6 Drive time analysis
The Arc View Network Analyst includes the ability to create clear directions customized to suit the user needs. The user can also specify what data to use when generating directions and what distance units should be used in the directions. An important feature of the Arc View Network Analyst is the ability to use additional landmark points within the directions. The directions will include these additional data features, resulting in clearer, easier to understand information. Arc View Network Analyst can also do point-to-point routing (known as mid-arc routing, as opposed to endpoint-to-endpoint routing) and can reference local landmarks when reporting route directions. The geographic network data can be based on Arc Info coverage's, shape files, or CAD drawings. Arc View Network Analyst also includes a suite of more advanced network analysis tools that can be accessed through Avenue requests. Developers will be able to deliver very sophisticated network analysis applications based on these extended capabilities.
7 Answering Based on Different Criteria
The Arc View Network Analyst can use any cost field for its calculations. This means the user can solve the questions based on drive time, street length, traffic conditions, or any of a number of criteria. This allows the user to move beyond simple distance based routing and make use of the additional information available today.
8 Build Custom Solutions
The Arc View Network Analyst adds additional functionality to Arc View and Avenue (Arc View's robust object oriented scripting environment). The user can build complete customized solutions from simple tools to complete applications using the power of Avenue and the Arc View Network Analyst.
Conclusion
The crux of the problem of urban transport is congestion of traffic. This results in increased number of trips, increased journey time, travel cost, mental agony and reduced accessibility. Widening of roads is not possible due to the intense developments on either side of the road. Heterogeneity of the traffic is the perpetual problem, which cause severe congestion. This project combines the advantages of both Fuzzy Logic Technology and GIS. It offers public a new means to access spatial information without owning expensive GIS software. It can also facilitate spatial data sharing within transportation agencies and between transportation department and other government agencies. Thus helps the commuters to plan their trip in advance to save time and energy.
Hence, this project gives a methodology to quantify congestion using fuzzy. In essence fuzzy logic opens the door to computers that understand and react to the language and behaviour of human beings rather than machines. From this study it is able to understand that, the present system of defining congestion using V / C ratio is not matching with reality. Thus, the fuzzy logic model helps us to alleviate congestion in the short-to medium-term.
Cars and traffic control systems can make use of the vague information derived from the natural environment that in turn can be fed into "expert" systems and so provide accurate recommendations to vehicle drivers, the police, motoring organisations and of course, local authorities. The effect such systems will have on the traffic scene is too early to say, but clearly they will give planners and traffic authorities some breathing space when considering long-term objectives and likely solutions.
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