Coordination of last train transfers using automated fare collection (AFC) system data

This paper studies last train coordination problem for metro networks, aiming to maximize the total number of passengers who can reach their destinations by metro prior to the end of operation. The concept of last boarding time is defined as the latest time that passengers can board the last trains and reach final destinations. The corresponding method for calculating last boarding time is also put forward. With automatic fare collection system data, an optimization model for coordinating last trains is proposed. The objective function optimizes the number of passengers who can reach their final destinations during the train period using departure times and headways of last trains for each line as decision variables. Afterwards, an adaptive genetic algorithm is put forward to solve this model and is applied to a case study of the Shanghai metro system. Copyright © 2017 John Wiley & Sons, Ltd.     

Eliminating barriers to nighttime activity participation: the case of on-demand transit in Belleville,Canada

Transportation - Demand-responsive technologies are rapidly changing the transportation landscape. The City of Belleville, Ontario has recently replaced its evening and nighttime fixed route bus...     

Simulation‐based estimates of delays at freeway work zones

Work zone related traffic delay is an important cost component on freeways with maintenance activities. This study demonstrates that delays may be underestimated by using the deterministic queuing theory. Computer simulation is a valuable approach of estimating delay under a variety of existing and future conditions. However, a single simulation run, which can be quite costly in terms of both computer and analyst time, produces a delay estimate for only one traffic level under one set of conditions. A method is developed in this paper to approximate delays by integrating limited simulation data, obtained from CORSIM and the concept of deterministic queuing theory, while various geometric conditions and time‐varying traffic distribution are considered. A calibrated and validated simulation model that can reflect work zone traffic operations on a segment of Interstate 1–80 in New Jersey is used to generate data for developing the proposed model. The comparison of delays estimated by the deterministic queuing model and the proposed model is conducted, while factors affecting the accuracy of the delay estimates are discussed.     

Scheduling highway work zones with genetic algorithm considering the impact of traffic diversion

Highway work zones caused excessive delay to road users. To reduce user and maintenance costs, work zones shall be designed and scheduled accordingly. An analytical model is developed to jointly optimize work zone lengths and schedule as well as diverted traffic volume for highway maintenance projects, considering time‐varying demand, variable maintenance cost, and various production rates of maintenance crew. With a genetic algorithm, an iterative procedure is developed to search for the optimal solution. A numerical example is illustrated, in which various traffic mitigation plans for a highway maintenance project are evaluated. A sensitivity analysis is conducted, and results indicate the threshold volumes for various conditions (e.g., maintenance crews and capacity of the work zone) at which diverting traffic is desirable. This study demonstrates an effective approach to search for the optimal work zone schedule, which is also applicable to evaluate the effectiveness of traffic diversion plans for a pre‐planned work zone schedule. Copyright © 2012 John Wiley & Sons, Ltd.     

How do local actions affect VMT? A critical review of the empirical evidence

In this paper, we present a discussion of the challenges for research on the topic of vehicle miles traveled. We then summarize and critique evidence from the US on the association between 14 distinct factors and vehicle miles traveled. Our results quantify how much vehicle miles traveled can be expected to change in response to changes in policy or land use factors, including residential density and land use mix, as well as specific transport policies and programs such as transit improvements, road pricing, and programs aimed at changing people’s travel choices. Overall, though individual studies differ as to exact effect sizes, it is clear that local-level policymakers can take actions that are likely to affect vehicle miles traveled. However, we highlight gaps in the knowledge base at a time when decision makers at the local level are being increasingly called upon to take action to reduce vehicle miles traveled. Variation in effect size based on local context or interaction with related policies and programs has been left largely unexplored. In addition, experimental research designs that can identify causal direction are rare, and appropriate data that quantifies vehicle miles traveled are often lacking.     

Optimal feeder bus routes on irregular street networks

The methodology presented here seeks to optimize bus routes feeding a major intermodal transit transfer station while considering intersection delays and realistic street networks. A model is developed for finding the optimal bus route location and its operating headway in a heterogeneous service area. The criterion for optimality is the minimum total cost, including supplier and user costs. Irregular and discrete demand distributions, which realistically represent geographic variations in demand, are considered in the proposed model. The optimal headway is derived analytically for an irregularly shaped service area without demand elasticity, with non‐uniformly distributed demand density, and with a many‐to‐one travel pattern. Computer programs are designed to analyze numerical examples, which show that the combinatory type routing problem can be globally optimized. The improved computational efficiency of the near‐optimal algorithm is demonstrated through numerical comparisons to an optimal solution obtained by the exhaustive search (ES) algorithm. The CPU time spent by each algorithm is also compared to demonstrate that the near‐optimal algorithm converges to an acceptable solution significantly faster than the ES algorithm.     

A Reusability Study of Vehicle Lateral Control System

The architecture of the PATH vehicle lateral control system is presented in this paper. The two main modules are an intelligent reference/sensing system, and an Frequency-Shaped-Linear-Quadratic/preview control algorithm. The whole lateral control system was formerly evaluated on a two-door test vehicle. It was transplanted to a four-door vehicle which is considerably different from the older two-door test vehicle in dynamic characteristics. The objective of this study is to investigate the reusability of our control system.     

The lost waterfront of New York

Abstract

No integrated municipal policy exists for managing the New York City waterfront. Despite much rhetoric and many proposals to renew the city's coast, the municipal government has done little to improve the city's coastal shoreline. External organizations and citizens’ groups have been largely responsible for efforts to improve the use of the city's coastal resources. This article assesses the role of the city government and analyzes the factors affecting its performance in coastal management. It proposes new policies to foster local initiatives and encourages private and public cooperation in the revitalization of the coast. Given the size and diversity of the city's coast, an incremental strategy may be the most feasible and sensible approach to recapture the city's lost waterfront.     

Optimizing sustainable feeder bus operation considering realistic networks and heterogeneous demand

A mathematical model is developed to optimize social and fiscal sustainable operation of a feeder bus system considering realistic network and heterogeneous demand. The objective total profit is a nonlinear, mixed integer function, which is maximized by optimizing the number of stops, headway, and fare. The stops are located which maximize the ridership. The demand elasticity for the bus service is dependent on passengers' access distance, wait time, in‐vehicle time, and fare. An optimization algorithm is developed to search for the optimal solution that maximizes the profit. The modeling approach is applied to planning a bus transit system within Woodbridge, New Jersey. Copyright © 2011 John Wiley & Sons, Ltd.