Measuring polycentricity via network flows, spatial interaction, and percolation

Recently published

Polycentricity, or the number of central urban places, is commonly measured by 10.1177_0042098019832517-fig1location-based metrics (e.g. employment density/total number of workers, above a threshold). While these metrics are good indicators of location ‘centricity’, results are sensitive to threshold choice. We consider the alternative idea that a centre’s status depends on its connectivity to other locations through trip inflows/outflows: this is inherently a network rather than placeidea. Three flow and network-based centricity metrics for measuring metropolitan area polycentricity using journey-to-work data are presented: (a) trip-based; (b) density-based; and (c) accessibility-based. Using these measures, polycentricity is computed and rank-centricity distributions are plotted to test Zipf-like or Christaller-like behaviours. Further, a percolation theory framework is proposed for the full origin–destination matrix, where trip flows are used as a thresholding parameter to count the number of sub-centres. Trip flows prove to be an effective measure to count and hierarchically organise metropolitan areas and sub-centres, tackling the arbitrariness of defining any threshold on employment statistics to count sub-centres. Applications on data from the Greater Sydney region show that the proposed framework helps to characterise polycentricity and sub-regional organisation more robustly, and provide unexpected insights into the connections between land use, labour market organisation, transport and urban structure.

I only get some satisfaction: Introducing satisfaction into measures of accessibility

Recently published

 

Travel time decay curves by mode

Improving accessibility is a goal pursued by many metropolitan regions to address a variety of objectives. Accessibility, or the ease of reaching destinations, is traditionally measured using observed travel time and has of yet not accounted for user satisfaction with these travel times. As trip satisfaction is a major component of the underlying psychology of travel, we introduce satisfaction into accessibility measures and demonstrate its viability for future use. To do so, we generate a new satisfaction-based measure of accessibility where the impedance functions are determined from the travel time data of satisfying trips gathered from the 2017/2018 McGill Transport Survey. This satisfaction-based measure is used to calculate accessibility to jobs by four modes (public transport, car, walking, and cycling) in the Montreal metropolitan region, with the results then compared to a standard gravity-based measure of accessibility. This comparison reveals a discrepancy between both measures of accessibility, particularly for public transport users. By combining this discrepancy with mode share data, we identify areas that may be targets for future investigations to better understand the causes for discrepancy. The study demonstrates the importance of including satisfaction in accessibility measures and allows for a more nuanced interpretation of the ease of access by practitioners, researchers, planners, and policy-makers.

Measures of Speeding from a GPS-based Travel Behavior Survey

Recently published

speedlimitAbstract

Objective: Lacking information about actual driving speed on most roads in the Minneapolis–St. Paul region, we determine car speeds using observations from a Global Positioning System (GPS)-based travel survey. Speed of travel determines the likelihood and consequences of collisions. We identify the road segments where speeding occurs. This article then analyzes the relationship between link length, traveler characteristics, and speeding using GPS data collected from 152 individuals over a 7-day period as part of the Minneapolis–St. Paul Travel Behavior Inventory.

Methods: To investigate the relationship, we employed an algorithm and process to accurately match the GPS data with geographic information system (GIS) databases. Comparing actual travel speed from GPS data with posted speed limits, we measure where and when speeding occurs and by whom. We posit that link length and demographics shape the decision to speed.

Results: Speeding is widespread under both high speed limits (e.g., 60 mph [97 km/h]) and low speed limits (less than 25 mph [40 km/h]); in contrast, speeding is less common at 30–35 mph (48–56 km/h). The results suggest that driving patterns depend on the road type. We also find that when there are many intersections, the average link speed (and speeding) drops. Long links are conducive to speeding. Younger drivers and more educated drivers also speed more, and speeding occurs more often in the evening.

Conclusions: Road design and link length (or its converse, frequency of intersections) affect the likelihood of speeding. Use of increasingly available GPS data allows more systematic empirical analysis of designs and topologies that are conducive to road safety.

Job-worker spatial dynamics in Beijing: Insights from Smart Card Data

Recently published:

Highlights

Beijing Metro
Beijing Metro
  • We evaluated the ratio of jobs to workers from Smart Card Data at the transit station level in Beijing.
  • A year-to-year evolutionary analysis of job to worker ratios was conducted at the transit station level.
  • We classify general cases of steepening and flattening job-worker dynamics.
  • The paper finds that only temporary balance appears around a few stations in Beijing.
  • Job-worker ratios tend to be steepening rather than flattening from 2011 to 2015.

Abstract
As a megacity, Beijing has experienced traffic congestion, unaffordable housing issues and jobs-housing imbalance. Recent decades have seen policies and projects aiming at decentralizing urban structure and job-worker patterns, such as subway network expansion, the suburbanization of housing and firms. But it is unclear whether these changes produced a more balanced spatial configuration of jobs and workers. To answer this question, this paper evaluated the ratio of jobs to workers from Smart Card Data at the transit station level and offered a longitudinal study for regular transit commuters. The method identifies the most preferred station around each commuter’s workpalce and home location from individual smart datasets according to their travel regularity, then the amounts of jobs and workers around each station are estimated. A year-to-year evolution of job to worker ratios at the station level is conducted. We classify general cases of steepening and flattening job-worker dynamics, and they can be used in the study of other cities. The paper finds that (1) only temporary balance appears around a few stations; (2) job-worker ratios tend to be steepening rather than flattening, influencing commute patterns; (3) the polycentric configuration of Beijing can be seen from the spatial pattern of job centers identified.

Spatiotemporal Short-term Traffic Forecasting using the Network Weight Matrix and Systematic Detrending

Recent working paper:

LookBackWindowsThis study examines the dependency between traffic links using a three-dimensional data detrending algorithm to build a network weight matrix in a real-world example. The network weight matrix reveals how links are spatially dependent in a complex network and detects the competitive and complementary nature of traffic links. We model the traffic flow of 140 traffic links in a sub-network of the Minneapolis – St. Paul highway system for both rush hour and non-rush hour time intervals, and validate the extracted network weight matrix. The results of the modeling indi- cate: (1) the spatial weight matrix is unstable over time-of-day, while the network weight matrix is robust in all cases and (2) the performance of the network weight matrix in non-rush hour traffic regimes is significantly better than rush hour traffic regimes. The results of the validation show the network weight matrix outperforms the traditional way of capturing spatial dependency between traffic links. Averaging over all traffic links and time, this superiority is about 13.2% in rush hour and 15.3% in non-rush hour, when only the 1st -order neighboring links are embedded in modeling. Aside from the superiority in forecasting, a remarkable capability of the network weight matrix is its stability and robustness over time, which is not observed in spatial weight matrix. In addition, this study proposes a naïve two-step algorithm to search and identify the best look-back time win- dow for upstream links. We indicate the best look-back time window depends on the travel time between two study detectors, and it varies by time-of-day and traffic link.

Accessibility Oriented Development

Recent working paper:

AoDMunicipal governments worldwide have been pursuing transit-oriented development (TOD) strategies in order to increase transit ridership, curb traffic congestion, and rejuvenate urban neighborhoods. In many cities, however, development of planned sites around transit stations has been close to non-existent, due to, among other reasons, a lack of coordination between transit investments and land use at the regional scale. Furthermore, the ability to access transit differs from the ability to access destinations that people care about. Reframing transit-oriented development as accessibility-oriented development (AOD) can aid the process of creating functional connections between neighborhoods and the rest of the region, and maximize benefits from transport investments. AOD is a strategy that balances accessibility to employment and the labor force in order to foster an environment conducive to development. AOD areas are thus defined as having higher than average accessibility to employment opportunities and/or the labor force; such accessibility levels are expected to increase the quality of life of residents living in these areas by reducing their commute time and encouraging faster economic development. To quantify the benefits of AOD, accessibility to employment and the labor force are calculated in the Greater Toronto and Hamilton Area, Canada in 2001 and 2011. Cross-sectional and temporal regressions are then performed to predict average commute times and development occurring in AOD areas and across the region. Results show that AOD neighborhoods with high accessibility to jobs and low accessibility to the labor force have the lowest commute times in the region, while the relationship also holds for changes in average commute time between the studied time periods. In addition, both accessibility to jobs and accessibility to the labor force are associated with changes in development, as areas with high accessibility to jobs and the labor force attract more development. In order to realize the full benefits of planned transit investments, planning professionals and policy makers alike should therefore leverage accessibility as a tool to direct development in their cities, and concentrate on developing neighbourhoods with an AOD approach in mind.

Indifference Bands for Route Switching

Printed, (after more than a year in “online first” purgatory) and now available for FREE Viewing.11116_2016_9699_Fig3_HTML

Abstract: The replacement I-35W bridge in Minneapolis saw less traffic than the original bridge though it provided substantial travel time saving for many travelers. This observation cannot be explained by the classical route choice assumption that travelers always take the shortest path. Accordingly, a boundedly rational route switching model is proposed assuming that travelers will not switch to the new bridge unless travel time saving goes beyond a threshold or “indifference band”. To validate the boundedly rational route switching assumption, route choices of 78 subjects from a GPS travel behavior study were analyzed before and after the addition of the new I-35W bridge. Indifference bands are estimated for both commuters who were previously bridge users and those who never had the experience of using the old bridge. This study offers the first empirical estimation of bounded rationality parameters from GPS data and provides guidelines for traffic assignment.

Keywords:

Bounded rationality, Indifference band, Empirical estimation, GPS study, Route Choice

 

Measuring the transportation needs of people with developmental disabilities: A means to social inclusion (free version)

“Measuring the transportation needs of people with developmental disabilities: A means to social inclusion” is now available online. The “free” link provides free access, and is valid until May 31, 2017

Recently published:

Abstract

Background

One of the major causes of social exclusion for people with developmental disability (PDD) is the inability to access different activities due to inadequate transportation services.

Objectivefrequencyofsocialtrips-disability

This research paper identifies transportation needs, and reasons for unmet, but desired untaken trips of adults with developmental disabilities in Hennepin County, Minnesota. We hypothesize that PDD cannot make trips they want to make due to personal and neighborhood characteristics.

Methods

A survey measuring existing travel behavior and unmet transportation needs of PDD (N=114) was conducted. The survey included both demographic and attitudinal questions as well as a travel diary to record both actual and desired but untaken trips. Logistic regression analyses were conducted to determine reasons associated with their inability to make desired, but untaken trips.

Results

Most respondents did not live independently. More than half of the surveyed population worked every day and recreation trips occurred at least once a week for about two-thirds of the population. About 46 percent were unable to make trips they needed to make. Public transit posed physical and intellectual difficulties, however the presence of public transit in neighborhoods decreased odds of not making trips. Concerns about Paratransit services were also reported.

Conclusion

Findings from this study can be of value to transportation engineers and planners interested in shedding light on the needs of a marginalized group that is rarely studied and have special transport needs that should be met to ensure their social inclusion in society.

Measuring the transportation needs of people with developmental disabilities: A means to social inclusion

Recently published:

 

Abstract

Background

One of the major causes of social exclusion for people with developmental disability (PDD) is the inability to access different activities due to inadequate transportation services.

Objectivefrequencyofsocialtrips-disability

This research paper identifies transportation needs, and reasons for unmet, but desired untaken trips of adults with developmental disabilities in Hennepin County, Minnesota. We hypothesize that PDD cannot make trips they want to make due to personal and neighborhood characteristics.

Methods

A survey measuring existing travel behavior and unmet transportation needs of PDD (N=114) was conducted. The survey included both demographic and attitudinal questions as well as a travel diary to record both actual and desired but untaken trips. Logistic regression analyses were conducted to determine reasons associated with their inability to make desired, but untaken trips.

Results

Most respondents did not live independently. More than half of the surveyed population worked every day and recreation trips occurred at least once a week for about two-thirds of the population. About 46 percent were unable to make trips they needed to make. Public transit posed physical and intellectual difficulties, however the presence of public transit in neighborhoods decreased odds of not making trips. Concerns about Paratransit services were also reported.

Conclusion

Findings from this study can be of value to transportation engineers and planners interested in shedding light on the needs of a marginalized group that is rarely studied and have special transport needs that should be met to ensure their social inclusion in society.