Zohreh Asadi-Shekari

Non-motorised Level of Service: Addressing Challenges in Pedestrian and Bicycle Level of Service

Motorised vehicle conditions have been evaluated by many researchers. In contrast, there are very limited studies on vulnerable and non-motorised users, such as cyclists and pedestrians, specifically children, the elderly and the disabled. Thus, this paper reviews prominent studies on street evaluations to identify effective indicators for non-motorised trips. The street condition for these trips is measured by the bicycle level of service (BLOS) and the pedestrian level of service (PLOS). In previous studies, different methods have been introduced for PLOS and BLOS. However, these methods have several major shortcomings. First, pedestrians and cyclists are assumed to be users who can share street facilities with motorised vehicles and thus are considered equivalent to cars. Second, the majority of these methods are complicated and time-consuming, and it is difficult to connect them to a design process. Furthermore, these methods support only a limited number of walking and cycling facilities; therefore, they may not be valid for a wide range of pedestrians and cyclists with a diverse variety of abilities and ages. This study discusses the challenges in the BLOS and PLOS research and attempts to introduce new objectives for further studies in this field to eliminate the aforementioned shortcomings.

Disabled Pedestrian Level of Service Method for Evaluating and Promoting Inclusive Walking Facilities on Urban Streets

Current analytical methods to estimate the pedestrian level of service (PLOS) usually only consider a narrow range of pedestrians and may not be applicable for more diverse pedestrian populations with different characteristics. The aim of this study is to conceptualize the disabled pedestrian level of service (DPLOS) for different street hierarchies not previously addressed to ensure inclusive walking conditions. An analytical point system comparing existing pedestrian facilities to a standard is proposed to estimate the DPLOS. Although this practical model is only used for one case study in Singapore, the use of international standards would make this model universally applicable.

A Bicycle Safety Index for Evaluating Urban Street Facilities

Objectives: The objectives of this research are to conceptualize the Bicycle Safety Index (BSI) that considers all parts of the street and to propose a universal guideline with microscale details. Method: A point system method comparing existing safety facilities to a defined standard is proposed to estimate the BSI. Two streets in Singapore and Malaysia are chosen to examine this model. Results: The majority of previous measurements to evaluate street conditions for cyclists usually cannot cover all parts of streets, including segments and intersections. Previous models also did not consider all safety indicators and cycling facilities at a microlevel in particular. This study introduces a new concept of a practical BSI to complete previous studies using its practical, easy-to-follow, point system–based outputs. Conclusions: This practical model can be used in different urban settings to estimate the level of safety for cycling and suggest some improvements based on the standards.

Analyzing the relationships between travel mode indicators and the number of passenger transport fatalities at the city level

ABSTRACT Objective: A number of efforts have been conducted on travel behavior and transport fatalities at the neighborhood or street level, and they have identified different factors such as roadway characteristics, personal indicators, and design indicators related to transport safety. However, only a limited number of studies have considered the relationship between travel behavior indicators and the number of transport fatalities at the city level. Therefore, this study explores this relationship and how to fill the mentioned gap in current knowledge. Method: A generalized linear model (GLM) estimates the relationships between different travel mode indicators (e.g., length of motorway per inhabitants, number of motorcycles per inhabitant, percentage of daily trips on foot and by bicycle, percentage of daily trips by public transport) and the number of passenger transport fatalities. Because this city-level model is developed using data sets from different cities all over the world, the impacts of gross domestic product (GDP) are also included in the model. Conclusions: Overall, the results imply that the percentage of daily trips by public transport, the percentage of daily trips on foot and by bicycle, and the GDP per inhabitant have negative relationships with the number of passenger transport fatalities, whereas motorway length and the number of motorcycles have positive relationships with the number of passenger transport fatalities.

The Relationship between Urban Structure and Travel Behaviour: Challenges and Practices

Since urban structure indicators influence travel behaviour, they have been widely studied. The goal of these studies was identifying effective factors to have sustainable transport patterns . However, investigating these factors has been problematic and the results are not reliable enough to be used universally. There are two main reasons for this:firstly, because socio-economic indicators impact neighbourhoods with comparable design differently; and secondly, factors such as income, and age, as well as self-selection factors are not easy to be evaluated. This paper addresses challenges and practices in this area to propose new objectives for further studies that cover previous shortcomings.

The relationship between urban street networks and private motorized trips at the city level

ABSTRACT There are factors that impact car usage in urban areas, such as density, diversity and design, but there have been few studies that examine the relationship between street network factors and car usage at the city level (macro level). This paper focuses on this relationship by introducing urban street network variables, such as blocks per area, nodes per block and length of roads and motorways, as independent variables and the percentage of daily trips by private motorized modes as the dependent variable. The street network in this study includes interconnecting lines and points that present streets, roads, motorways, intersections and blocks. The strength of the relationship in this study is found using multiple linear regression. The findings of this research indicate that an increase in car usage is correlated with an increasing number of blocks per area, number of nodes per block and length of motorways. In addition, because the urban street network is the result of macro-scale planning decisions, considering this relationship can lead to better planning decisions.