Bus stop | EPFL Graph Search

A bus stop is a place where buses stop for passengers to get on and off the bus. The construction of bus stops tends to reflect the level of usage, where stops at busy locations may have shelters, seating, and possibly electronic passenger information systems; less busy stops may use a simple pole and flag to mark the location. Bus stops are, in some locations, clustered together into transport hubs allowing interchange between routes from nearby stops and with other public transport modes to maximise convenience. Types of service For operational purposes, there are three main kinds of stops: Scheduled stops, at which the bus should stop irrespective of demand; request stops (or flag stop), at which the vehicle will stop only on request; and hail and ride stops, at which a vehicle will stop anywhere along the designated section of road on request. Certain stops may be restricted to "discharge/set-down only" or "pick-up only". Some stops may be designated as "timing poin

A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Konstantinos Ampountolas, Nikolaos Geroliminis, Nan Zheng

Recent research has studied the existence and the properties of a macroscopic fundamental diagram (MFD) for large urban networks. The MFD should not be universally expected as high scatter or hysteresis might appear for some type of networks, like heterogeneous networks or freeways. In this paper, we investigate if aggregated relationships can describe the performance of urban bi-modal networks with buses and cars sharing the same road infrastructure and identify how this performance is influenced by the interactions between modes and the effect of bus stops. Based on simulation data, we develop a three-dimensional vehicle MFD (3D-nu MFD) relating the accumulation of cars and buses, and the total circulating vehicle flow in the network. This relation experiences low scatter and can be approximated by an exponential-family function. We also propose a parsimonious model to estimate a three-dimensional passenger MFD (3D-pMFD), which provides a different perspective of the flow characteristics in hi-modal networks, by considering that buses carry more passengers. We also show that a constant Bus-Car Unit (BCU) equivalent value cannot describe the influence of buses in the system as congestion develops. We then integrate a partitioning algorithm to cluster the network into a small number of regions with similar mode composition and level of congestion. Our results show that partitioning unveils important traffic properties of flow heterogeneity in the studied network. Interactions between buses and cars are different in the partitioned regions due to higher density of buses. Building on these results, various traffic management strategies in hi-modal multi-region urban networks can then be integrated, such as redistribution of urban space among different modes, perimeter signal control with preferential treatment of buses and bus priority. (C) 2014 Elsevier Ltd. All rights reserved.

Elsevier2014

A systematic analysis of multimodal transport systems with road space distribution and responsive bus service

Nikolaos Geroliminis, Fangni Zhang, Nan Zheng

A smart design of transport systems involves efficient use and allocation of the limited urban road capacity in the multimodal environment. This paper intends to understand the system-wide effect of dividing the road space to the private and public transport modes and how the public transport service provider responds to the space changes. To this end, the bimodal dynamic user equilibrium is formulated for separated road space. The Macroscopic Fundamental Diagram (MFD) model is employed to depict the dynamics of the automobile traffic for its state-dependent feature, its inclusion of hypercongestion, and its advantage of capturing network topology. The delay of a bus trip depends on the running speed which is in turn affected by bus lane capacity and ridership. Within the proposed bimodal framework, the steady-state equilibrium traffic characteristics and the optimal bus fare and service frequency are analytically derived. The counter-intuitive properties of traffic condition, modal split, and behavior of bus operator in the hypercongestion are identified. To understand the interaction between the transport authority (for system benefit maximization) and the bus operator (for its own benefit maximization), we examine how the bus operator responds to space changes and how the system benefit is influenced with the road space allocation. With responsive bus service, the condition, under which expanding bus lane capacity is beneficial to the system as a whole, has been analytically established. Then the model is applied to the dynamic framework where the space allocation changes with varying demand and demand-responsive bus service. We compare the optimal bus services under different economic objectives, evaluate the system performance of the bimodal network, and explore the dynamic space allocation strategy for the sake of social welfare maximization.

2018

How do Transport Infrastructure and Policies Affect House Prices and Rents? Evidence from Athens, Greece

Dimitrios Efthymiou

The interaction between land use and transportation infrastructure is a topic that has been extensively researched and continues to be of interest as new underlying economic, infrastructure and environmental conditions emerge. In this research, the direct and indirect effects of transportation infrastructure and policies on house prices and rents are studied. Since real estate transaction data are not available, a web-scraping tool was developed to parse house prices and attributes from publicly available resources. Econometric models of two categories were then estimated: (1) hedonic price models, based on Ordinary Least Squares (OLS) and (2) spatial econometric models, such as the spatial regression model (SAR), spatial error (SEM), Durbin (SDM) and autocorrelation (SAC) model and Geographically Weighted Regression (GWR), which are increasingly used by econometricians in order to capture the effect of the - usually unobserved - spatial factors on house valuation. The results of this research indicate that proximity to transportation infrastructure has a direct impact on house and apartment purchase prices and rents, which is either positive or negative depending on the type of the transportation system. Metro, tram, suburban railway and bus stations affect the prices positively, while ISAP (the old urban railway of Attica) and national rail stations, airports and ports, have a negative effect, due to a number of externalities associated with them, such as noise. The obtained results are consistent with expectations and the literature. While these results cannot be assumed directly transferable to other locations and areas, they could be cautiously used as indications for planning applications (where dedicated models have not been developed). (C) 2013 Elsevier Ltd. All rights reserved.

Pergamon-Elsevier Science Ltd2013