique

Abstract Given that real-time bus arrival information is viewed positively by passengers of public transit, it is useful to enhance the methodological basis for improving predictions. Specifically, data captured and communicated by intelligent systems are to be supplemented by reliable predictive travel time. This paper reports a model for real-time prediction of urban bus running time that is based on statistical pattern recognition technique, namely locally weighted scatter smoothing. Given a pattern that characterizes the conditions for which bus running time is being predicted, the trained model automatically searches through the historical patterns which are the most similar to the current pattern and on that basis, the prediction is made. For training and testing of the methodology, data retrieved from the automatic vehicle location and automatic passenger counter systems of OC Transpo (Ottawa, Canada) were used. A comparison with other methodologies shows enhanced predictive capability.

Reducing Traffic Density: The Experience of Hong Kong and Singapore

This article focuses on the road networks in Singapore and Hong Kong. Both have initiated innovative programs to restrain the demand for road space. The policies and methods for reducing traffic density are reviewed. The electronic road pricing (ERP) system now operating in Singapore is compared to both the Hong Kong ERP system of the late 1980s and early 1990s and Singapores Area Licensing Scheme of the same period. The article demonstrates how Singapores ERP optimizes the citys road network and thus saves a valuable urban resource - land.

Bayesian-Monte Carlo model for collision avoidance system design of cognitive connected vehicle

Cognitive connected vehicles will require a number of essential features that integrate intelligent technology and human factors, including collision avoidance advice and adaptive longitudinal control. This paper describes a self-calibrating adaptive model for aiding the design of a warning system for preventing rear and side swipe collisions. The cognitive vehicle is expected to have the capability of information on location and distance between vehicles obtained on-line. The location and distance information is used in association with a Monte Carlo simulation and Bayesian decision model to identify pre-crash condition. Here, the case of human control is covered and the system provides advice for avoiding rear or side swipe accidents while minimizing false alarms. The model structure and algorithm are presented and illustrative examples of distracted driving are provided.

Risk factors in toll road life cycle analysis

At present there is a very high level of interest in public–private partnerships in the provision and timely maintenance of highway infrastructure. Although in the past a number of jurisdictions around the world developed toll ring roads and sometimes radial roads in major urban areas, the current heightened interest in toll facilities is unprecedented, given that it even extends to the level of toll lanes. The experience of a number of existing public–private partnership type of toll facilities suggests that risk variables are encountered in the development, operations and maintenance/rehabilitation phases. According to literature sources, although the financial and research community are aware of the need to address risk, only a small number of practitioners carry out a detailed risk assessment. There could be a number of reasons for inaction. One of these is the lack of awareness of methodologies that address risk in key parts of the life cycle. This article identifies risk factors in the lifecycle analysis of a toll road and suggests measures to address risks. A methodological framework and constituent components are described while highlighting risk factors in the revenue estimation and maintenance/rehabilitation phases. Risk analysis methods, namely sensitivity analysis, Monte Carlo simulation and Bayesian statistical method are illustrated. The conclusions are drawn from the synthesis of information and analyses carried out on the merits of treating risk factors in toll road life cycle analysis.

Modelling Intelligent Transportation Systems and Their Implications for Climate Change

Intelligent transportation systems (ITS) have been promoted as a way to enhance transportation system performance through application of advanced technology to the planning, management, and operation of transportation services and infrastructure. Improvements in operational efficiency brought about through ITS may also have significant environmental benefits, including a reduction in Greenhouse Gas (GHG) emissions. Given the complex interactions which characterize the urban transport system, a comprehensive modelling framework is needed to fully understand the potential implications of ITS technologies from a climate change perspective. This paper reports on a research project that is currently being carried out to examine the operational and environmental benefits of adopting ITS measures in Ottawa, Ontario. One of the primary objectives of the project is to develop a realistic, integrated freeway / arterial network model which is capable of capturing the system-wide effects of ITS initiatives at a traffic operations level of detail using a traffic microsimulation approach. The model was implemented using the software INTEGRATION and is currently being used to analyze a variety of ITS measures, including variable message signs, incident management, en-route traveler information, in-vehicle navigation, and electronic toll collection.

Design of Real-Time Transition from Driving Assistance to Automation Function: Bayesian Artificial Intelligence Approach

Forecasts of automation in driving suggest that wide spread market penetration of fully autonomous vehicles will be decades away and that before such vehicles will gain acceptance by all stake holders, there will be a need for driving assistance in key driving tasks, supplemented by automated active safety capability. This paper advances a Bayesian Artificial Intelligence model for the design of real time transition from assisted driving to automated driving under conditions of high probability of a collision if no action is taken to avoid the collision. Systems can be designed to feature collision warnings as well as automated active safety capabilities. In addition to the high level architecture of the Bayesian transition model, example scenarios illustrate the function of the real-time transition model.

Optimization of Travel in Bus Rapid Transit-Based Multimodal Corridors

Frequently, urban transportation infrastructure and services are operated in a suboptimal manner with respect to key policy objectives such as enhancing mobility, avoiding severe congestion, improving public transit ridership, reducing fuel consumption, and emissions. To overcome this problem, a hybrid simulation-optimization methodology was developed for identification of values of demand management variables that result in the most favorable travel conditions in a multimodal corridor regarding a policy objective. This methodology was applied to a bus rapid transit based major travel corridor in Ottawa, Canada. The travel simulation part of the model is implemented within the EMME/2 modeling framework, supported by a transitway simulation technique. The optimization part of the methodology is based on direct search method that identifies the optimal values of key demand management variables for policy responsiveness. Optimization results are presentede for bus modal split, in-vehicle travel time, fuel consumption, and greenhouse gas emission.

TECHNOLOGICAL RESPONSES TO URBAN TRAFFIC CONGESTION. PART TWO: THE TECHNOLOGY OF TRAFFIC MANAGEMENT

This is the second of three articles discussing technological responses to urban traffic congestion.This paper reports on the components of intelligent vehicle highway systems, their present state of development around the world, the benefits of adopting these technologies, and the issues that have to be overcome if their potential is to be achieved. The IVHS categories discussed in this paper include: Advanced Traffic Management Systems; Advanced Traveler Information Systems; Commercial Vehicle Operations; and Advanced Vehicle Control Systems.