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SECTION 5: ACCOUNTING FOR AND MODELLING NON-MOTORIZED TRAVEL (NMT) 32
Accounting for and modelling NMT proves to be very diffi cult because of a range of factors related to data availability: learning of behaviours, representing them along networks, and using units of analysis and simulation strategies precise enough to detect noticeable differences. We comment on each below. A basic foundation of NMT research—knowing the various behaviours of individuals— continues to be a major hurdle. Most available information on NMT addresses the number of people who walk or cycle, as opposed to number of trips or miles travelled. The existing surveys and other sources that address the frequency of NMT produce a wide variety of results. Each source asks about a different time frame; the number of people who complete the behaviour on a bicycle in a week will be larger than the number who ride in a day. Figure 10. Measurement Strategies and How Well the Behaviour is Captured Measurement strategies Self-report Observation Instrumentation Phenomena / Behaviour to Measure Who does and does not walk or cycle Number of trips Distance In terms of measurement, NMT behaviour can be ascertained by (a) self report (e.g., diary, survey), (b) observation (in person, using sensors) or (c) via various motion detectors (accelerometers, pedometers, global position systems, etc.) (Troiano 2005). There is signifi cant work testing the relative reliability and validity of these approaches. Figure 10 captures some of the differences across these measures (Troped 2001; Krizek et al. 2007b). Purpose or destination Intensity + – + – – + – – + + – + * + = is good at capturing this phenomenon/behaviour = fair — = poor * the ability to measure intensity differs from accelerometers (good) to GPS units (poor) Source: Krizek et al. 2007b. More specifi cally self-report has problems with defi nitions (what is a trip—does it include walking to the bus, walking the dog) and, because NMT is a virtuous behaviour, people want to win the researchers’ approval by showing that they engage in these activities. However, because many walk trips are short and chained with other trips they are easy to forget e.g., walking to transit or from a parked car around a shopping centre. Furthermore, a key issue for walking is that one trip can serve multiple purposes— e.g., travel and health—which is diffi cult to deal with in models. These are diffi cult problems to address. The data necessary to reliably build such models is in short supply for walking and cycling. User and trip characteristics at a suitable level of aggregation, along with user preferences for facility design characteristics are currently of limited quality and are considered a high priority for improvement (USDOT 2000). These data items are not adequately covered in most large scale survey instruments, such as metropolitan travel surveys or the Nationwide Personal Transportation Survey (NPTS) in the U.S. and where they do, there are problems. As Krizek WALKING AND CYCLING LITERATURE REVIEW FINAL REPORT 33
Page 1 and 2: Walking and Cycling International L
Page 3 and 4: CYCLING FINDINGS: A FOCUS ON SEPARA
Page 5 and 6: LOS: Level of Service models aim to
Page 7 and 8: WALKING AND CYCLING COMMON THEMES
Page 9 and 10: KEY SUMMARY POINTS AND RECOMMENDATI
Page 11 and 12: POLICY MOTIVATIONS AND CENTRAL QUES
Page 13 and 14: policy changes in areas of relevanc
Page 15 and 16: Summary 1.1 Interventions for walki
Page 17 and 18: PRICING: THE LOW COST OF DRIVING/PA
Page 19 and 20: SECTION 3: HARD MEASURES: COMMUNITY
Page 21 and 22: speeds attainable by bicycle. At th
Page 23 and 24: Type of facility Representative pho
Page 25 and 26: CYCLING FINDINGS: A FOCUS ON SEPARA
Page 27 and 28: commuting rates. Interestingly enou
Page 29 and 30: Figure 8: Innovative Crossing Treat
Page 31 and 32: SUMMARY 3.1 Community or urban desi
Page 33: SELF-SELECTION The bulk of existing
Page 37 and 38: eplicate roadways. Networks for wal
Page 39 and 40: CONCLUSIONS BASED EXCLUSIVELY ON AV
Page 41 and 42: increase NMT. For walking, infrastr
Page 43 and 44: ecause effi ciency is paramount and
Page 45 and 46: Bibliography Note: * Indicates arti
Page 47 and 48: Bibliography continued *Birk, M., a
Page 49 and 50: Bibliography continued City of Davi
Page 51 and 52: Bibliography continued Eash, R. 199
Page 53 and 54: Bibliography continued Gehl, J. 198
Page 55 and 56: Bibliography continued *Humpel, N.,
Page 57 and 58: Bibliography continued *Kitamura, R
Page 59 and 60: Bibliography continued Litman, T. 1
Page 61 and 62: Bibliography continued *National Hi
Page 63 and 64: Bibliography continued Quiroga, C.,
Page 65 and 66: Bibliography continued Schneider, R
Page 67 and 68: U. S. Department of Transportation.
Page 69 and 70: Appendix A LEGEND FOR APPENDIX Issu
Page 71 and 72: Citation Mode Issue Lit. Type Study
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Citation Mode Issue Lit. Type Study
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