Motorway crash duration and its determinants: do durations vary across motorways?

Traffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways. Identifying the critical determinants of travel delays has been of significant importance to the incident management systems, which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard‐based models to develop in‐depth insights into how the crash‐specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland, and the differential effects of determinants on crash survival functions have been studied on these two motorways individually. A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, has been compared with random parameter AFT structures in terms of goodness of fit to the duration data, and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway 1 exhibits durations that are on average 19% shorter compared with the durations on motorway 2. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.     

Economic impact of non-motorized transportation in Indian cities

Lack of a clear understanding regarding the economic impacts of non-motorized modes is a major reason why they are excluded from the transportation development agenda of cities in India. Keeping this aspect in mind the present study has been divided in to two parts. The first part tries to understand the non-motorized traffic evolution in India. It focuses on the declination of non-motorized modes, necessity to revamp it, the favorable conditions to promote them in India and the relative problems associated with it. It is found here that there is a necessity for defining the role of non-motorized modes in India for the viable implementation of infrastructure and policies related with it.     

尼泊尔喜马拉雅地区塔玛科什3级水电工程——穿越软弱构造片岩修建隧洞所面临的挑战

由于尼泊尔喜马拉雅地区岩石强度较低,水平应力较高,因此在该软弱构造片岩带中开挖隧洞具有较大的挑战性.文章主要阐述装机容量为650 kW的塔玛科什3级水电工程17km长大跨度隧洞和大型地下发电厂房(这两项工程计划穿越夹杂有软弱构造片岩带的坚硬眼球状片麻岩区域)所面临的重大技术挑战.穿过片岩带开挖的隧洞长度约占总长的15％,由于此岩层带岩石强度较低,具有剪切特性和渗流现象,且水平应力较高,围岩挤压和隧洞塌方都是可预期的问题,因此该工程地下开挖主要关注的问题是大尺寸隧洞的可施工性和工期.为了解决可预期问题,进行了更进一步的研究,主要集中在隧洞最大可建尺寸、方位、减少围岩挤压的开挖方法,以及地下发电厂房稳定性和合理岩石支护设计上.研究发现,在构造片岩带中可施工的全断面隧洞最大尺寸可达9m,为改进的马蹄形(有弧形仰拱).通过对隧洞三种不同方位方案(即正交、斜交、平行)的分析发现,与叶理面正交的方案最佳,可减少围岩挤压近50％.     

Pick‐up locations and bus allocation for transit‐based evacuation planning with demand uncertainty

This paper develops a decision‐support model for transit‐based evacuation planning under demand uncertainty. Demand uncertainty refers to the uncertainty associated with the number of transit‐dependent evacuees. A robust optimization model is proposed to determine the optimal pick‐up points for evacuees to assemble, and allocate available buses to transport the assembled evacuees between the pick‐up locations and different public shelters. The model is formulated as a mixed‐integer linear program and is solved via a cutting plane scheme. The numerical example based on the Sioux Falls network demonstrates that the robust plan yields lower total evacuation time and is reliable in serving the realized evacuee demand. Copyright © 2012 John Wiley & Sons, Ltd.     

Sustainable urbanization using high speed rail (HSR) in Karnataka,India

Considering the present trends of urbanization and motorization in India, there is an urgent need for integration, revitalization and renewal of the smaller towns and cities to make urban areas in India more sustainable. Unless our regional space is reorganized to upgrade development of towns and cities and integrate them with each other and the larger cities, the urbanization process in India will become unsustainable. It is argued that High Speed Rail (HSR) can play a role in achieving this more balanced and sustainable development of towns and cities, opening up opportunities for growth across a wider, inter-connected, region, with the benefit of taking the pressure of the larger cities to absorb additional burgeoning populations. This paper will make the case that in the current Indian context, current patterns of mega-city growth are unsustainable, and that HSR can play an important role in providing opportunities for medium and smaller size cities through their interconnections. It begins by highlighting the role that railways have played in India and other countries, noting that merely economic analysis of their costs and benefits generally underestimated their contributions to development. It then provides an introduction to HSR and its potential impact in general, before applying this to the example of the State of Karnataka in South India.     

A hybrid scheme for real‐time prediction of bus trajectories

The uncertainty associated with public transport services can be partially counteracted by developing real‐time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical data. The contribution of each predictor as well as values of respective parameters is estimated by minimizing the prediction error using a linear regression heuristic. The hybrid method was applied to five bus routes in Stockholm, Sweden, and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different route layouts, passenger demands and operation practices. Model validation confirms model transferability and real‐time applicability. Generating more accurate predictions can help service users adjust their travel plans and service providers to deploy proactive management and control strategies to mitigate the negative effects of service disturbances. Copyright © 2017 John Wiley & Sons, Ltd.     

Empirical modelling of the relationship between bus and car speeds on signalised urban networks

Vehicle speed is an important attribute for analysing the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and transit signal priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus, in-service bus during peak periods and in-service bus during off-peak periods with average car speed are proposed. The models are cross-validated and the interrelationships are significant.     

Activity based travel demand models as a tool for evaluating sustainable transportation policies

India is in the course of an economic transition. The economic growth nurtured the life in the cities and cities have become a major livelihood destination for everyone. This migration of people contributed to the increased urbanization of Indian cities. The booming economy fostered the well-being and shaped the lifestyle of people in such a way that the dependency on private vehicle has become an unavoidable affair. Along with population growth, the increased vehicle ownership gave rise to overall spurt in travel demand. But the supply side lagged behind the demand adding to many of the transport related externalities such as accidents, congestion, pollution, inequity etc. The importance of sustainability is understood in the current urban transport scenario leading to the development and promotion of sustainable transport polices. The core agenda of these polices is to target the travel behavior of people and change the way they travel by creating a different travel environment. However, the impacts of many such policies are either unknown or complex. Hence, before adopting and implementing such policies, it is important for the decision makers to be aware of the impacts of them. The role of travel demand models comes here as they predict the future travel demand under different policy scenarios. This paper reviews the ability of travel demand models applied in India in analyzing the sustainable transport policies. The study found that the conventional model system in India, which is trip based four step aggregate methodology, is inadequate in analyzing the sustainable transport policies. A review of alternative approach, known as activity based travel demand modeling found that they are capable of handling such policies better than conventional models and are assistive to the decision makers in arriving at right mix of polices specific to the situations. Since there is no operational activity based travel demand model system developed in India, the study at the end envisaged a conceptual framework of an integrated activity based travel demand model based on the requirements identified from the review. This can potentially replace the existing travel demand models and can be used for planning applications once the modification & validation have been done according to the existing activity-travel behavior of individuals.     

Transfer demand prediction for timed transfer coordination in public transport operational control

Timed transfer coordination in public transit reduces passenger transfer time by providing seamless interconnected transfers. The problem arises when a Receiving Vehicle (RV) arrives to the transfer stop before a Feeding Vehicle (FV) carrying transferring passengers. Timed transfer coordination in operational control dynamically decides whether a RV is held at the transfer stop to allow transfers, or departs as scheduled. While transfer demand is essential for implementing timed transfer coordination, this variable is generally not available in public transit because of the lack of passenger transfer plans. The problem of acquiring this variable in real‐time has also received limited attention in the related literature. This paper proposes a new method to dynamically predict the transfer demand. We anticipate the transferring probability from each individual passenger by examining historical travel itineraries. Three different types of models (simple analytical, statistical, and computation intelligence model) are developed to forecast the number of transferring passengers. Numerical experiments using observed Automatic Vehicle Location and Automatic Fare Collection data from South East Queensland, Australia show the accuracy and applicability of the proposed models in timed transfer coordination. Copyright © 2017 John Wiley & Sons, Ltd.