This paper summarizes an ongoing research program to advance the state of the art in robotics: the U.S. Defense Advanced Research Projects Agency Autonomous Robotic Manipulation (ARM) program. The program began in 2010 with three tracks, which was later extended to four. The software track is developing intelligent control of manipulators to perform autonomous tasks, using local perception sensors. The hand track has developed rugged, dexterous, multi-fingered hands with significantly reduced costs. The arm track is working to reduce the cost of robot arms. And the outreach track is showcasing robot technology to the general public. Technology developed under the program is iteratively evaluated through a series of hands-off tests. To date, the ARM developers have performed beyond expectations, yielding outstanding hardware designs and robust manipulation software. The results of this program are expected to strengthen the general robotics community and transition technology to U.S. military efforts.

This paper summarizes an ongoing research program to advance the state of the art in robotics: the U.S. Defense Advanced Research Projects Agency Autonomous Robotic Manipulation (ARM) program. The program began in 2010 with three tracks, which was later extended to four. The software track is developing intelligent control of manipulators to perform autonomous tasks, using local perception sensors. The hand track has developed rugged, dexterous, multi-fingered hands with significantly reduced costs. The arm track is working to reduce the cost of robot arms. And the outreach track is showcasing robot technology to the general public. Technology developed under the program is iteratively evaluated through a series of hands-off tests. To date, the ARM developers have performed beyond expectations, yielding outstanding hardware designs and robust manipulation software. The results of this program are expected to strengthen the general robotics community and transition technology to U.S. military efforts. D. Hackett (B) Griffin Technologies, Fort Washington, PA, USA e-mail: dhackett@griffin-technologies.com J. Pippine Golden Knight Technologies, Fairfax, VA, USA e-mail: Jim@goldenknighttechnologies.com A. Watson · C. Sullivan Mechanismo, Reston, VA, USA e-mail: adam@mechanismollc.com C. Sullivan e-mail: chad@mechanismollc.com G. Pratt Defense Advanced Research Projects Agency (DARPA), Arlington, VA, USA e-mail: gpratt@darpa.mil

Circa 2010, manipulation systems required burdensome human operation and high-precision arms and hands, yet could not match the manipulation skills of a two-year old child.To address this situation, the U.S.

views, opinions, and/or findings contained in this article/presentation are those of the author/ presenter and should not be interpreted as represent-ing the official views or policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the Department of Defense.

Given that the safety impacts of traffic management measures, including their effect on traffic speed, have been reasonably well-established, this reports explores the potential impact of such treatments on mode choice and travel behaviour such as travel patterns. The term 'slow zone' treatment or programme was created to generically describe the aim of any programme that modified the physical road environment in such a way it would moderate driver behaviour, slow vehicle traffic, and/or improve the environment of the neighbourhood. An evaluability assessment framework was adopted as the methodological approach for this research project. Evaluability assessment is a systematic process that helps identify whether a planned programme evaluation is justified, feasible and likely to provide useful information. In the first stage of an assessment, one output is an evidence-based logic model. In completing the tasks for this stage, it was found that the evidence review did not allow the development of a comprehensive logic model as planned, because it was not possible to clearly identify slow zone programme 'best practice(s)' for facilitating mode shifts or changes in transport mode use. Hence, less detailed guidance for a monitoring framework to help collect appropriate outcome and impact data was developed.

Sample surveys are widely used in the social sciences and business. The news media almost daily quote from them, yet they are widely misused. Using students with prior managerial experience embarking on an MBA course, we show that common sample survey results are misunderstood even by those managers who have previously done a statistics course. In general, they fare no better than managers who have never studied statistics. There are implications for teaching, especially in business schools, as well as for consulting.

This report is an update of an earlier study of travel patterns of people age 60 and older, in New Zealand. The original study was conducted 1997-1998. The current study, performed 2004-2007, found that older people had increased their amount of travel significantly, since 1997-1998. This was most especially true for driving trips.

This report describes the 2008-09 reformulation of the 2004-07 Ongoing New Zealand Household Travel Survey trips database into trip chains and tours. The reformulation required us to re-create programming sequences for key elements of the new datasets (segments, trip chains, tours, main mode and main purpose, and three different tour classification schemes) based on previous reformulation of the 1997-98 New Zealand Household Travel Survey dataset. The reformulated datasets permitted us to compare New Zealanders travel patterns in 1997-98 and over 2004-07. Thus, we can comment on some trends in New Zealander's travel behaviour. Comparing the 2004-07 and 1997-98 datasets revealed that: 1 . The mean number of trip chains per day (2.3) and the mean number of tours per day (1.3) were essentially unchanged; 2. Both trip chains and tours were increasingly likely to have fewer segments; 3. Vehicle driver only trip chains increased significantly to 53 per cent of all trip chains from 48 per cent. Vehicle driver only tours increased significantly to 50 per cent from 47 per cent; 4. Most trip chains and tours were non-work/non-education tours (e.g. personal business, shopping, social, recreational, etc.); 5. Walk only trip chains declined to 11 per cent from 13 per cent. (a)

Segmentation research projects are often relatively large and complex, putting them at risk of wasting time and money. This paper suggests some do’s and don'ts to help guide sound planning and to minimise such risks for segmentation research about sustainable transport. It is based on recent work reviewing local and international literature, and also the practical experience of doing segmentation research (both quantitative and qualitative). (a) For the covering record of the conference, please refer to ITRD no. E218380.

In 2008, we reformulated the 2004-07 Ongoing New Zealand Household Travel Survey trips dataset into trip chains and tours. We based this on our previous reformulation of the 1997/98 New Zealand Household Travel Survey dataset. Trip chains and tours are combinations of the basic unit of these surveys, the trip leg. For example, if I drive home from work but stop briefly twice (e.g., to get a newspaper, and later to pick up children), that travel comprises three trip legs but only one trip chain. Using the reformulated datasets, we made comparisons between New Zealanders’ travel patterns in 1997/98 and the four-year period of 2004-07 and commented on the emergence of some trends in New Zealand travel behaviour. (a) For the covering record of the conference, please refer to ITRD no. E218380.

This paper contributes to building good practice guidelines for evaluating travel plans, especially where data on changes in kilometres travelled is an objective (e.g. to estimate changes in emissions from the changes in kilometres travelled) and before/after surveys are used for data collection. The lessons here include: 1.something old (reminders of evaluation fundamentals that can easily get overlooked); 2. something borrowed (relevant points from methods for evaluating personalised marketing that have been discussed in great detail at previous Australasian Transport Research Forums); 3. something new (innovations for collecting data about kilometres travelled). (a) For the covering entry of this conference, please see ITRD abstract no. E217541.

Research teams use common robots and machine learning to teach the robots outdoor navigation and locomotion skills.

In 2003, Sport and Recreation New Zealand (SPARC) and the Cancer Society of New Zealand commissioned a major nationwide survey to segment adult New Zealanders in terms of physical activity and healthy eating habits. The questionnaire, based on previous work by the American Cancer Society, included several questions about current usage of, and attitudes toward, active transport (particularly cycling, and to a lesser extent walking). The resulting Obstacles to Action database (with responses from over 8000 people aged 16 or over) thus provides opportunities to analyse transport responses with a larger sample size than is usual with New Zealand surveys. The focus of this paper is on one aspect of that report, namely the stage of change questions that build on the detailed development work done in the UK by the Transport Research Laboratory (TRL). The transtheoretical model of change, or stages of change model, is widely used in New Zealand and overseas to promote major changes in behaviour (e.g. quitting smoking, increasing intake of fruit and vegetables, alcohol abuse, cocaine abuse, safer sex). There is also evidence that approaches based on this model are effective for promoting physical activity in general. (a) For the covering entry of this conference, please see ITRD abstract no. E214666.

In 2003, Sport and Recreation New Zealand (SPARC) and the Cancer Society of New Zealand commissioned a major nationwide survey to segment adult New Zealanders in terms of physical activity and healthy eating habits. The questionnaire included several transport-related questions. The resulting Obstacles to Action database (with responses from over 8000 people aged 16 or over) thus provides opportunities to analyse transport responses with a larger sample size than is usual with New Zealand surveys. This report analyses the Obstacles to Action database with respect to cycling and walking. A focus is the stage of change questions which can be useful for developing and monitoring active transport promotional strategies, given that behaviour change may often involve a number of process steps being undertaken before individuals are ready to change behaviour. Current cycling and walking, together with stage of change for cycling and walking, were first analysed for demographic differences (age, gender, ethnicity, level of urbanisation, region, effect of children, work status, household income). Differences between stages of change with respect to motivations, perceived benefits, and perceived barriers (physical activity in general) were also briefly considered, as well as readiness to replace car trips with walking and cycling, relevant environmental perceptions, and perceived environmental barriers. (a)

To improve the understanding of people’s travel behaviour, the authors re-formulated the 1997/98 NZ (Household) Travel Survey database to link together the trip legs to derive two datasets, one based on “trip chains” and the other on “tours” (beginning and ending at home). While this re-formulation appears straightforward, the authors encountered a number of difficulties in creating definitions and procedures for the treatment of trip chains, tours, main mode and main purpose as researchers use the same terms interchangeably or give them different meanings. This paper explores some of the issues encountered while trying to derive coherent meanings for the terms “trip segment”; “trip chain”; “tour”; “main mode”; and “main purpose.” It then goes on to demonstrate how the definitions are applied by highlighting some results from the re-formulated datasets. (a) For the covering entry of this conference, please see ITRD abstract no. E213716.

There has been increasing interest by governments in New Zealand in replacing short car trips (less than 5 kilometress) with trips using other more environmentally friendly modes, such as passenger transport, walking and cycling. However, discussion of the potential for changing short trips often misuses the available data, with the potential cited being based on segments (or legs), which often differ from what most people would consider as a or what we define as a trip chain. The LTSA's 1997/98 New Zealand (Household) Travel Survey database during 2003-2004 has been reformulated to derive chains and tours (beginning and ending at home) to better understand New Zealanders' travel behaviour. Among other things, the research helps to: correct widespread misunderstandings about the nature and frequency of short trips; enable better quantification of potential for change from short car trips to other modes; provide inputs for developing policy and infrastructure programmes, and enable new and improved performance measures. (a)

This paper provides guidance to local authorities and others who may wish to apply a personalised marketing program in a given area and to measure the impact of such an intervention. 'Personalised Marketing' is used to describe a program aimed at changing people's travel behaviour by a combination of education, persuasion and provision of personalised information to either individual households or individual people. One of the best-known personalised marketing programs in Australasia and Europe is 'IndiMark' or 'individualised marketing'. Various personalised marketing demonstration programs have claimed substantial success in decreasing car use and increasing trips by alternative modes, thereby convincing some local authorities that such programs may be the 'panacea' to congestion problems in urban areas. Our recent involvement in helping to plan the evaluation of a personalised marketing trial in Birkenhead (Auckland, New Zealand) caused us to review the international experience with various trials and their evaluation. Our investigation is two-pronged: to learn to what extent we can guide 'pre-selection' of the area and participants/households for a personalised marketing initiative to learn from pitfalls in the evaluation of the impacts of such programs. The evaluation ('after') and elicitation surveys in Birkenhead highlighted the inadequacies of the current public transport system, providing evidence to support the widely-used pre-selection criteria of a 'good quality' public transport service being in place prior to the initiation of a personalised marketing program. Analysis of the 'before' survey data revealed characteristics distinguishing 'receptive' from 'non-receptive' individuals and households. Not only did the analysis reveal significant differences in personal characteristics and attitudes towards 'environmentally friendly modes', but also we found indications of pre-existing differences in mode use, which could confound potential evaluations of mode change after the intervention (e.g. as claimed in some analyses of individualised marketing in South Perth). Furthermore, great care must be taken with respect to the sample used for the evaluation. The statistical power to detect significant differences between before- and after-measurements is determined not only by sample size but also by the variability of behaviour. If people vary greatly in the number of trips driven and/or distance driven on a day-to-day or week-to-week basis (even in the absence of an intervention), then larger sample sizes (and/or longer data collection periods than the usual one-day trip diary) are needed. We used the 1997/98 New Zealand Travel Survey to estimate day-to-day variability in transport behaviour (both distance and trips, for several different modes). Results suggest that the sample sizes required are distinctly larger than seen in some recent research locally and that traditional travel diary methods may not be cost-effective for impact evaluation of many small pilot projects.

In New Zealand as elsewhere, there is an increasing interest in alleviating congestion on the road transport network to improve economic productivity, reduce pollution, and to use the transport network more effectively. Governments enact various policies to encourage car drivers to change their behaviour, but often find that the full impact is not reached. We propose that car drivers have constraints influencing their mode choice for the morning peak period trip (e.g. needing to transport children, needing a car for work during the day). A stated preference experiment conducted in the three largest New Zealand urban areas not only quantifies the likely impact of a wide range of policy tools (both ‘sticks’ discouraging car use, and ‘carrots’ encouraging alternative modes) for each area, but also identifies many significant constraints.