The Impact of Alternative Access Modes on Urban Public Transport Network Design

Public transport network design determines the quality for travellers as well as operational costs. Network design is therefore crucial for the cost effectiveness of urban public transport. In urban public transport network design it is commonly assumed that all travellers walk to the stops. This might be true for short access distances, but if stop and line spacing increase other modes such as bicycles might become interesting as an alternative access mode. An analytical model is presented that determines optimal network characteristics, i.e. stop spacing, line spacing, and frequency, and that explicitly accounts for alternative access modes. The objective used is maximising social welfare. Results show that, if cycling is considered as an alternative access mode, all three network characteristics mentioned above should be increased, offering benefits for the traveller, the operator as well as the society. However, if there is a large sub-population of travellers who are not able to use the alternative mode, or if there are barriers for using an alternative mode to access the urban public transport system, it is better to assume that walking is the only access mode available. In the case of cycling as an access mode there are possibilities for positive benefits, at least in countries such as Denmark or the Netherlands. It is expected that for other access modes, such as peoplemovers and demand responsive public transport systems, the barriers are too high to have an impact on urban public transport network design

Choice Set Generation for Multi-modal Travel Analysis

Multi-modal trips are a common travel phenomenon, which are expected to become more important in the future because of their expected contribution to sustainable urban transportation. However, multiple different types of travel choices, such as transport service types, travel modes, and transfer locations, are involved in a multi-modal trip, making it difficult to model multi-modal traveling. We present a method that generates choice sets of multi-modal routes using a supernetwork, which might be used for prediction purposes. This method considers stochasticity in the perception of the network attributes as well as in the preferences for the different trip components. The primary objective of the paper is to analyze the comparison of generated route sets and observed route sets. Three options for generating route sets have been studied, i.e.: variation in the network attributes only, variation in traveler preferences only, and the combination of both. The latter case proved to yield the best match with observed route sets. Furthermore, the analysis shows that variation in travelers’ preferences is more important than variation in network attributes. Recommendations for further improvement of the choice set generation method are included. The analysis revealed insights into the possibilities of generating realistic multi-modal route sets and it is proved that the randomization approach is feasible providing good coverage of the observed routes. By far the best results are obtained by randomizing both network attributes and variation in traveler preferences

Modelling travel time reliability in public transport route choice behaviour

The implementation of travel time reliability (TTR) in route choice behaviour is still not very common in transport models, especially not in a public transport context. The reasons probably are that it is difficult to measure and that there is no agreement how it best can be represented in utility functions. Typically, it is represented by a standard deviation, however, particularly in public transport choices it is more likely that travellers think about the consequences of unreliability in travel times in terms of buffer times. This paper contributes to the literature by comparing five different model specifications of TTR in public transport route choices that are either based on standard deviations or on buffer time indicators. The models are estimated from choices observed in a stated choice experiment. To address heterogeneity, a latent class model is estimated. The results suggest that the reliability buffer time indicator outperforms the standard deviation indicator. Furthermore, the reliability buffer time parameter is only statistically significant in two of the four classes. The other two classes are particularly sensitive to making transfers and to low frequencies of public transport services, suggesting different strategies to deal with TTR

Interventions in Bicycle Infrastructure, Lessons from Dutch and Danish Cases

AbstractToday the interest in cycling is increasing worldwide and in many countries authorities are faced with the question how cycling can be promoted efficiently. In the Netherlands and Denmark, this question came up already in the 1970s when the downsides of the rapidly increasing motorisation became evident. At the time, in both countries large scale interventions in bicycle infrastructure were introduced and evaluated extensively in order to create knowledge on efficient promoting of cycling in urban areas. The interventions included the construction of new bicycle routes on urban arterials in some larger cities and an area wide comprehensive upgrade of the bicycle network one medium sized city (Delft). The evaluations were based on before and after studies where in the case of Delft also a long-term after study was performed. The evaluations produced a wealth of information about the impacts of interventions in bicycle infrastructure on travel choices, safety, design appreciation, and other factors. These clarify under which conditions certain measures are effective or not and inform about the effectiveness of improving a single route versus upgrading a whole network. The information from the studies was used in both countries for formulating guidelines for road and bicycle infrastructure design. However, at that time the study results were not shared with the international scientific audience. The paper describes briefly the classical cases and the main study results.The outcomes of the classical studies are compared with those of some more recent cases of assessed interventions in urban bicycle infrastructure in the Danish largest cities. Generally the outcomes are in line with those from the classical studies. This indicates that results of the latter are rather timeless and are likely to be still generally valid. In addition to studies that traditionally focus on dedicated bicycle infrastructure, two cases of shared space are discussed, a rather new type of intervention that assumes mixed use of infrastructure. One case is from Denmark, the other from the Netherlands.The paper will so uncover the valuable results of the possibly largest evaluations of interventions in bicycle infrastructure ever made, verify these by examining more recent studies, and contribute to the discussion of shared space

Recommendations for a large-scale European naturalistic driving observation study. PROLOGUE Deliverable D4.1.

Naturalistic driving observation is a relatively new research method using advanced technology for in-vehicle unobtrusive recording of driver (or rider) behaviour during ordinary driving in traffic. This method yields unprecedented knowledge primarily related to road safety, but also to environmentally friendly driving/riding and to traffic management. Distraction, inattention and sleepiness are examples of important safety-related topics where naturalistic driving is expected to provide great added value compared to traditional research methods. In order to exploit the full benefits of the naturalistic driving approach it is recommended to carry out a large-scale European naturalistic driving study. The EU project PROLOGUE has investigated the feasibility and value of carrying out such a study, and the present deliverable summarises recommendations based on the PROLOGUE project

The study design of UDRIVE: the Naturalistic Driving Study across Europe for cars, trucks and scooters

Purpose: UDRIVE is the first large-scale European Naturalistic Driving Study on cars, trucks and powered two wheelers. The acronym stands for "European naturalistic Driving and Riding for Infrastructure & Vehicle safety and Environment". The purpose of the study is to gain a better understanding of what happens on the road in everyday traffic situations. Methods: The paper describes Naturalistic Driving Studies, a method which provides insight into the actual real-world behaviour of road users, unaffected by experimental conditions and related biases. Naturalistic driving can be defined as a study undertaken to provide insight into driver behaviour during everyday trips by recording details of the driver, the vehicle and the surroundings through unobtrusive data gathering equipment and without experimental control. Data collection will take place in six EU Member States. Results: Road User Behaviour will be studied with a focus on both safety and environment. The UDRIVE project follows the steps of the FESTA-V methodology, which was originally designed for Field Operational Tests. Conclusions: Defining research questions forms the basis of the study design and the specification of the recording equipment. Both will be described in this paper. Although the project has just started collecting data from drivers, we consider the process of designing the study as a major result which may help other initiatives to set up similar studies

Ecological Thresholds in the Savanna Landscape: Developing a Protocol for Monitoring the Change in Composition and Utilisation of Large Trees

BACKGROUND: Acquiring greater understanding of the factors causing changes in vegetation structure -- particularly with the potential to cause regime shifts -- is important in adaptively managed conservation areas. Large trees (> or =5 m in height) play an important ecosystem function, and are associated with a stable ecological state in the African savanna. There is concern that large tree densities are declining in a number of protected areas, including the Kruger National Park, South Africa. In this paper the results of a field study designed to monitor change in a savanna system are presented and discussed. METHODOLOGY/PRINCIPAL FINDINGS: Developing the first phase of a monitoring protocol to measure the change in tree species composition, density and size distribution, whilst also identifying factors driving change. A central issue is the discrete spatial distribution of large trees in the landscape, making point sampling approaches relatively ineffective. Accordingly, fourteen 10 m wide transects were aligned perpendicular to large rivers (3.0-6.6 km in length) and eight transects were located at fixed-point photographic locations (1.0-1.6 km in length). Using accumulation curves, we established that the majority of tree species were sampled within 3 km. Furthermore, the key ecological drivers (e.g. fire, herbivory, drought and disease) which influence large tree use and impact were also recorded within 3 km. CONCLUSIONS/SIGNIFICANCE: The technique presented provides an effective method for monitoring changes in large tree abundance, size distribution and use by the main ecological drivers across the savanna landscape. However, the monitoring of rare tree species would require individual marking approaches due to their low densities and specific habitat requirements. Repeat sampling intervals would vary depending on the factor of concern and proposed management mitigation. Once a monitoring protocol has been identified and evaluated, the next stage is to integrate that protocol into a decision-making system, which highlights potential leading indicators of change. Frequent monitoring would be required to establish the rate and direction of change. This approach may be useful in generating monitoring protocols for other dynamic systems

MULTILEVEL NETWORK OPTIMIZATION FOR PUBLIC TRANSPORT NETWORKS

Most studies on public transport network design deal with single-level networks only. Urban public transport networks, however, not only offer transport services to and from the city center but also to stations of interurban public transport networks. A population\u27s use of both types of public transport services implies a dependency between these networks. An analytical model was developed to analyze this dependency for two connected networks. For each network, the operator will adopt a certain objective in optimally designing the network. An analysis was made for the cases in which a single operator is responsible for both networks, or in which two different operators run each network. In all cases the objectives of profit maximization and welfare maximization were used. In the two-operator case, each operator may follow its own objective. The different scenarios led to sensibly different values for stop spacing, line spacing, and frequencies. For interurban public transport companies it appears to be profitable to cooperate with urban public transport companies or to pursue a strategy for local authorities to adopt the objective of welfare maximization for urban public transport network design. In the case of welfare maximization, that is, the authorities\u27 perspective, the impact of two operators instead of a single operator is nearly negligible. The combination of welfare maximization for the urban public transport network and profit maximization for the interurban network indirectly subsidizes interurban public transport. These findings provide interesting insights for authorities responsible for commissioning public transport services

MULTI-CLASS URBAN TRANSIT NETWORK DESIGN

In transit network design it is common to use characteristics of the average traveler to describe travel behavior, while in reality different traveler groups can be distinguished that react differently with respect to transport service quality. A study is conducted of the possible consequences of basing the design of urban transit networks on the preferences of specific traveler groups. To that end, an analytical network optimization model is developed that considers a mix of different traveler groups simultaneously. Results from the analyses show that focusing on specific traveler groups leads to clearly different network design characteristics. However, the optimal network design developed for the average traveler proved to be the best network for all traveler groups. Furthermore, it was found that focusing on traveler groups having good transport alternatives led to very low values of consumer surplus and social welfare. Optimizing transit networks while considering different traveler groups simultaneously results in networks that are similar to those using the traditional single-user-class approach based on the average traveler. Differences in preferences for traveler groups are balanced by the size of the resulting transit patronage. Apparently, a more realistic description of the demand side is not essential for urban transit network design

Regularity analysis for optimizing urban transit network design

Transit network planners often propose network structures that either assume a certain level of regularity or are even especially focused on improving service reliability, such as networks in which parts of lines share a common route or the introduction of short-turn services. The key idea is that travelers on that route will have a more frequent transit service. The impact of such network designs on service regularity is rarely analyzed in a quantitative way. This paper presents a tool that can be used to assess the impact of network changes on the regularity on a transit route and on the level of transit demand. The tool can use actual data on the punctuality of the transit system. The application of such a tool is illustrated in two ways. A case study on introducing coordinated services shows that the use of such a tool leads to more realistic estimates than the traditional approach. Second, a set of graphs is developed which can be used for a quick scan when considering network changes. These graphs can be used to assess the effect of coordinating the schedules and of improving the punctuality