AbstractsTransportation

Designing a highly efficient public transit system can help reduce the congestion andpollution in large cities. This dissertation tries to improve public transit systems at boththe micro and macro scales.At the microscale, a Transit Signal Priority strategy is developed to integrate a pre-signal scheme. Buses often compete with cars for limited road space and signal times atintersections. Providing signal priority together with exclusive lanes for buses will oftendiminish car discharge flows into the intersection. This can create huge car delays, whichwill undermine the benefit brought by the priority measures to buses. To solve this problem,we propose a midblock pre-signal to recover the loss in the cars’ discharge capacity causedby the bus priority measures. We show how the pre-signal can be coordinated with theintersection’s main signal under a simple signal priority scheme. Analytical models areformulated to examine the effects of our strategy on two performance metrics: the expectedbus delay and the car capacity. Pareto frontiers between the two performance metrics aredeveloped. Numerical case studies show that huge benefits for both buses and cars can beachieved by the proposed strategy, as compared to baseline scenarios where a bus signalpriority scheme or pre-signal is absent.At the macroscale, two continuum approximation (CA) optimization models are formu-lated to design city-wide transit systems at minimum cost. Transit routes are assumed to lieatop a city’s street network. Model 1 assumes that the city streets are laid out in ring-radialfashion. Model 2 assumes that the city streets form a grid. Both models can furnish hybriddesigns, which exhibit intersecting routes in a city’s central (downtown) district and onlyradial branching routes in the periphery. Model 1 allows the service frequency and the routespacing at a location to vary arbitrarily with the location’s distance from the center. Model2 also allows such variation but in the periphery only.We show how to solve these CA optimization problems numerically, and how the numeri-cal results can be used to design actual systems. A wide range of scenarios is analyzed in this way. It is found among other things that in all cases and for both models: (i) the optimal2headways and spacings in the periphery increase with the distance from the center; and (ii)at the boundary between the central district and the periphery both, the optimal servicefrequency and the line spacing for radial lines decrease abruptly in the outbound direction.On the other hand, Model 1 is distinguished from Model 2 in that the former produces inall cases: (i) a much smaller central district, and (ii) a high frequency circular line on theouter edge of the central district. Parametric tests with all the scenarios further show thatModel 1 is consistently more favorable to transit than Model 2. Cost differences betweenthe two designs are typically between 9% and 13%, but can top 21.5%. This is attributed tothe manner in which ring-radial networks naturally concentrate passenger’s shortest…