טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
Ph.D Thesis
Ph.D StudentSharav Nir
SubjectOptimal Urban Transit Investment Model and its Application
DepartmentDepartment of Civil and Environmental Engineering
Supervisor Professor Yoram Shiftan
Full Thesis textFull thesis text - English Version


Abstract

Cities vary by size, density, urban structure, population, employment, and socio-economic characteristics. These differences are also reflected in the mobility solutions each city has developed. Urban planners and decision makers need to choose which projects to build and how to allocate the budget among them. City planners need to decide how much to invest in public transport and what should be the network structure, transit lines and modes. However, planning the optimal transit network is an NP-Hard problem, that have challenged many researchers to develop heuristic approaches to the optimal network planning.


In this research we developed an urban transit optimal investment model integrating transit planning, transport economics, and policy decisions. The model expands the theory of optimal transit planning and investment taking into account the effects of the investment on accessibility, level of service, and transit speed. The model simultaneously seeks long term optimal transit investment policy with short term decisions such as frequencies and road pricing in an integrated multi modal model. This approach combines the two main traditional approaches to solve the congestion problem (giving priority to public transportation and charging tolls for road users), with one unified theory that includes infrastructure investment and policy decision simultaneously. We then applied the model in two cities, Tel Aviv and Toronto, and by comparing the model results to the current and planned transit networks we demonstrated how the model can assist in planning and investing in the city’s transit network.


The results show the optimal transit mode and investment on a corridor level, and by aggregating these results, the total investment in the transit network. The model prediction can help planners to optimize urban transport planning by providing directions to the network structure and the optimal investment and mode in each corridor. The model results, compared to the city’s current network and future transit plans, provide insights to how the planners can plan a better and more efficient transit network. The model also showed that applying the right toll with the applicable transit investment is crucial to obtain efficient network and performance. The model results showed that network utilization might be sub-optimal considering passengers’ preferences and that policy decisions is needed together with optimal investment and mode decisions.