Daniela Vanessa Rodriguez Lara Universidade de São Paulo
daniela.lara@usp.br
DISTINCT STREET USERS’ PERCEPTIONS REGARDING THE EFFECT OF TRAFFIC
SPEED ON PEDESTRIANS AND CYCLISTS
Frank Alves Ferreira Universidade de São Paulo
frankferreira@usp.br
Gustavo Garcia Manzato Universidade de São Paulo
gusmanzato@feb.unesp.br
Antônio Nélson Rodrigues da Silva Universidade de São Paulo
anelson@sc.usp.br
8º CONGRESSO LUSO-BRASILEIRO PARA O PLANEAMENTO URBANO,
REGIONAL, INTEGRADO E SUSTENTÁVEL (PLURIS 2018)
Cidades e Territórios - Desenvolvimento, atratividade e novos desafios
Coimbra – Portugal, 24, 25 e 26 de outubro de 2018
DISTINCT STREET USERS’ PERCEPTIONS REGARDING THE EFFECT OF TRAFFIC SPEED ON PEDESTRIANS AND CYCLISTS
D. V. R. Lara, F. A. Ferreira, G. G. Manzato and A. N. Rodrigues da Silva
ABSTRACT
High death rates among pedestrians and cyclists caused by traffic accidents and the increase of motorized vehicles in urban areas have led government agencies to implement speed limit reductions and promote more active and sustainable travel alternatives, such as walking and cycling. Thus, this study assesses distinct groups of urban street users’ perceptions regarding speed limit reductions and measures to stimulate walking and cycling trips. An online questionnaire was developed to address mainly urban and transportation planners and students. Differences in distinct street users’ perceptions were evaluated through chi-square association tests and decision trees. Regardless of their transport modes, most users agreed that reducing speed limits on urban streets stimulates non-motorized trips. In addition, besides or rather than reducing the speed limits, users understand that measures to improve safety, walkability, infrastructure and awareness could also stimulate walking and cycling. 1 INTRODUCTION
In Brazil, 37,345 deaths caused by traffic accidents were registered in 2016. Seventeen percent of those fatalities involved pedestrians and four percent cyclists (MS/SVS/CGIAE, 2016). In addition, deaths caused by traffic accidents are predicted to rise from the current ninth position to the seventh position in 2030 (WHO, 2015). Thus, worldwide actions to reduce traffic accidents involving pedestrians and cyclists are urgently needed. As a consequence, the period from 2011 to 2020 was announced as the Decade of Action for Road Safety in the General Assembly of the United Nations (United Nations, 2010).
The Decade of Action for Road Safety 2011-2020 was created with the objective of establishing a set of short, medium and long terms measures aiming at reducing the mortality rate by 50%. The measures involve programs to reduce accidents with pedestrians and cyclists on urban streets, standardization and reduction of the speed of motorized vehicles on urban streets and assurance of safe conditions for pedestrians and cyclists (ANTP/CEDATT/IE, 2011).
However, in a recent case in the city of São Paulo, the implementation and enforcement of speed limit reductions caused popular dissatisfaction and even raised a public civil action against the speed limit reduction on the main streets alongside the Tietê and Pinheiros rivers by the Order of Attorneys of Brazil (OAB) in 2015 (Monteiro, 2015).
In view of the importance of the topic for stimulating active travel modes (walking and cycling) and the lack of studies and information about it, the present study aims to assess the
perception of distinct groups of urban street users regarding speed limit reductions and incentives for walking and cycling trips.
The article was divided into six sections. After the introductory section, a brief literature review is presented. In Section 3, we introduce the methods used to analyze the distinct groups of urban street users’ perceptions: chi-square association tests and decision trees. In Section 4, a summary description of the sample is presented and the main analysis results discussed. Section 5 draws some conclusions, followed by the references listed in Section 6. 2 LITERATURE REVIEW
Some urban street users have the impression that the reduction of speed limits leads to an increase in travel times, travel delays and congestions (OPAS/OMS, 2017). However,
according to Archer et al. (2008), in the urban environment, drivers are often likely to stop
and slow down due to congestions, regulatory control at intersections, pedestrian crossings and reduced speed areas (schools and residential areas). Thereby, even during off-peak times, there is a large variation in the individual speed profiles that are independent of the posted speed limits.
Studies carried out by the Traffic Engineering Company of São Paulo - CET/SP analyzed a case in which the speed limit reduction on urban streets in the city did not modify the traffic capacity (Santos and Vilanova, 2012). Furthermore, it even resulted in a reduction of the
deaths caused by traffic accidents (Pinto et al., 2016). Moreover, there was no reduction in
the average value of the maximum slowdowns between April, 2015 and August, 2016 on the main streets alongside the Tietê and Pinheiros rivers (Sarno, 2016), and the percentage of delay over total time due to congestion did not change between 2015 and 2016 (CET/SP, 2016; CET/SP, 2017).
A study conducted by Dijkema et al. (2008) in The Netherlands also revealed that a speed
limit reduction did not increase the congestion levels. The authors also found a significant decrease in inhalable particulate matter because of a speed limit reduction on part of the Amsterdam ring highway. Furthermore, other studies have shown that trips by active modes are impaired due to the high speeds and densities of urban traffic flows (Anciaes, 2015; Mouette and Waisman, 2004).
Active modes for short distance travel have been gaining more and more prominence in research studies and government programs. This can be explained by the increase in the number of motorized vehicles in urban areas of various cities around the world. According to WHO (2015), there was an increase of 25.9% in the motorized registered vehicles in Brazil during the period from 2010 to 2013, while the worldwide increase for the same period corresponded to 16.0%. The increasing number of motorized vehicles also raised the CO2 emissions in the atmosphere (from vehicles using internal combustion engines), noise pollution and traffic congestion. Active modes represent a sustainable alternative for reducing the use and negative impacts of motorized vehicles on urban streets, with additional benefits to the health of people and social interaction.
As identifying stimuli and deterrents to active mode trips is complex and varies from user to user, understanding the behavior and perception of different groups of users is essential. Conditions that stimulate non-motorized trips, according to different authors are: routes
away from traffic pollution (noise and air pollution) and scenic routes (Winters et al., 2011);
and Voros, 2007; Sener et al., 2009), cycling routes integrated with public transport (Pucher
et al., 2010), with wide lanes, enlarged visibility in intersections and extensive arborization
(Providelo and Sanches, 2011); urban streets with low speed limits and few intersections
(Providelo and Sanches, 2011; Sener et al., 2009); improved traffic education and increased
street safety (López and Wong, 2017) and low traffic volume (Sener et al., 2009, Stinson
and Bhat, 2003).
Regarding the deterrents, it is worth highlighting: absence of bicycle lanes (Dill and Voros, 2007); lack of access to a bicycle; lack of need or desire to walk or ride a bicycle; health restrictions; adverse weather (NHTSA, 2008). In the specific case of urban streets, Winters
et al. (2011) highlight the negative impact of the presence of debris, high traffic volumes
and speeds. One aspect pointed out by López and Wong (2017) further reveals that users’ main complaints were related to the differences in speeds between transport modes, whereby pedestrians complained about cyclists and cyclists complained about motor vehicle drivers. The latter study was the only one that more specifically addressed users’ perceptions regarding speed, which is the focus of the present study.
3 METHODS
Assessment of distinct groups of urban street users’ perceptions regarding speed limit reductions and motivators to walking and cycling trips was carried out using an online questionnaire designed to address mainly professionals and students involved with urban
and transportation planning in Brazil, according to Ferreira et al. (2017).
The complete questionnaire consists of questions for users’ characterization (gender, age, municipality and state, level of formal education, profession, frequency of using transport modes in daily commutes, etc.), and specific questions (with a multiple-choice part and an open question part) to investigate opinions on sustainable urban mobility, totaling 35
questions (Ferreira et al., 2017). One question used for characterization and a specific
two-part question of the second group were selected for this study. The characterization question refers to the users’ most frequently used transport mode in daily commutes. The first part of the opinion question “Do you believe that the speed limit reduction of motorized vehicles (cars, motorcycles, trucks and buses) on some streets can stimulate walking and cycling trips?” had pre-established answers varying from “definitely does not stimulate” to “definitely stimulates”.
The second part consisted of an open question: “If you have comments on the previous question, please use the space below.”, wherein the users were free to leave comments about the first part of the opinion question. The second part of the opinion question was used to identify recurrent keywords. Those were later classified as factors that users consider relevant to stimulate walking and cycling trips, besides or rather than reducing the speed limit.
The evaluation of the interviewed users’ perceptions was initially conducted through chi-square association tests, in which the following aspects were related: the answers of the first part of the opinion question with the most frequently used transport modes; the most frequently used transport modes with the factors identified in the second part of the opinion question and also the answers of the first part with the factors identified in the second part. Once associations were identified, the users’ perceptions could be modeled with decision trees, in which the dependent variable was the first part of the opinion question and the
independent variables corresponded to: (i) the most frequently used transport modes and (ii) the factors identified as strong motivators of walking and cycling trips.
4 RESULTS
The questionnaires were sent to over 9,000 individuals between February and April 2017, with a return of 2,863 replied questionnaires. The responses to the characterization question related to the frequency of use of transport modes in daily commutes have five ordered response levels varying from “never” to “always”. To simplify the analysis, it was necessary to adapt this question into the most frequently used transport mode in daily commutes because due to the way the question was elaborated there would be five variables (one for each mode - bicycle, car, motorcycle, public transport and walking) with five categories each. Once the adaptation was carried out, the most frequently used transport mode in daily commutes for each user could be identified. Therefore, 127 observations were discarded, resulting in a sample of 2,736 valid observations. The sample had a good representation in all regions of Brazil, including respondents from all the states in the country. The predominant respondents’ backgrounds are Architecture and Urbanism (32.7%) and Civil Engineering (20.1%). Among the respondents, 36.4% stated that they work as technicians, 31.4% are researchers, mainly lecturers and graduate students, and 7.1% are managers. 4.1 Exploratory Data Analysis
The first part of the opinion question investigated the effect of the traffic speed of urban streets on walking and cycling trips. Among the options of the pre-established answers, users could choose: definitely does not stimulate, almost does not stimulate, may or may not stimulate, partially stimulates and definitely stimulates. A synthesis of the absolute and relative frequencies of the responses of the first part in relation to the most frequently used transport modes is presented in Table 1.
Table 1 Frequencies of the responses to the first part of the opinion question (“Do you believe that the speed limit reduction of motorized vehicles (cars, motorcycles, trucks and buses) on some streets can stimulate walking and cycling trips?”) in
relation to the most frequently used transport mode
Transport Modes
Responses to the first part of the opinion question
Total Definitely does
not stimulate
Almost does not stimulate May or may not stimulate Partially stimulates Definitely stimulates Bicycle 3 (0.1%) 5 (0.2%) 17 (0.6%) 12 (0.4%) 19 (0.7%) 56 (2.0%) Car 107 (3.9%) 169 (6.2%) 376 (13.7%) 429 (15.7%) 234 (8.6%) 1315 (48.1%) Motorcycle 8 (0.3%) 10 (0.4%) 41 (1.5%) 33 (1.2%) 29 (1.1%) 121 (4.4%) Public transport 16 (0.6%) 23 (0.8%) 68 (2.5 %) 95 (3.5%) 63 (2.3%) 265 (9.7%) Walking 57 (2.1%) 99 (3.6%) 228 (8.3%) 357 (13.0%) 238 (8.7%) 979 (35.8%) Total 191 (7.0%) 306 (11.2%) 730 (26.7%) 926 (33.8%) 583 (21.3%) 2736 (100.0%)
The sample collected for the second part of the opinion question was relatively small when compared to the first part as it consists of an open question that respondents could choose
whether to answer or not. Therefore, 602 observations were collected, from which 33 observations were discarded due to inconsistencies in the responses.
From the 569 available observations, keywords that could represent the main idea of each user’s comments were identified. Recurrent keywords were then used to identify other factors that users considered relevant to motivate walking and cycling trips. However, as in 104 observations it was not possible to identify keywords, the sample of the second part has 465 valid observations classified into four factors: awareness, infrastructure, safety and walkability.
In Figure 1, we show a summary of absolute and relative frequencies of the most frequently used transport modes and the factors identified in the second part of the opinion question in relation to the responses of the first part.
Fig. 1 Frequencies of the most frequently used transport mode and the factors identified in relation to the responses to the first part of the opinion question (“Do you believe that the speed limit reduction of motorized vehicles (cars, motorcycles, trucks and buses) on some streets can stimulate walking and cycling trips?”) The classification of the keywords into the four factors are illustrated in some of the highlighted answers (originally in Portuguese), as follows:
“(...) How to convince someone to get out of the shade and air conditioning to go on a 15 to 20-minute walk under the scorching hot sun?” (female, aged between 31 and 39 years old, public transport user - keyword identified: weather and response classified as walkability).
“People have individual and collective cultural aspects. In the Brazilian case, choices are geared towards convenience, lack of awareness (...)” (male, aged between 40 and 49 years old, car driver - keyword identified: awareness and response classified as awareness).
“(...) I believe in exclusive lanes for pedestrians and cyclists that are functional, that can connect areas of interest of the population (...). What there is most of in Brazilian cities are recreational bicycle paths that ‘connect nothing to nowhere’.” (male, aged between 31 and 39 years old, car driver - keyword identified: suitable infrastructure and response classified as infrastructure).
“(...) more signposted streets, safer sidewalks and a stronger enforcement policy regarding the irregular occupation of street vendors of all kinds, who literally end up pushing pedestrians into the middle of the street.” (male, aged between 31 and 39 years old, motorcycle driver - keyword identified: public safety and response classified as safety).
4.2 Association test
The chi-square association test was used to check the association significance between two qualitative variables and to compare the samples. In the comparison of the variables of the first part of the opinion question with the most frequently used transport mode, 4.0% of the expected frequencies had values under 5.0. The adjustment of these values was done by joining the categories “definitely does not stimulate” and “almost does not stimulate” in the category “does not stimulate”. This combination was not a problem given that the chi-square association test considering only the two categories showed no association between them. Having joined the categories into “does not stimulate”, the test was repeated. The sum of the chi-square partial statistics of each transport mode and response category resulted in 44.2
with a p-value equal to 0.0014x10-2. Considering the chi-square distribution with 12 degrees
of freedom at a significance level of 0.01, the critical value is equal to 26.22. Thus, the test suggests an association between the qualitative variables of the first part of the opinion question and the most frequently used transport mode at a significance level lower than 0.01, as shown in Table 2.
The association test to compare the samples corresponding to the most frequently used transport modes in relation to the factors identified as motivators for walking and cycling trips presented 35.0% of the expected counts with values under 5.0. The adjustment of these values was done by joining the categories “walking” and “bicycle” into a new category called “non-motorized modes”, and the categories “car” and “motorcycle” into the category “private motorized modes”. Having acquired these new categories, the test was repeated,
and the result obtained was equal to 3.3 with a p-value equal to 0.7740. Considering the
chi-square distribution with 6 degrees of freedom at a significance level of 0.05, the critical value is equal to 12.59. Thus, the test does not present evidence of an association between the samples corresponding to the most frequently used transport modes in relation to the factors identified from the answer to the open question.
Table 2 Chi-square test between categorical variables of the responses to the first part of the opinion question (“Do you believe that the speed limit reduction of motorized vehicles (cars, motorcycles, trucks and buses) on some streets can stimulate walking
and cycling trips?”) and the most frequently used transport mode Transport
modes
Chi-square statistic
Responses to the first part of the opinion question
Total Does not stimulate May or may not stimulate Partially stimulates Definitely stimulates Bicycle Observed count 8 17 12 19 56 Expected count 10.2 14.9 19.0 11.9 56.0 Chi-square 0.5 0.3 2.6 4.2 Car Observed count 276 376 429 234 1315 Expected count 238.9 350.9 445.1 280.2 1315.0 Chi-square 5.8 1.8 0.6 7.6 Motorcycle Observed count 18 41 33 29 121 Expected count 22.0 32.3 41.0 25.8 121,0 Chi-square 0.7 2.4 1.5 0.4 Public transport Observed count 39 68 95 63 265 Expected count 48.1 70.7 89.7 56.5 265.0 Chi-square 1.7 0.1 0.3 0.8 Walking Observed count 156 228 357 238 979 Expected count 177.8 261.2 331.3 208.6 979.0 Chi-square 2.7 4.2 2.0 4.1
Total Observed count 497 730 926 583 2736
Expected count 497.0 730.0 926.0 583.0 2736.0
Σ chi-squaretotal 44.2
On the other hand, the association test for comparing the variables of the first part of the
opinion question with the identified factors resulted in 59.8 and a p-value equal to
0.0015x10-6. Considering the chi-square distribution with 9 degrees of freedom and a
significance level of 0.01, the critical value is equal to 21.67. Thus, the test suggests an association between the variables of the first part and the identified factors at a level of significance lower than 0.01.
4.3 Decision trees
The modeling of the street users’ perceptions regarding the effect of traffic speed on
pedestrians and cyclists was carried out using decision trees, based on the CART division
algorithm. The IBM SPSS Statistics v. 22 software was used.
According to the chi-square association tests described in Item 4.2, an association between the variables of the responses of the first part of the opinion question and the most frequently used transport mode was observed, as well as between the responses of the first part and the identified factors. However, no association between the most frequently used transport modes and the identified factors was detected. For this reason, only two models were created using decision trees (Figures 2 and 3).
The first decision tree model considers the responses to the first part of the opinion question as the dependent variable and the most frequently used transport mode as the independent variable. This yielded in a risk equal to 0.659 and a standard error equal to 0.009. This model indicates that 33.9% of the users, whose most frequently transport mode is the bicycle, understand that speed limit reductions totally stimulate walking and cycling trips. On the
other hand, 36.3% of the users that walk and use public transport understand that trips are partially stimulated. In addition, 32.6% of the car drivers understand that trips are partially stimulated and 33.9% of motorcyclists comprehend that trips may or may not be stimulated by speed limit reductions, as indicated in Figure 2.
Fig. 2 First decision tree model: dependent variable regarding responses to the first part of the opinion question (“Do you believe that the speed limit reduction of motorized vehicles on some streets can stimulate walking and cycling trips?”) and
Fig. 3 Second decision tree model: dependent variable regarding the responses to the first part of the opinion question (“Do you believe that the speed limit reduction of
motorized vehicles on some streets can stimulate walking and cycling trips?”) and independent variable regarding the identified factors from the second part of the
question (“If you have comments on the previous question, please use the space below”)
The second decision tree model considers the responses to the first part of the opinion question as the dependent variable and the identified factors as the independent variable. This yielded in a risk equal to 0.716 and a standard error equal to 0.021. This model demonstrates that some users share the perception that walking and cycling trips are partially stimulated by common factors: awareness/walkability (34.8%) and infrastructure (42.1%). Moreover, 61.2% of the users who indicated safety comprehend that those trips are definitely or partially stimulated, as shown in Figure 3.
5 CONCLUSIONS
The descriptive analysis of the sample shows that the vast majority of the interviewed users most frequently walk (35.8%) and drive cars (48.1%) on their daily commutes. Concerning the first part of the opinion question, the largest portion of the respondents believe that walking and cycling trips may or may not be stimulated (26.7%) or that they are partially stimulated (33.9%) by the speed limit reduction of motorized vehicles. Furthermore, the majority identified infrastructure (40.9%) as a relevant factor to motivate walking and cycling trips. The combinations that produced the highest frequencies correspond to: “partially stimulates”, related to walking and infrastructure (9.0% of the total); “may or may not stimulate”, related to car mode and infrastructure (8.0% of the total); and “partially stimulates”, related to car mode and infrastructure (7.3% of the total).
The chi-square association test also revealed that the street users’ perceptions regarding the speed limit reduction and the motivation of walking and cycling trips are associated with the most frequently used transport mode and the identified factors. However, the users’ most frequently used transport modes on daily commutes are not associated with the identified factors.
In general, walking and cycling trips were not associated with the responses “definitely does not stimulate” and “almost does not stimulate” in any perception of the groups of urban street users (both modes and factors groupings). However, in the case of walking and cycling trips, it was possible to observe that: i) these trips may or may not be stimulated in motorcycle users’ perceptions; ii) these trips are partially stimulated in the perceptions of pedestrians, car drivers, public transport users and users who pointed out safety, walkability and awareness as relevant factors; and iii) these trips are totally stimulated in the perceptions of cyclists and users that indicated safety as a relevant factor.
Therefore, the majority of the interviewed users perceived that speed limit reductions on urban streets stimulate walking and cycling trips. In addition, users understand that measures to improve safety, walkability, infrastructure and awareness can also stimulate walking and cycling, besides or rather than reducing the speed limit on urban streets.
It is worth noting that the findings of the study cannot be generalized as the data were collected mainly among experts in the field of urban and transportation planning. On the other hand, given the influence of these professionals in transport infrastructure management, their perceptions are very relevant for shaping public policies aiming at promoting active mode trips.
6 ACKNOWLEDGEMENT
The authors thank the Brazilian agencies FAPESP (São Paulo Research Foundation), CNPq (Brazilian National Council for Scientific and Technological Development) and CAPES
(Post-Graduate Federal Agency) for supporting the development of this work in different ways and periods.
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