A conflict model and interactive simulator (FASTCARS) for predicting enroute driver behavior in response to real-time traffic condition information

This paper proposes a theoretical methodology and practical data collection approach for modeling enroute driver behavioral choice under Advanced Traveler Information Systems (ATIS). The theoretical framework is based on conflict assessment and resolution theories popularized in psychology and applied to models of individual consumer behavior. It is posed that enroute assessment and adjustment is a reactionary process influenced by increased conflict arousal and motivation to change. When conflict rises to a level at which conflict exceeds a personal threshold of tolerance, drivers are likely to alter enroute behavior to alleviate conflict through either route diversion of goal revision. Assessment and response to conflict arousal directly relate to the driver's abilities to perceive and predict network conditions in conjunction with familiarity of network configurations and accessible alternate routes.Data collection is accomplished through FASTCARS (Freeway andArterialStreetTrafficConflictArousal andResolutionSimulator), in interactive microcomputer-based driving simulator. Limited real-world implementation of ATIS has made it difficult to study or predict individual driver reaction to these technologies. It is contended here that in-laboratory experimentation with interactive route choice simulators can substitute for the lack of real-world applications and provide an alternate approach to data collection and driver behavior analysis. This paper will explain how FASTCARS is useful for collecting data and testing theories of driver behavior.     

A study of tour formation: pre-, during,and post-recession analysis

Transportation - This study examines changes in activity-travel patterns of employed people during a recession by using a tour-based representation of the activity-based approach. The term tour is...     

How Are Our MPAs Doing? Challenges in Assessing Global Patterns in Marine Protected Area Performance

Without effective management, protected areas are unlikely to achieve the high expectations the conservation and development sectors have for them: conserving biodiversity and alleviating poverty. Numerous marine protected area (MPA) assessment initiatives have been developed at various spatial and temporal scales, including the guidebook How is your MPA doing? These management assessments have been useful to sites to clarify and evaluate their objectives, yet efforts to examine broader regional or global patterns in MPA performance are only beginning. The authors conducted exploratory trend analyses on How is your MPA doing? indicator data collected by 24 MPAs worldwide to identify challenges and areas for future work. Wide variability across sites with regard to the indicators examined and the constructs used to measure them prevented a true meta-analysis. Managers assessed biophysical indicators more often than socioeconomic and governance constructs. Investment by the conservation community to support collecting and reporting high-quality data at the site level would enable a better understanding of the variation in MPA performance, clarify the contribution of MPAs to both biodiversity conservation and poverty alleviation, and help drive better MPA performance. The absence of rigorous and consistent monitoring protocols and instruments and a platform to turn raw MPA monitoring data into actionable information is a critical but under-recognized obstacle to cross-project learning, comparative analyses, and adaptive resource management.     

An empirical investigation on the dynamic processes of activity scheduling and trip chaining

Investigation of the dynamic processes of activity scheduling and trip chaining has been an interest of transportation researchers over the past decade because of its relevance to the effectiveness of congestion management and intelligent transportation systems. To empirically examine the processes, a computerized survey instrument is developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes the investigation on the dynamic processes of activity scheduling and trip chaining based on data collected from a pilot study of the instrument. With the data, ordered logit models are applied to identify factors that are pertinent to the scheduling horizon of activities. Results of the empirical analysis show that a daily schedule often starts with certain activities occupying a portion of the schedule and other activities are then arranged around these pre-occupants. Activities of shorter duration are more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Persons with children often expect more constraining activities than those with no children. The analysis also shows that female respondents tend to be more structured in terms of how the week is planned. Additionally, analysis of travel patterns reveals that many trip-chains are formed opportunistically. Travel time required to reach an activity is positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.     

Coastal Livelihood Diversification as a Pathway Out of Poverty and Vulnerability: Experiences from Tanzania

Livelihood diversification can increase the number of activities generating income and is often adopted as a means to reduce vulnerability to risk and provide a pathway out of poverty. Previous empirical studies, however, have found that this diversification carries no guarantee of success. This study examines the impacts of investments in conservation-based enterprises and micro-credit interventions implemented in coastal Tanzania. Project beneficiaries (n = 178) and non-beneficiaries (n = 117) from seventeen communities surrounding Saadani National Park and the Menai Bay Conservation area were surveyed in 2013, to gather quantitative and qualitative data on a suite of parameters including the number of livelihood activities, total annual income, and engagement in extractive activities. We found that the beneficiaries reported an average of 2.15 livelihoods, which was significantly higher than the 1.44 average reported by the non-beneficiaries. The beneficiaries also had significantly higher mean annual incomes than the non-beneficiaries as the former reported an annual mean income of US $2,076 while the latter reported US $646. The research found a complex relationship between occupational diversity and people's interactions with the environment and it is clear that livelihood diversification is not a blanket solution to reducing pressure on coastal resources. Another important finding from the research is that there are distinct differences between types of livelihood interventions and it is crucial to be clear about the goal of a livelihoods intervention. If the goal is diversifying livelihoods and strengthening resilience, then livelihoods that provide a small and steady income for many entrepreneurs may be enough. However, if the goal is to bring people out of a poverty trap, then it makes more sense to invest in livelihoods that bring in a higher income, even if that means reaching fewer beneficiaries.     

On the structure of weekly activity/travel patterns

Understanding the process of activity scheduling is a critical pre-requisite to an understanding of changes in travel behavior. To examine this process, a computerized survey instrument was developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes an investigation of the structure of activity/travel patterns based on data collected from a pilot study of the instrument. The term “structure” refers to the sequence by which various activities enter one’s daily activity scheduling process. Results of the empirical analyses show that activities of shorter duration were more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Additionally, analysis of travel patterns reveals that many trip-chains were formed opportunistically. Travel time required to reach an activity was positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.