Simulation Analyses of Two On-Ramp Lane Arrangements

Ramps are vital pieces of infrastructure connecting city traffic networks to freeways. The performance of a ramp is to some extent determined by the on-ramp lane arrangement. In this paper, our primary aim is to evaluate the performance in terms of travel time and vehicle emissions for two on-ramp lane arrangements: added lane and zip merging. We estimate the travel time and CO2 emissions on the basis of the speed, and acceleration of vehicles in accordance with the improved comprehensive modal emission model (CMEM), and then analyse the impacts of traffic volume and heavy goods vehicles (HGVs) on travel time and emissions. The impacts of main road traffic flow on travel time and emissions for the two on-ramp lane arrangements are analysed under scenarios with traffic volumes of 800, 1\ua0000, 1\ua0200, 1\ua0400, 1\ua0600 and 1\ua0800 vehs/h/lane. Meanwhile, the relationships between travel time, emissions and various proportions of HGVs (2%, 4%, 6%, 8% and 10%) for both on-ramp lane arrangements are evaluated as well. We eventually present emission contour charts for the two on-ramp lane arrangements based on the possible combinations of traffic volumes and HGV percentages

Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube

The present Deliverable (D5.1) describes the identification and evaluation of infrastructure related risk factors. It outlines the results of Task 5.1 of WP5 of SafetyCube, which aimed to identify and evaluate infrastructure related risk factors and related road safety problems by (i) presenting a taxonomy of infrastructure related risks, (ii) identifying “hot topics” of concern for relevant stakeholders and (iii) evaluating the relative importance for road safety outcomes (crash risk, crash frequency and severity etc.) within the scientific literature for each identified risk factor. To help achieve this, Task 5.1 has initially exploited current knowledge (e.g. existing studies) and, where possible, existing accident data (macroscopic and in-depth) in order to identify and rank risk factors related to the road infrastructure. This information will help further on in WP5 to identify countermeasures for addressing these risk factors and finally to undertake an assessment of the effects of these countermeasures. In order to develop a comprehensive taxonomy of road infrastructure-related risks, an overview of infrastructure safety across Europe was undertaken to identify the main types of road infrastructure-related risks, using key resources and publications such as the European Road Safety Observatory (ERSO), The Handbook of Road Safety Measures (Elvik et al., 2009), the iRAP toolkit and the SWOV factsheets, to name a few. The taxonomy developed contained 59 specific risk factors within 16 general risk factors, all within 10 infrastructure elements. In addition to this, stakeholder consultations in the form of a series of workshops were undertaken to prioritise risk factors (‘hot topics’) based on the feedback from the stakeholders on which risk factors they considered to be the most important or most relevant in terms of road infrastructure safety. The stakeholders who attended the workshops had a wide range of backgrounds (e.g. government, industry, research, relevant consumer organisations etc.) and a wide range of interests and knowledge. The identified ‘hot topics’ were ranked in terms of importance (i.e. which would have the greatest effect on road safety). SafetyCube analysis will put the greatest emphasis on these topics (e.g. pedestrian/cyclist safety, crossings, visibility, removing obstacles). To evaluate the scientific literature, a methodology was developed in Work Package 3 of the SafetyCube project. WP5 has applied this methodology to road infrastructure risk factors. This uniformed approach facilitated systematic searching of the scientific literature and consistent evaluation of the evidence for each risk factor. The method included a literature search strategy, a ‘coding template’ to record key data and metadata from individual studies, and guidelines for summarising the findings (Martensen et al, 2016b). The main databases used in the WP5 literature search were Scopus and TRID, with some risk factors utilising additional database searches (e.g. Google Scholar, Science Direct). Studies using crash data were considered highest priority. Where a high number of studies were found, further selection criteria were applied to ensure the best quality studies were included in the analysis (e.g. key meta-analyses, recent studies, country origin, importance). Once the most relevant studies were identified for a risk factor, each study was coded within a template developed in WP3. Information coded for each study included road system element, basic study information, road user group information, study design, measures of exposure, measures of outcomes and types of effects. The information in the coded templates will be included in the relational database developed to serve as the main source (‘back end’) of the Decision Support System (DSS) being developed for SafetyCube. Each risk factor was assigned a secondary coding partner who would carry out the control procedure and would discuss with the primary coding partner any coding issues they had found. Once all studies were coded for a risk factor, a synopsis was created, synthesising the coded studies and outlining the main findings in the form of meta-analyses (where possible) or another type of comprehensive synthesis (e.g. vote-count analysis). Each synopsis consists of three sections: a 2 page summary (including abstract, overview of effects and analysis methods); a scientific overview (short literature synthesis, overview of studies, analysis methods and analysis of the effects) and finally supporting documents (e.g. details of literature search and comparison of available studies in detail, if relevant). To enrich the background information in the synopses, in-depth accident investigation data from a number of sources across Europe (i.e. GIDAS, CARE/CADaS) was sourced. Not all risk factors could be enhanced with this data, but where it was possible, the aim was to provide further information on the type of crash scenarios typically found in collisions where specific infrastructure-related risk factors are present. If present, this data was included in the synopsis for the specific risk factor. After undertaking the literature search and coding of the studies, it was found that for some risk factors, not enough detailed studies could be found to allow a synopsis to be written. Therefore, the revised number of specific risk factors that did have a synopsis written was 37, within 7 infrastructure elements. Nevertheless, the coded studies on the remaining risk factors will be included in the database to be accessible by the interested DSS users. At the start of each synopsis, the risk factor is assigned a colour code, which indicates how important this risk factor is in terms of the amount of evidence demonstrating its impact on road safety in terms of increasing crash risk or severity. The code can either be Red (very clear increased risk), Yellow (probably risky), Grey (unclear results) or Green (probably not risky). In total, eight risk factors were given a Red code (e.g. traffic volume, traffic composition, road surface deficiencies, shoulder deficiencies, workzone length, low curve radius), twenty were given a Yellow code (e.g. secondary crashes, risks associated with road type, narrow lane or median, roadside deficiencies, type of junction, design and visibility at junctions) seven were given a Grey code (e.g. congestion, frost and snow, densely spaced junctions etc.). The specific risk factors given the red code were found to be distributed across a range of infrastructure elements, demonstrating that the greatest risk is spread across several aspects of infrastructure design and traffic control. However, four ‘hot topics’ were rated as being risky, which were ‘small work-zone length’, ‘low curve radius’, ‘absence of shoulder’ and ‘narrow shoulder’. Some limitations were identified. Firstly, because of the method used to attribute colour code, it is in theory possible for a risk factor with a Yellow colour code to have a greater overall magnitude of impact on road safety than a risk factor coded Red. This would occur if studies reported a large impact of a risk factor but without sufficient consistency to allocate a red colour code. Road safety benefits should be expected from implementing measures to mitigate Yellow as well as Red coded infrastructure risks. Secondly, findings may have been limited by both the implemented literature search strategy and the quality of the studies identified, but this was to ensure the studies included were of sufficiently high quality to inform understanding of the risk factor. Finally, due to difficulties of finding relevant studies, it was not possible to evaluate the effects on road safety of all topics listed in the taxonomy. The next task of WP5 is to begin identifying measures that will counter the identified risk factors. Priority will be placed on investigating measures aimed to mitigate the risk factors identified as Red. The priority of risk factors in the Yellow category will depend on why they were assigned to this category and whether or not they are a hot topic

Speed, speed variation and crash relationships for urban arterials

Speed and speed variation are closely associated with traffic safety. There is, however, a dearth of research on this subject for the case of urban arterials in general, and in the context of developing nations. In downtown Shanghai, the traffic conditions in each direction are very different by time of day, and speed characteristics during peak hours are also greatly different from those during off-peak hours. Considering that traffic demand changes with time and in different directions, arterials in this study were divided into one-way segments by the direction of flow, and time of day was differentiated and controlled for. In terms of data collection, traditional fixed-based methods have been widely used in previous studies, but they fail to capture the spatio-temporal distributions of speed along a road. A new approach is introduced to estimate speed variation by integrating spatio-temporal speed fluctuation of a single vehicle with speed differences between vehicles using taxi-based high frequency GPS data. With this approach, this paper aims to comprehensively establish a relationship between mean speed, speed variation and traffic crashes for the purpose of formulating effective speed management measures, specifically using an urban dataset. From a total of 234 one-way road segments from eight arterials in Shanghai, mean speed, speed variation, geometric design features, traffic volume, and crash data were collected. Because the safety effects of mean speed and speed variation may vary at different segment lengths, arterials with similar signal spacing density were grouped together. To account for potential correlations among these segments, a hierarchical Poisson log-normal model with random effects was developed. Results show that a 1% increase in mean speed on urban arterials was associated with a 0.7% increase in total crashes, and larger speed variation was also associated with increased crash frequency

Streets of clay : design and assessment of sustainable urban and suburban streets

Since automobile use became widespread in North America, Europe, and Australia during the first two decades of the 20th century, cities and their streets have been reshaped to adapt to the motor vehicle surge. Efforts are now underway to re-define the purpose of arterial streets and to re-design these important thoroughfares accordingly. This movement has taken a variety of names, including “Livable Streets”, “Context Sensitive Streets” and “Complete Streets”. Such streets are multimodal transport links as well as places for socio-economic life and active living.This thesis presents findings from research on assessing just how “active” and “sustainable” are a set of arterial streets in five San Francisco Bay Area cities. Six streets, two re-designed as more “livable” or more “context sensitive” streets, and four more conventional arterial streets, are compared across a set of objective performance metrics and subjective assessments from street users and businesses. The analysis was grounded in a mixed methods approach. Streets were evaluated on an array of quantitative measures, as well as the results of six street user focus groups and surveys of 716 street users and local businesses.An important outcome of the research is a framework or model for influences on and supports for street activity and sustainability. Thesis findings affirm the importance to communities of multi-purpose street environments. Thesis results show that arterial streets can be redesigned to engender activity and promote sustainability. This research confirmed the importance of providing space on arterial streets for pedestrians, cyclists, and transit users. This thesis represents a significant extension of the knowledge in the field of what constitutes a more sustainable arterial street environment. The assessment framework integrates a far wider range of research disciplines and concerns than previously evidenced in the literature. As such it may provide policymakers with a better understanding and basis on which to pursue further arterial street re-designs in similar contexts to those of the six streets I studied in this research

Identification of safety effects of infrastructure related measures, Deliverable 5.2 of the H2020 project SafetyCube

Identification of safety effects of infrastructure related measures, Deliverable 5.2 of the H2020 project SafetyCub

Operational and Safety Analysis with Mitigation Strategies for Freeway Truck Traffic in Wyoming [MPC 19\u2013396]

MPC-519The State of Wyoming road network is characterized by heavy truck traffic. In 2015, truck traffic was approximately 22% of vehicle miles traveled (VMTs) along all routes in Wyoming, according to the WYDOT Annual Traffic Report. The heaviest truck traffic exists along I-80 with about 47% truck VMTs. Trucks have significantly different physical and driving characteristics than passenger cars, especially on grades, which has impacts on operational efficiency, safety, and pavement deterioration. The presence of heavy vehicles reduces the capacity of freeway segments, with the reduction being more significant along specific grades. This study focuses on the benefits of climbing lanes on operations and safety of freeway truck traffic. Various methodologies were used in this assessment. The results show that the addition of climbing lanes reduces delays and increases overall traffic speeds on upgrades, and can reduce the total and truck-related crashes from 6% to 34%, and from 1% to 16%, respectively, depending on the analyzed location and applied methodology

Toward a Safer Transportation System for Senior Road Users

Senior pedestrians and drivers (65 years and older) are among the most vulnerable road users. As the population of seniors rise, concerns regarding older adults\u27 traffic safety are growing. The advantages of using autonomous vehicles, innovative vehicle technologies, and active transportation are becoming more widely recognized to improve seniors\u27 mobility and safety. This behooves researchers to further investigate senior road users’ safety challenges and countermeasures. This study contributes to the literature by achieving two main goals. First, to explore contributing factors affecting the safety of older pedestrians and drivers in the current transportation system. Second, to examine seniors’ perceptions, preferences, and behaviors toward autonomous vehicles and advanced vehicle technologies, the main components of future transportation systems. To achieve the first objective, crash data involving senior pedestrians and drivers were collected and analyzed. Using structural equation modeling, it was found out that seniors’ susceptibility to pedestrian incidents is a function of level of walking difficulty, fear of falling, and crossing evaluation capability. Senior drivers’ risk factors were found to be driving maneuver & crash location, road features & traffic control devices, driver condition & behavior, road geometric characteristics, crash time and lighting, road class latent factors, as well as pandemic variable. To achieve the second objective, a national survey and a driving simulator experiment were conducted among seniors. The national survey investigates seniors’ perceptions and attitudes to a wide range of AVs features from the perspective of pedestrians and users. Using principal component analysis and cluster analysis, three distinctive clusters of seniors were identified with different perceptions and attitude toward different AV options. The driving simulator experiment examined drivers’ behavior and preferences towards vehicle to infrastructure warning messages. Using the analysis of covariance technique, the results revealed that audio warning message was more effective compared to other scenarios. This finding is consistent with the results of stated preferences of the participants. Female and senior drivers had higher speed limit compliance rate. The findings of this study shed light on key aspects of the current and future of transportation systems that are needed to improve the safety of senior road users

14-07 Development of Decision Support Tools to Assess Pedestrian and Bicycle Safety: Focus on Population, Demographic and Socioeconomic Spectra

Despite the increase of these non-motorized trips, bicyclists and pedestrians remain vulnerable road users that are often over represented in traffic crashes. While the currently used methods that identify hazardous locations serve their purpose well, majority represent a reactive approach that seeks improvement after crashes happen. This research addressed these issues and proposed decision support tools to aid the implementation of bicycle and pedestrian safety strategies. This work developed an access based tool to predict the expected number of crashes at different neighborhood levels. This tool combines the traditional methods such as those provided in the Highway Safety manual to predict the expected number of bicycle and pedestrian crashes. First, a cluster analysis technique is proposed and developed a Geographic Information Systems (GIS) technique to facilitate the identification of high crash locations. Safety Performance Functions (SPFs) are developed in form of mathematical equations to relate the number of crashes to area socioeconomic and demographic characteristics. An integrated system consisting of access database and safety performance functions, and whose interface is designed to automatically compute the number of crashes given the input values is developed. Basing on crash value, the tool can be adopted as a framework to guide the appropriate allocation of safety improvement resources