A model of two-destination choice in trip chains with GPS data

Recently published:

Studying trip chaining behavior has been a challenging endeavor which requires the support of microscopic travel data. New insights into trip chaining can be gained from real-time GPS travel data. This research introduces a framework that considers two-des- tination choice in the context of home-based trip chains. We propose and empirically compare three alternatives of building choice sets where we consider various relation- ships of the two destinations (such as major–minor destinations, selecting one first, and selecting two concurrently). Our choice set formation alternatives use survival models to determine the selection probability of a destination. Our results reveal that trip chaining behavior is shaped by the features of retail clusters, spatial patterns of clusters, trans- portation networks, and the axis of travel. This research reveals that not only the spatial relationship but also the land use relationship of the destinations in a trip chain affect the decision making process.

Justice, Exclusion, and Equity: An Analysis of 48 U.S. Metropolitan Areas

Recent working paper

Injustice in transportation services experienced by disadvantaged demographic groups account for much of these groups’ social exclusion.

HoustonOppUnfortunately, there is little agreement in the field about what theoretical foundation should be the basis of measures of the justice of transportation services, limiting the ability of transportation professionals to remedy the issues. Accordingly, there is a need for an improved measure of the justice of the distribution of transportation services, which relates to the effectiveness of transportation services for all members of disadvantaged groups rather than for only segregated members of these disadvantaged groups. To this end potential measures of distributive justice, based on the accessibility to jobs provided by various modes, are evaluated in 48 of the top 50 largest metropolitan areas in the United States. The purpose of the study is to inform recommendations for appropriate use of each measure.

Sydney Transport/Urban Twitter/Blogosphere Meetup

Sydney Transport/Urban Twitter/Blogosphere Meetup – Friday Sept, 22 (6pm) at Hotel Sweeney’s 236 Clarence St, Sydney NSW 2000, Australia

Come one, come all.


Safety in Numbers and Safety in Congestion for Bicyclists and Motorists at Urban Intersections

Recent working paper:

The rate of number of crashes to traffic flow
The rate of number of crashes to traffic flow

This study assesses the estimated crashes per bicyclist and per vehicle as a function of bicyclist and vehicle traffic, and tests whether greater traffic reduces the per-car crash rate. We present a framework for comprehensive bicyclist risk assessment modeling, using estimated bicyclist flow per intersection, observed vehicle flow, and crash records. Using a two-part model of crashes, we reveal that both the annual average daily traffic and daily bicyclist traffic have a diminishing return to scale in crashes. This accentuates the positive role of safety in numbers. Increasing the number of vehicles and cyclists decelerates not only the probability of crashes, but the number of crashes as well. Measuring the elasticity of the variables, it is found that a 1% increase in the annual average daily motor vehicle traffic increases the probability of crashes by 0.14% and the number of crashes by 0.80%. However, a 1% increase in the average daily bicyclist traffic increases the probability of crashes by 0.09% and the number of crashes by 0.50%. The saturation point of the safety in numbers for bicyclists is notably less than for motor vehicles. Extracting the vertex point of the parabola functions examines that the number of crashes starts decreasing when daily vehicle and bicyclist traffic per intersection exceed 29,568 and 1,532, respectively.

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.

Seminar: The End of Traffic and the Future of Access: A Roadmap for the New Transport Landscape


I am giving at talk at ITLS on Tuesday, September 19, 2017 at 14:00

Title: The End of Traffic and the Future of Access: A Roadmap for the New Transport Landscape

Venue : Abercrombie Building (H70) Level 5 – Room 5050 , Corner Abercrombie Street and Codrington Street, The University of Sydney

The University of Sydney: Click here for directions

RSVP is required if you wish to attend


Less than two decades into the new millennium, transport is becoming interesting again. Revolutionary technical advances are taking root; evolutionary social forces are responding; together, these phenomena are changing how people access and exchange goods. Transport and planning discussions are now being reshaped, prompting even seasoned transport professionals to appear as neophytes. This talk reframes the evolving nature of debates about transport and to shape perspectives about the future of transport in cities. It discusses the implications of automation, electrification, sharing, and demassification on travel demands and transport policy.


Prof. David Levinson teaches at the School of Civil Engineering at the University of Sydney, where he leads the Network Design Lab and the Transport Engineering group. He is an honorary affiliate of the Institute of Transport and Logistics Studies, where he is also a member of the Board of Advice. From 1999 to 2016, he served on the faculty of the University of Minnesota where he held the Richard P. Braun/CTS Chair in Transportation (2006-2016).  Levinson has authored or edited several books, including Spontaneous Access,  The Transportation Experience, and Planning for Place and Plexus, as well as numerous peer reviewed articles. He is the editor of the Journal of Transport and Land Use.

Traffic Flow Variation and Network Structure

Recent working paper

Figure4This study defines and detects competitive and complementary links in a complex network and constructs theories illustrating how the variation of traffic flow is interconnected with network structure. To test the hypotheses, we extract a grid-like sub-network containing 140 traffic links from the Minneapolis – St. Paul highway system. We reveal a real-world traffic network comprises both competitive and complementary links, and there is a negative network dependency between a competitive link pair and a positive network dependency between a complementary link pair. We validate a robust linear relationship between standard deviation of flow in a link and its number of competitive links, its link correlation with competitive links, and its network dependency with both competitive and complementary links. The results indicate the number of competitive links in a traffic network is negatively correlated with the variation of traffic flow in congested regimes as drivers are able to take alternative paths. The results also signify that the more the traffic flow of a link is correlated to the traffic flow of its competitive links, the more the flow variation is in the link. Considering the network dependency, however, it is corroborated that the more the network dependency between a link and its competitive links, the more the flow variation in the link. This is also true for complementary links.

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.

The Healthiest vs. Greenest Path: Comparing the Effects of Internal and External Costs of Motor Vehicle Pollution on Route Choice 

On-road emissions, a dominant source of urban air pollution, damage human health. The ‘healthiest path’ and the ‘greenest path’ are proposed as alternative patterns of traffic route assignment to minimize the costs of pollution exposure and emission, respectively. As a proof-of-concept, the framework of a link-based emission cost analysis is built for both internal and external environmental costs and is applied to the road network in the Minneapolis – St. Paul Metropolitan Area based on the EPA MOVES and RLINE models. The healthiest and the greenest paths are skimmed for all work-trip origin-destination pairs and then aggregated into work trip flows to identify the healthier or greener roads in a comparative statics analysis. The estimates show that highways have higher emission concentrations due to higher traffic flow, on which, but that the internal and external emission costs are lower. The emission cost that commuters impose on others greatly exceeds that which they bear. In addition, the greenest path is largely consistent with the traditional shortest path which implies that highways tend to be both greener and shorter (in travel time) for commuters than surface streets. Use of the healthiest path would generate more detours, and higher travel times.
Route choice, Traffic assignment, Shortest path, Pollution, Emissions, Exposure, Intake