DEVELOPING A FRAMEWORK TO PRIORITIZE AND ASSESS THE TRAFFIC IMPACTS OF LOW TRAFFIC NEIGHBORHOODS: A CASE STUDY IN BEIRUT

Abstract

For the better part of the past century, streets have been designed with the private vehicle in mind. It is not until relatively recently that a surge in design ideas putting humans and their social and physical health as priority was observed in many cities around the world. One scheme that aims at reducing the harms of private vehicle dependence, especially on urban residential neighborhoods, is the Low Traffic Neighborhood (LTN). It is a simple idea based on preventing through-traffic from passing in predominantly residential neighborhoods and prioritizing pedestrian and soft mobility movement within their boundaries by using simple tools like modal filters, bollards, and street direction reassignment. Vehicular traffic can always reach any destination within the neighborhood, but it cannot cut through it to reach a parallel main road. This thesis develops a framework that defines the boundaries, prioritizes implementation, and assesses the traffic impact of LTN schemes. The boundaries are placed based on a set of criteria and assessed by locals and experts to fine tune them. Then the LTNs are ranked in terms of priority of implementation relating to each LTN’s likelihood to succeed and expected impact level. After that, implementation is usually done gradually with local feedback improving every iteration. The implementabilty is assessed qualitatively by interviewing stakeholders, experts, and locals. The traffic impact is assessed using an EMME traffic model. The model is set up by defining the suggested LTNs as new traffic analysis zones and then using Institution of Transportation Engineers (ITE) trip generation rates and traffic counts to calibrate and update the model. The model is run with current conditions and later with the implemented interventions. Before and after percentages of through-traffic on identified through-streets and total traffic on boundary streets of the LTNs are compared. This thesis also investigates a case study of implementing the framework of proposed LTNs within the context of a developing country, and specifically within the challenges presented in Beirut, Lebanon. The chosen area that lies at the east of municipal Beirut is characterized by an existing urban landscape that is too dependent on private vehicles. The results show that implementing LTNs decreases the through-traffic by 33% on average on internal streets but increases traffic by 9% on average on boundary roads as expected. However, after implementing a 15% reduction in trip demand from and to the implemented LTNs to simulate mid to long-term effects, the traffic on boundary roads decreased again: in some cases, less than the base conditions. The traffic reduction effect on higher ranked implemented LTNs was found to be higher than on the lower ranked ones which corroborates the results of the prioritization framework presented by this research. More intrusive interventions were considered favoring complete through-traffic prevention over maintaining easy access to commuters reaching destinations within the LTN with the effect on travel time being minimal when compared to the less intrusive intervention. The framework presented by this research may be used as a tool by cities that are considering implementing LTNs.