计量经济分析 = Econometric analysis

The mapping of large-scale human movements is important for urban planning, traffic forecasting and epidemic prevention. Work in animals had suggested that their foraging might be explained in terms of a random walk, a mathematical rendition of a series of random steps, or a Levy flight, a random walk punctuated by occasional larger steps. The role of Levy statistics in animal behaviour is much debated — as explained in an accompanying News Feature — but the idea of extending it to human behaviour was boosted by a report in 2006 of Levy flight-like patterns in human movement tracked via dollar bills. A new human study, based on tracking the trajectory of 100,000 cell-phone users for six months, reveals behaviour close to a Levy pattern, but deviating from it as individual trajectories show a high degree of temporal and spatial regularity: work and other commitments mean we are not as free to roam as a foraging animal. But by correcting the data to accommodate individual variation, simple and predictable patterns in human travel begin to emerge. The cover photo (by Cesar Hidalgo) captures human mobility in New York's Grand Central Station. This study used a sample of 100,000 mobile phone users whose trajectory was tracked for six months to study human mobility patterns. Displacements across all users suggest behaviour close to the Levy-flight-like pattern observed previously based on the motion of marked dollar bills, but with a cutoff in the distribution. The origin of the Levy patterns observed in the aggregate data appears to be population heterogeneity and not Levy patterns at the level of the individual. Despite their importance for urban planning1, traffic forecasting2 and the spread of biological3,4,5 and mobile viruses6, our understanding of the basic laws governing human motion remains limited owing to the lack of tools to monitor the time-resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period. We find that, in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models7, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time-independent characteristic travel distance and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent-based modelling.

/pdf/understanding-individual-human-mobility-patterns-3k1tyob274.pdf

Understanding individual human mobility patterns

The talk with present the key results of the IPCC Working Group III 5th assessment report. Concluding four years of intense scientific collaboration by hundreds of authors from around the world, the report responds to the request of the world's governments for a comprehensive, objective and policy neutral assessment of the current scientific knowledge on mitigating climate change. The report has been extensively reviewed by experts and governments to ensure quality and comprehensiveness.

Climate change 2014 - Mitigation of climate change

https://www.rug.nl/staff/e.m.steg/abrahamsestegvlekrothengatterreview.pdf

A review of intervention studies aimed at household energy conservation

Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has been an area of research focus for many decades. However, in the absence of detailed driving data that would help improve the identification of cause and effect relationships with individual vehicle crashes, most researchers have addressed this problem by framing it in terms of understanding the factors that affect the frequency of crashes - the number of crashes occurring in some geographical space (usually a roadway segment or intersection) over some specified time period. This paper provides a detailed review of the key issues associated with crash-frequency data as well as the strengths and weaknesses of the various methodological approaches that researchers have used to address these problems. While the steady march of methodological innovation (including recent applications of random parameter and finite mixture models) has substantially improved our understanding of the factors that affect crash-frequencies, it is the prospect of combining evolving methodologies with far more detailed vehicle crash data that holds the greatest promise for the future.

http://ceprofs.tamu.edu/dlord/Papers/Lord-Mannering_Review.pdf

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

Travel behaviour research in an evolving world : select papers from the 12th International Conference on Travel Behaviour Research

The Transportation Research Board’s (TRB’s) second Strategic Highway Research Program (SHRP 2) Capacity Project C10A has released this prepublication, non-edited report that explores development of a dynamic integrated travel demand model with advanced policy analysis capabilities. The model system is scalable; relatively easy to implement and maintain; and does not require a multi-year, multi-million dollar implementation and maintenance effort. The report describes the implementation of the model system in Burlington, Vermont and in Jacksonville, Florida; the calibration and validation of the model system; and the application of the model system to a set of initial sensitivity tests.

Partnership to Develop an Integrated, Advanced Travel Demand Model and a Fine-Grained Time-Sensitive Network

Activity-based microsimulation methods aim to model activity-travel patterns at the level of the individual traveler or decision-maker. However, quite often, individual activity-travel patterns and decisions are influenced through interactions with various agents. Models of activity engagement and time allocation should reflect these interactions to accurately portray the effects that such interactions may have on activity-travel patterns. This paper examines interactions between two adult household members in two-adult households using a data set derived from a household travel survey conducted in Thane city in India. Daily work and non-work activity and travel time allocations between two household members are examined and potential trade-offs and complementary effects are modeled simultaneously using a structural equations modeling methodology. The model estimation results offer significant model coefficients and plausible interpretations consistent with the Indian context. The model meaningfully captures strong interactions, joint activity participation and task allocation among household members and its effects in making work and non-work activity and travel time allocation decisions. Also, this research offers a unique opportunity to compare the study findings with a past study carried out on a data set from Southeast Florida. Comparison between a developed and a developing country context facilitates the understanding about how diverse socio-cultural aspects can influence interaction between household adults and its effect on their activity-travel patterns. Finally, the study suggests activity-based approach can provide suitable framework in the development of advanced modeling techniques in the developing countries like India.

Relationships Between Work and Nonwork Activity and Travel Durations in a Developing Country Context

This chapter demonstrates the feasibility of applying an integrated microsimulation model of activitytravel demand and dynamic traffic assignment for analyzing the impact of pricing policies on traveler activity-travel choices. The model system is based on a dynamic integration framework wherein the activity-travel simulator and the dynamic traffic assignment model communicate with one another along the continuous time axis so that trips are routed and simulated on the network as and when they are generated. This framework is applied to the analysis of a system-wide pricing policy for a small case study site to demonstrate how the model responds to various levels of pricing. Case study results show that trip lengths, travel time expenditures, and vehicle miles of travel are affected to a greater degree than activity-trip rates and activity durations as a result of pricing policies. Measures of change output by the model are found to be consistent with elasticity estimates reported in the literature.

The application of an integrated behavioral activity-travel simulation model for pricing policy analysis

Activity-based models (ABMs) adopt the notion of tours to model activity–travel patterns, because the concept of a tour closely mimics how individuals chain their activities in the real world. Each tour may be defined by a primary destination that corresponds to a primary purpose and may include a multitude of secondary stops on the way to the primary destination (the outbound half-tour) or on the way back (the inbound half-tour). This paper presents a tour characterization framework capable of simulating all secondary stops on a tour, the time allocated to each activity, and the sequence of stops on a tour. The first component simulates the mix of activities and their corresponding durations and was presented in an earlier paper. The current paper presents the stop-sequencing component, which is capable of determining the order in which activities will be pursued on outbound and inbound half-tours. Model estimation results and comparisons between observed and predicted stop-sequencing patterns are presen...

Ram M. Pendyala

Papers

Travel behaviour research in an evolving world : select papers from the 12th International Conference on Travel Behaviour Research

Partnership to Develop an Integrated, Advanced Travel Demand Model and a Fine-Grained Time-Sensitive Network

Relationships Between Work and Nonwork Activity and Travel Durations in a Developing Country Context

The application of an integrated behavioral activity-travel simulation model for pricing policy analysis

Tour Characterization Framework Incorporating Activity Stop Sequencing Model System