Is the curb 80% full or 20% empty? Assessing the impacts of San Francisco’s parking pricing experiment

The city of San Francisco is undertaking a large-scale controlled parking pricing experiment. San Francisco has adopted a performance goal of 60–80% occupancy for its metered parking. The goal represents an heuristic performance measure intended to reduce double parking and cruising for parking, and improve the driver experience; it follows a wave of academic and policy literature that calls for adjusting on-street parking prices to achieve similar occupancy targets. In this paper, we evaluate the relationship between occupancy rules and metrics of direct policy interest, such as the probability of finding a parking space and the amount of cruising. We show how cruising and arrival rates can be simulated or estimated from hourly occupancy data. Further, we evaluate the impacts of the first two years of the San Francisco program, and conclude that rate changes have helped achieve the City’s occupancy goal and reduced cruising by 50%.     

Evaluating parking reservation policy in urban areas: An environmental perspective

This paper investigates a parking reservation mechanism to reduce car cruising to find parking. To consider the benefits for drivers and parking facility providers, we charge drivers for making reservations in addition to parking fees, by introducing a reservation pricing model that makes reservation prices equivalent to the value of saved search time. By modeling the number of vacant spaces as a stochastic variable, and applying binomial pricing methods, parking reservation prices are obtained. Numerical examples based on the data for two parking facilities in Taiwan are given.     

Expirable parking reservations for managing morning commute with parking space constraints

When total parking supply in an urban downtown area is insufficient, morning commuters would choose their departure times not only to trade off bottleneck congestion and schedule delays, but also to secure a parking space. Recent studies found that an appropriate combination of reserved and unreserved parking spaces can spread the departures of those morning commuters and hence reduce their total travel cost. To further mitigate both traffic congestion and social cost from competition for parking, this study considers a parking reservation scheme with expiration times, where commuters with a parking reservation have to arrive at parking spaces for the reservation before a predetermined expiration time. We first show that if all parking reservations have the same expiration time, it is socially preferable to set the reservations to be non-expirable, i.e., without expiration time. However, if differentiated expiration times are properly designed, the total travel cost can be further reduced as compared with the reservation scheme without expiration time, since the peak will be further smoothed out. We explore socially desirable equilibrium flow patterns under the parking reservation scheme with differentiated expiration times. Finally, efficiencies of the reservation schemes are examined.     

Energy savings in transport

A decade of increasing Federal attention to urban transportation needs has culminated in the 1970 Urban Mass Transportation Assistance Act. This Act is intended to provide 10 thousand million dollars over the next 12 years in Federal assistance money to urban public transportation systems. This paper examines the needs of selected U.S. cities as a basis for (1) understanding the vast, various and complex transportation needs of urban areas throughout the country, and (2) assessing the sufficiency of these funds. The sample cities have been placed into three broad categories based on the state of development of their transportation systems. In Category I cities, the essential need is to ensure the survival of bus systems for the use of non‐drivers, or to provide some other viable alternative to the automobile; in Category II cities, the primary needs are to relieve auto congestion and to improve public transportation components, while in Category III cities, the primary need is massive investment to improve and to extend public transportation facilities. It is concluded that the presently intended Federal funding level for transportation will not meet the financial requirements of the Category III cities.     

Computing 4D near-optimal trajectories for dynamic air traffic flow management with column generation and branch-and-price

Abstract

The current air traffic system faces recurrent saturation problems. Numerous studies are dedicated to this issue, including the present research on a new dynamic regulation filter holding frequent trajectory optimisations in a real-time sliding horizon loop process. We consider a trajectory optimisation problem arising in this context, where a feasible four-dimensional (4D) trajectory is to be built and assigned to each regulated flight to suppress sector overloads while minimising the cost of the chosen policy. We model this problem with a mixed integer linear programme and solve it with a branch-and-price approach. The pricing sub-problem looks for feasible trajectories in a dynamic three-dimensional (3D) network and is solved with a specific algorithm based on shortest path labelling algorithms and on dynamic programming. Each algorithm is tested on real-world data corresponding to a complete traffic day in the European air traffic system; experimental results, including computing times measurement, validate the solution process.