Integrating transport and land-use planning? How steering cultures in local authorities affect implementation of integrated public transport and land-use planning

Previous research has shown integrated planning to be important for achieving aims concerning more environmentally friendly transport operations, but less good at explaining prerequisites of implementation. This paper analyses how management and working practises in local authorities, here understood as steering cultures, affect implementation of integrated land-use and public transport planning approaches. The analysis builds on case studies of planning in two Swedish municipalities. These have developed two antithetical steering cultures, namely one that can be described as deliberative and one that can be described as sectorised. The paper describes the advantages and disadvantages of these steering cultures. The findings show the deliberative model to facilitate integration through advanced mechanisms of consensus and co-ordination between policy-makers and officials. The sectorised model has no such mechanisms, but this need not result in poor prospects of integrated planning. It is important for integrated planning approaches, whatever the steering culture, to be in line with the institutionalised norms and objectives by which planning practices are governed. Integration therefore needs a normative component, so as to ensure implementation. The important normative component in this context can be construed as discourses and rationales concerning transport and the urban development of which public transport forms part.     

Transport planning in Hungary: a case study of Pécs

This review emerged from an opportunity provided in 1988 to the author to study the process of Hungarian transport planning in general, and that of the major regional city of Pécs in particular.

It begins by outlining the difficulties of obtaining detailed information on transport policy‐making and planning in Eastern Europe, and then goes on to analyse the situation in Hungary as a whole since the early 1960s. The specific situation in Pécs is then discussed in relation to national transport planning, with detailed case studies drawn from problems on the local and regional road network, the growth in car ownership and usage, the development of local and inter‐regional rail services, the provision of adequate local bus services, and the growth of local taxi services.

The problems stemming from State intervention and planning control in local transport are emphasized, as are the increasingly difficult issues of the Hungarian economy in constraining public investment. The paper concludes with a discussion of the relationship of the problems of Pécs with those of urban areas elsewhere in Europe, and emphasizes the particular difficulties faced by East European planners in the future.     

Public participation in the Helsinki crosstown artery project

The paper reports on citizen participation in the planning of Helsinki Crosstown Artery in the early 1990s. The project had difficult beginnings: there was disagreement on benefits and costs, a broad-based mistrust, and an externally prepared work program which sought to resolve these emotional disagreements using technical information. The citizen participation program consisted of Open Houses preceded by a newsletter, newspaper advertisements, a 1–800 Number hotline, and a responsiveness summary. Additional techniques were used as necessary. The design of the citizen participation program was sound and inexpensive, provided for continuous evaluation, and drove the planning work. Substantial informed consent was created in the project. The main conclusion from the present case study is this: in planning and in public participation emotional issues dominate and can rarely be solved by “rational” studies. The citizen participation technique evolved during the study is transferable and has broad planning implications.     

Passenger Perspectives in Railway Timetabling: A Literature Review

When looking at railway planning, a discrepancy exists between planners who focus on the train operations and publish fixed railway schedules, and passengers who look not only at the schedules but also at the entirety of their trip, from access to waiting to on-board travel and egress. Looking into this discrepancy is essential, as assessing railway performances by merely measuring train punctuality would provide an unfair picture of the level of service experienced by passengers. Firstly, passengers’ delays are often significantly larger than the train delays responsible for the passengers to be late. Secondly, trains’ punctuality is often strictly related to too tight schedules that in turn might translate into knock-on delays for longer dwelling times at stations, trip delays for increased risk of missing transfer connections, and uncertain assessment of the level of service experienced, especially with fluctuating passenger demand. A key aspect is the robustness of railway timetables. Empirical evidence indicates that passengers give more importance to travel time certainty than travel time reductions, as passengers associate an inherent disutility with travel time uncertainty. This disutility may be broadly interpreted as an anxiety cost for the need for having contingency plans in case of disruptions, and may be looked at as the motivator for the need for delay-robust railway timetables. Interestingly, passenger-oriented optimisation studies considering robustness in railway planning typically limit their emphasis on passengers to the consideration of transfer maintenance. Clearly, passengers’ travel behaviour is far more complex and multi-faceted and thus several other aspects should be considered, as becoming more and more evident from passenger surveys. The current literature review starts by looking at the parameters that railway optimisation/planning studies are focused on and the key performance indicators that impact railway planning. The attention then turns to the parameters influencing passengers’ perceptions and travel experiences. Finally, the review proposes guidelines on how to reduce the gap between the operators’ railway planning and performance measurement on the one hand and the passengers’ perception of the railway performance on the other hand. Thereby, the conclusions create a foundation for a more passenger-oriented railway timetabling ensuring that passengers are provided with the best service possible with the resources available.     

Path flow estimator for planning applications in small communities

This paper presents an alternative planning framework to model and forecast network traffic for planning applications in small communities, where limited resources debilitate the development and applications of the conventional four-step travel demand forecasting model. The core idea is to use the Path Flow Estimator (PFE) to estimate current and forecast future traffic demand while taking into account of various field and planning data as modeling constraints. Specifically, two versions of PFE are developed: a base year PFE for estimating the current network traffic conditions using field data and planning data, if available, and a future year PFE for predicting future network traffic conditions using forecast planning data and the estimated base year origin–destination trip table as constraints. In the absence of travel survey data, the proposed method uses similar data (traffic counts and land use data) as a four-step model for model development and calibration. Since the Institute of Transportation Engineers (ITE) trip generation rates and Highway Capacity Manual (HCM) are both utilized in the modeling process, the analysis scope and results are consistent with those of common traffic impact studies and other short-range, localized transportation improvement programs. Solution algorithms are also developed to solve the two PFE models and integrated into a GIS-based software called Visual PFE. For proof of concept, two case studies in northern California are performed to demonstrate how the tool can be used in practice. The first case study is a small community of St. Helena, where the city’s planning department has neither an existing travel demand model nor the budget for developing a full four-step model. The second case study is in the city of Eureka, where there is a four-step model developed for the Humboldt County that can be used for comparison. The results show that the proposed approach is applicable for small communities with limited resources.     

Struggling,settling, solutions: A qualitative study of landscape protection in motorway planning

Landscape is an important public interest with social, cultural, ecological, and environmental dimensions. It is central to the formation of local cultures and contributes to human well-being. Some areas are protected by supranational agreements that have significant international value. The European Landscape Convention (ELC) calls for integrating landscape considerations into other policy areas such as motorway planning that may directly or indirectly impact the landscape. The key challenge is the integration of existing institutional backgrounds and governing traditions. This paper compares how two qualitative case studies managed landscape protection while planning motorways. Specifically, we examine two internationally protected areas – one in Hungary that focuses on nature and one in Sweden the focuses on culture – to consider how these areas were assessed during the planning of the new motorways. Analysing the cases through the theoretical lens of institutional interplay, we found that the main differences between the two cases can be attributed to the different governing traditions and interpretations of landscape.     

Heavy-duty trucking and the energy efficiency paradox: Evidence from focus groups and interviews

Theory suggests that profit maximizing firms have an incentive to incorporate cost-effective technologies into their products. However, simple net present value calculations comparing upfront costs of fuel-saving technologies to future savings suggest this is not always the case. This puzzle is commonly referred to as the “energy efficiency paradox.” A growing number of empirical studies examine why households may under-invest in energy efficiency. Fewer studies examine similar undervaluation by businesses. We explore investment decisions within the heavy-duty trucking sector for fuel-saving technologies via focus groups and interviews to gain insight into what factors might explain apparent underinvestment in fuel-saving technologies. We find some evidence that market failures related to lack of information about technology performance and network externalities contribute to slow adoption of some technologies. However, information about new technologies for tractors seems to generate limited spillovers. There is also some evidence of split incentives between owners and drivers, though companies have invested in a variety of technologies and approaches in an attempt to address these effects. Other factors important in trucking investment decisions that are not classic market failures include tradeoffs between fuel economy and other valued truck attributes, as well as uncertainty and risk associated with new technologies if decision-makers are loss averse.     

Procedures for planning multi-leg journeys with fixed-route and demand-responsive passenger transport services

This paper describes journey-planning procedures designed for use in a traveller information system covering fixed-schedule and demand-responsive public transport modes. The task is to construct a sequence of journey-legs to meet a traveller’s requirements with the least possible generalised cost, subject to time-window and other constraints. A journey may be carried out in a single leg by walking or by taking a taxi all the way from the origin to the destination, or by a sequence of one or more legs carried by public transport services sandwiched between walked segments connecting an initial pickup and final setdown stop. The public transport services may include fixed-route modes such as bus and train, and demand-responsive services running between fixed points. The main planning procedures are a high-level request-broker and a branch and bound procedure to handle multi-legged journeys; the request-broker also invokes a fleet-scheduling module to obtain bookings on demand-responsive services. The paper describes planning conditions, the planning procedures, and reduction techniques that are used to obtain acceptable computational performance. Tests with simulated demand suggest that the procedures are well suited for use in a real-time traveller information system.     

Bi-level GA and GIS for Multi-objective TSP Route Planning

Abstract

Route planning is usually carried out to achieve a single objective such as to minimize transport cost, distance traveled or travel time. This article explores an approach to multi-objective route planning using a genetic algorithm (GA) and geographical information system (GIS) approach. The method is applied to the case of a tourist sight-seeing itinerary, where a route is planned by a tour operator to cover a set of places of interest within a given area. The route planning takes into account four criteria including travel time, vehicle operating cost, safety and surrounding scenic view quality. The multi-objective route planning in this paper can be viewed as an extension of the traditional traveling salesman problem (TSP) since a tourist needs to pass through a number of sight points. The four criteria are quantified using the spatial analytic functions of GIS and a generalized cost for each link is calculated. As different criteria play different roles in the route selection process, and the best order of the multiple points needs to be determined, a bi-level GA has been devised. The upper level aims to determine the weights of each criterion, while the lower level attempts to determine the best order of the sights to be visited based on the new generalized cost that is derived from the weights at the upper level. Both levels collaborate during the iterations and the route with the minimal generalized cost is thus determined. The above sight-seeing route planning methodology has been examined in a region within the central area of Singapore covering 19 places of interest.     

Identifying the most critical transportation intersections using social network analysis

Traffic congestion negatively impacts our society. Most of the traditional transportation planning techniques – though effective – require rigorous amounts of data and analysis which consumes time and resources. This paper uses social network analysis (SNA) to analyze transportation networks, and consequently corroborate the effectiveness of SNA as a complementary tool for improved transportation planning. After creating the connection between the language and concepts of SNA and those of transportation systems – as well as developing a model that utilizes different SNA centrality measures within the transportation context – the authors utilize SNA to investigate traffic networks in three case studies in the state of Louisiana, analyze the results and draw conclusions. To this effect, with minimal cost and time, the model identifies the most critical intersections that should be further investigated using traditional techniques. These results are in agreement with the findings of Louisiana’s Department of Transportation and Development.     

Online distributed cooperative model predictive control of energy-saving trajectory planning for multiple high-speed train movements

The cooperative energy-efficient trajectory planning for multiple high-speed train movements is considered in this paper. We model all the high-speed trains as the agents that can communicate with others and propose a local trajectory planning control model using the Model Predictive Control (MPC) theory. After that we design an online distributed cooperative optimization algorithm for multiple train trajectories planning, under which each train agent can regulate the trajectory planning procedure to save energy using redundancy trip time through tuning ACO’s heuristic information parameter. Compared to the existing literature, the vital distinctions of our work lies not only on the online cooperative trajectory planning but also on the distributed mechanism for multiple high-speed trains. Experimental studies are given to illustrate the effectiveness of the proposed methods with the practical operational data of Wuhan-Guangzhou High-speed Railway in China.     

Understanding successful workplace travel initiatives in the UK

Across the world, there is increasing interest in managing car traffic. One approach developed for addressing the journey to work is known as ‘workplace travel planning’. This paper primarily reports on 20 case studies of UK employers undertaking travel planning, who had cut commuter driving by an average of 18%. It concludes that considerable behavioural change can be achieved in a variety of contexts – but employers usually need an overall strategy that addresses car parking, in addition to improving alternative travel modes. Moreover, a more comprehensive national strategy is needed, if travel planning is to achieve its potential.     

Benefit-cost analysis for labor intensive transportation systems

Labor-intensive systems such as bikeways and pedestrian ways suffer in transportation planning in part because traditional benefit-cost analysis focuses on narrow, private transportation savings (e.g., reducing vehicle and time costs).Planners need benefit-cost frameworks which capture the community-wide effects of such innovative transportation systems — reduction in air pollution, less congestion, and increases in exercise and outdoor recreation. This study discusses practical methods for planners to include such categories in their analyses and applies these methods to two case studies. The analysis yields benefit-cost ratios which are much higher than those found in most public projects — suggesting negative returns to marginal automobiles in congested areas such as university campuses. The paper concludes with some suggested bikeway planning guidelines that emerge from expanded benefit-cost analysis.     

Cost escalations in the front-end of projects – empirical evidence from Norwegian road projects

This paper investigates an issue largely ignored in the transport literature on cost overruns, namely, cost increases in the early project phase, long before the decision to build is made. This is the phase of project planning that is referred to as the front-end phase in the literature. The rationale of the study is that unless cost estimates during the front-end phase are relatively accurate, the wrong projects may be selected for further development. We first argue for why it is important to address cost escalation during the front-end phase of project planning. We then use Norwegian data to demonstrate the magnitude of cost escalations during the front-end phase of projects and in comparison to the implementation phase. We find that even in a sample of projects with relatively small cost overruns as in the case of Norway, there are substantial cost increases before the formal decision to build was made. This raises the issue of whether decisions and priorities taken at the early stages of project development are based on false information and whether this may lead to the wrong project concepts being selected.     

Modeling a rail transit alignment considering different objectives

An optimization model for station locations for an on-ground rail transit line is developed using different objective functions of demand and cost as both influence the planning of a rail transit alignment. A microscopic analysis is performed to develop a rail transit alignment in a given corridor considering a many-to-one travel demand pattern. A variable demand case is considered as it replicates a realistic scenario for planning a rail transit line. A Genetic Algorithm (GA) based on a Geographical Information System (GIS) database is developed to optimize the station locations for a rail transit alignment. The first objective is to minimize the total system cost per person, which is a function of user cost, operator cost, and location cost. The second objective is to maximize the ridership or the service coverage of the rail transit alignment. The user cost per person is minimized separately as the third objective because the user cost is one of the most important decision-making factors for planning a transit system from the users’ perspective. A transit planner can make an informed decision between various alternatives based on the results obtained using different objective functions. The model is applied in a case study in the Washington, DC area. The optimal locations and sequence of stations obtained using the three objective functions are presented and a comparative study between the results obtained is shown in the paper. In future works we will develop a combinatorial optimization problem using the aforementioned objectives for the rail transit alignment planning and design problem.     

Freight Data Assembling and Modeling: Methodologies and Practice

Abstract

In comparison to personal travel, freight movements within large metropolitan areas are much less studied. Most conventional transportation models and planning analysis that disregarded freight flows have been criticized on the plausibility of their results and conclusions. To alleviate these problems, this study proposes a non-survey based approach to assemble and process freight data in a systematic way. A freight origin–destination (OD) matrix of freight flows can be developed using secondary data sources. The estimated freight flows can be loaded together with conventional passenger flows onto the regional highway network of a large metropolitan area. As a case study, this non-survey based approach was applied to build a freight OD and study the traffic flows in Los Angeles. It concluded that this approach can be used to analyze urban freight movement in a low-cost way in which planning agencies can overcome the common omission of freight flow information in their transportation plans.     

Modeling the time to the next primary and secondary incident: A semi-Markov stochastic process approach

Incidents are notorious for their delays to road users. Secondary incidents – i.e., incidents that occur within a certain temporal and spatial distance from the first/primary incident – can further complicate clearance and add to delays. While there are numerous studies on the empirical analysis of incident data, to the best of our knowledge, an analytical model that can be used for primary and secondary incident management planning that explicitly considers both the stochastic as well as the dynamic nature of traffic does not exist. In this paper, we present such a complementary model using a semi-Markov stochastic process approach. The model allows for unprecedented generality in the modeling of stochastics during incidents on freeways. Particularly, we relax the oftentimes restrictive Poisson assumption (in the modeling of vehicle arrivals, vehicle travel times, and incidence occurrence and recovery times) and explicitly model secondary incidents. Numerical case studies are provided to illustrate the proposed model.     

Quantifying the environmental and economic benefits of cooperation: A case study in temperature-controlled food logistics

Inefficient road transportation causes unnecessary costs and polluting emissions. This problem is even more severe in refrigerated transportation, in which temperature control is used to guarantee the quality of the products. Organizing logistics cooperatively can help decrease both the environmental and the economic impacts. In Joint Route Planning (JRP) cooperation, suppliers and customers jointly optimize routing decisions so that cost and emissions are minimized. Vendor Managed Inventory (VMI) cooperation extends JRP cooperation by optimizing routing and inventory planning decisions simultaneously. However, in addition to their economic advantages, VMI and JRP may also yield environmental benefits. To test this assertion, we perform a case study on cooperation between a number of supermarket chains in the Netherlands. The data of this case study are analyzed to quantify both the economic and environmental benefits of implementing cooperation via JRP and VMI, using vehicle routing and an inventory routing models. We found that JRP cooperation can substantially reduce cost and emissions compared with uncooperative routing. In addition, VMI cooperation can further reduce cost and emissions, but minimizing cost and minimizing emissions no longer result in the same solution and there is a trade-off to be made.     

An agent-based framework for cooperative planning of intermodal freight transport chains

The recent development of Intelligent Transportation Systems offers the possibility of cooperative planning of multi-actor systems in a distributed framework, by enabling prompt exchange of information among actors. This paper proposes a modeling framework for cooperation in intermodal freight transport chains as multi-actor systems. In this framework, the problem of optimizing freight transportation is decomposed into a suitable set of sub-problems, each representing the operations of an actor which are connected using a negotiation scheme. A Discrete Event model is developed which optimizes the system on a rolling horizon basis to account for the dynamics of intermodal freight transport operations. This framework allows for an event driven short/medium term planning of intermodal freight transport chains. The proposed methodology is evaluated using a realistic case study, and the results are compared against the First-Come-First-Served strategy, highlighting the significance of cooperation in systems operating close to capacity.