Running head: URBAN TRAFFIC NETWORK DESIGN 1URBAN TRAFFIC NETWORK DESIGN 2

Urban Traffic Network DesignNameInstitution

Proposal for Integrated Optimisation Model for Urban Traffic Network DesignThe demand for transport in the urban areas has increased exponentially over the last few decades. This has led to increase in the number of automobiles in the urban areas. Increase in the number of automobiles has led to emergence of other negative consequences such as traffic congestion, increased pollution, increased rates of road accidents and casualties and chronic delays. Over the years there are many solutions that have been designed with a view of creating solutions to the issue of traffic congestion and related negative consequences. One of the most recent solutions designed to solve traffic related problems in the urban areas is the use of information technology. Information Technology has led to development of a broad range of applications and solutions that have helped road operators and users to deal with the issue of urban congestion (Bonsal, 2004). Though there are many opportunities to find solutions to the problems of urban traffic, there is one thing that is hampering application of these solutions to solve the problems. It is important to note that the problems have already been identified; however, the root causes of these problems and the context within which these problems occur have not been identified. When realizing technical details, there are many issues that are overlooked (Meyer, 2001). That is why most engineering activities on urban roads are meant to solve the problem of congestion only because little attention is paid to other problems caused by the rise in demand for transportation and the subsequent increase in the number of automobiles in urban areas. Before any other solution is designed, it is important for an in depth study of traffic problems in urban areas. When urban traffic network designs are being put in place, the needs and the priorities of the road operators and road users need to be considered (Gutierrez, 1995). The problems that face road users and operators need to be identified so that the designs can solve those problems. This proposal seeks to identify the problems that urban traffic network designs should focus on solving. There are various problems that are common to almost all urban areas that urban traffic network designs should solve. One of the problems is inappropriate and inefficient use of roads. The network capacity that is available in most towns is not used in an efficient manner. This means that some roads are underutilised while others are over-utilised leading to congestion. Some of the roads are not used for the purpose that was originally intended when they were being designed. Some residential roads are being used by commercial and public transport vehicles. This means that solutions to urban traffic network design should aim at ensuring that people use the urban transport infrastructure efficiently to avoid inefficient and inappropriate use of roads (Rodrique, Comtois and Slack, 2006). The second problem within the urban traffic network design is the connection between these urban networks and motorways. There are some congestion control actions such as metering that prevent urban traffic from entering motorways and motorway traffic from entering into urban traffic networks. These actions end up creating gridlocks and spillbacks. When some motorways get congested, urban networks in most cases are used as shortcuts. This means that future urban network design solutions should aim at combining motorways and urban network activities (May, Kelley and Sheppard, 2006). The other problem that urban road network designs should aim at solving is organisation of road-works. In most cities and towns, there is insufficient organisation of these road-works leading to inconveniences especially in event of road closures. Network designs can be made in a way that enables better organisation that prevents inconveniences within the infrastructure. The most important and pertinent problem that should be addressed by urban traffic network designs is air quality. When designing and managing urban transportation systems, air quality is one of the most important considerations that can be made. Motor vehicles are the main sources of most pollutants such as hydrocarbons, nitrogen oxides, carbon monoxide and lead. Despite enforcement of emission standards for motor vehicles, they are expected to remain the leading source of pollutions due to the expected surge in the number of motor vehicles due to increased transport demands. The clean air act of 1977 set the National Ambient Air quality standards which require an approach to transportation planning that is integrated (Kloth 2010). For a long time, transportation planning has been approached in an isolated manner, without any regard for environmental concerns. For instance, the central focus of assignments of traffic has been minimizing travel time within the network. However, there is a complicated link between the capacity of network link, speed, flow and levels of pollution. This means that there must be an integrated approach that accounts for the link between environmental goals and network efficiency goals (Pitcher, 1996). Therefore, this paper proposes and optimization approach that can efficiently account for these connections and trade offs. The paper will also illustrate mathematically, a hypothetically realistic urban transportation network that can solve a variety of the problems listed above. The model of non linear optimization chooses the network capacity projects for expansions. It also assigns destination-origin traffic flows on the road links on certain networks while at the same time reducing several cost functions. These functions include fuel consumption costs, travel time costs and costs for network capacity expansion. The model takes into consideration the conventional capacity and flow constraints. It also includes ambient air quality and emissions constraints (Hanne, 2001). This model has several nonlinearities. These nonlinearities concern the connection between flow and speed of the traffic, fuel consumption and the speed of the traffic and vehicle emission pollution and speed of the traffic. In the model, the constraints of air quality are based on a coefficient matrix for pollution transfer. This coefficient matrix links all the segments in the road network to the pollution receptors that are dependent on the adjacent meteorology (Goldberg, 1999). The non linear model may be hypothetical but it is applicable to a realistic city based network configuration consisting of more than thirty areas of residence that generate commuter traffic towards the central business district. The advantage of this model is that it reduces travel time, cost of fuel consumption and capacity investments while at the same time accounting for various constraints such as pollution emissions, travel speeds and traffic flow. The application of this model and its results will underscore the role of intra-daily variables in meteorological conditions, traffic demand, urban growth strategies and optimal network sensitivity (Turksman and Vreeswijk, 2008). It also demonstrates the importance of physical and meteorological considerations during the design and management of transport networks in urban areas. The model can also be expanded to include the impact of enhanced transit systems and modal split, the impact of changes in land use on network design and optimal new design activities allocation in the urban areas. The model is related to the FREILOT project. In this project, green priority uses V21 mode of communication that provides a wide range of benefits to a number of stakeholders that use the urban road networks. These stakeholders include road operators and other logistic companies. FREILOT has resulted in improved traffic performance in places like Helmond in Holland, Bilbao in Spain, Lyon in France, and Glasgow in Scotland and Basel in Switzerland (Turksman and Vreeswijk, 2008). It has enhanced traffic safety, traffic speed and air quality within the aforementioned urban networks. Since this non linear model has been adopted from FREILOT, it can be applied under several temporal and spatial contexts by creating prerequisites to better solutions. Its ability to mis green priority with regulations for access control illustrates the potential success of the model. The model will definitely create packages that will enable engineers to create integrated solutions that lead to synergy, additivity and complementarities

References

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May, A.D., C. Kelly, & Shepherd,D. (2006). The principles of integration in urban transport strategies, Transport Policy, 2006. 13(4), 319-327