Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Dynamic OD transit matrix estimation: formulation and model-building environment

The aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering formulation defined by the authors has been included in the application. The definition of the input for building the space-state model is linked to network scenarios modeled with the transportation planning platform EMME. The transit assignment framework is optimal strategy-based, which determines the subset of paths related to the optimal strategies between all OD pairsPeer ReviewedPostprint (author’s final draft

Timely Data Delivery in a Realistic Bus Network

Abstract—WiFi-enabled buses and stops may form the backbone of a metropolitan delay tolerant network, that exploits nearby communications, temporary storage at stops, and predictable bus mobility to deliver non-real time information. This paper studies the problem of how to route data from its source to its destination in order to maximize the delivery probability by a given deadline. We assume to know the bus schedule, but we take into account that randomness, due to road traffic conditions or passengers boarding and alighting, affects bus mobility. We propose a simple stochastic model for bus arrivals at stops, supported by a study of real-life traces collected in a large urban network. A succinct graph representation of this model allows us to devise an optimal (under our model) single-copy routing algorithm and then extend it to cases where several copies of the same data are permitted. Through an extensive simulation study, we compare the optimal routing algorithm with three other approaches: minimizing the expected traversal time over our graph, minimizing the number of hops a packet can travel, and a recently-proposed heuristic based on bus frequencies. Our optimal algorithm outperforms all of them, but most of the times it essentially reduces to minimizing the expected traversal time. For values of deadlines close to the expected delivery time, the multi-copy extension requires only 10 copies to reach almost the performance of the costly flooding approach. I

Factors influencing walking distance to the preferred public transport stop in selected urban centres of Czechia

One of the ways of improving the attractiveness of public transport is to bring it closer to its potential users. A long walking distance from a stop is often one of the critical factors limiting its more frequent and extensive use. Studies dealing with the accessibility of transport networks usually work only with the closest stop. This article analyses the actual walking distance from the place of residence to the preferred stop. The survey used a questionnaire method and was conducted in two cities in the Czech Republic-Ostrava and Olomouc. Based on the results of the study, the average walking distance was assessed and the impact of demographic characteristics (gender, age, education, number of members in the household, economic activity, the presence of a child in the household, and car ownership), transport behavior (preferred mode of transportation, car convenience and opinions on public transport), and urban characteristics (prevailing housing type) on the walking distance were analyzed. The main findings prove a significant impact on walking distance by a number of these factors, but the preferred use of a car for commuting or unemployment does not significantly affect walking distance. Highlights for public administration, management and planning: The public transport stop reported as being closest to a respondent's residence was used by only 51% of all respondents in the survey. Another 20% of residents used the second closest stop, 11% the third stop. Travellers select the stop based on number of connections; seamless connection; the speed of connection; potential delays; equipment of stops and nearby areas; the comfort of the vehicle; avoiding overcrowded stop; other personal factors. The average walking distance to the preferred stop is 568 metres in Ostrava while only 439 metres in Olomouc. Significantly shorter distances refer to the female population in Ostrava, retired and unemployed. Assumption of the negative influence of the higher number of family members, higher salaries, car ownership and worse education (blue collar) was not proved.Web of Science131301

Analyzing the Effects of Transit Network Change on Agency Performance and Riders in a Decentralized, Small-to-Mid-sized US Metropolitan Area: A Case Study of Tallahassee, Florida, MTI Report 12-04

On July 11, 2011, StarMetro, the local public transit agency in Tallahassee, Florida, restructured its entire bus network from a downtown-focused radial system to a decentralized, grid-like system that local officials and agency leaders believed would better serve the dispersed local pattern of population and employment. The new, decentralized network is based on radial routes serving the major arterial roads and new crosstown routes linking the outer parts of the city, where population and employment is growing. Local officials and agency staff hoped the change would increase transit’s attractiveness and usefulness to the community. One year after the service restructuring, overall performance results are similar to those experienced in other cities that have implemented major service changes. Overall ridership and productivity are lower than before the service restructuring, due to the short time frame for rider adjustments and longer-than-anticipated headways, but new ridership has appeared in previously un-served or under-served corridors and neighborhoods. The service restructuring resulted in longer walks to bus stops, due to the removal of stops from many neighborhoods and their relocation to major roads, but overall transit travel times are shorter due to more direct routing. No particular neighborhoods or community groups disproportionately benefited from or were harmed by the change. The service restructuring was supported by some segments of the community who viewed the older system as ill-suited to the increasingly decentralized community, while it was opposed by other community stakeholders who worried about the loss of service in some neighborhoods and issues of access and safety, particularly affecting elderly and disabled riders, at new stop locations. StarMetro’s extensive public outreach efforts and ongoing service adjustments have reduced the intensity of the opposition to the service restructuring over time, although some segments of the community continue to voice their concerns about the effects of the change on transit-dependent, disabled, and elderly riders

General scores for accessibility and inequality measures in urban areas

In the last decades, the acceleration of urban growth has led to an unprecedented level of urban interactions and interdependence. This situation calls for a significant effort among the scientific community to come up with engaging and meaningful visualizations and accessible scenario simulation engines. The present paper gives a contribution in this direction by providing general methods to evaluate accessibility in cities based on public transportation data. Through the notion of isochrones, the accessibility quantities proposed measure the performance of transport systems at connecting places and people in urban systems. Then we introduce scores rank cities according to their overall accessibility. We highlight significant inequalities in the distribution of these measures across the population, which are found to be strikingly similar across various urban environments. Our results are released through the interactive platform: www.citychrone.org, aimed at providing the community at large with a useful tool for awareness and decision-making

Trip-Based Public Transit Routing Using Condensed Search Trees

We study the problem of planning Pareto-optimal journeys in public transit networks. Most existing algorithms and speed-up techniques work by computing subjourneys to intermediary stops until the destination is reached. In contrast, the trip-based model focuses on trips and transfers between them, constructing journeys as a sequence of trips. In this paper, we develop a speed-up technique for this model inspired by principles behind existing state-of-the-art speed-up techniques, Transfer Pattern and Hub Labelling. The resulting algorithm allows us to compute Pareto-optimal (with respect to arrival time and number of transfers) 24-hour profiles on very large real-world networks in less than half a millisecond. Compared to the current state of the art for bicriteria queries on public transit networks, this is up to two orders of magnitude faster, while increasing preprocessing overhead by at most one order of magnitude

Promoting Intermodal Connectivity at California’s High Speed Rail Stations

High-speed rail (HSR) has emerged as one of the most revolutionary and transformative transportation technologies, having a profound impact on urban-regional accessibility and inter-city travel across Europe, Japan, and more recently China and other Asian countries. One of HSR’s biggest advantages over air travel is that it offers passengers a one-seat ride into the center of major cities, eliminating time-consuming airport transfers and wait times, and providing ample opportunities for intermodal transfers at these locales. Thus, HSR passengers are typically able to arrive at stations that are only a short walk away from central business districts and major tourist attractions, without experiencing any of the stress that car drivers often experience in negotiating such highly congested environments. Such an approach requires a high level of coordination and planning of the infrastructural and spatial aspects of the HSR service, and a high degree of intermodal connectivity. But what key elements can help the US high-speed rail system blend successfully with other existing rail and transit services? That question is critically important now that high-speed rail is under construction in California. The study seeks to understand the requirements for high levels of connectivity and spatial and operational integration of HSR stations and offer recommendations for seamless, and convenient integrated service in California intercity rail/HSR stations. The study draws data from a review of the literature on the connectivity, intermodality, and spatial and operational integration of transit systems; a survey of 26 high-speed rail experts from six different European countries; and an in-depth look of the German and Spanish HSR systems and some of their stations, which are deemed as exemplary models of station connectivity. The study offers recommendations on how to enhance both the spatial and the operational connectivity of high-speed rail systems giving emphasis on four spatial zones: the station, the station neighborhood, the municipality at large, and the region