Traffic density estimation of signalised arterials with stop line detector and probe data

This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

Traffic safety culture : what can we learn from Australia?

-- The role of traffic safety culture in Australia -- A comparison of drink driving (a success story) and speeding (a work in progress) ―Countermeasure approaches ―Community attitudes, perceptions and behaviors -- Lessons from Australia for the further development of the traffic safety culture concept

Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

The Arab Spring and social media audiences : English and Arabic Twitter users and their networks

Although popular media narratives about the role of social media in driving the events of the 2011 “Arab Spring” are likely to overstate the impact of Facebook and Twitter on these uprisings, it is nonetheless true that protests and unrest in countries from Tunisia to Syria generated a substantial amount of social media activity. On Twitter alone, several millions of tweets containing the hashtags #libya or #egypt were generated during 2011, both by directly affected citizens of these countries and by onlookers from further afield. What remains unclear, though, is the extent to which there was any direct interaction between these two groups (especially considering potential language barriers between them). Building on hashtag data sets gathered between January and November 2011, this article compares patterns of Twitter usage during the popular revolution in Egypt and the civil war in Libya. Using custom-made tools for processing “big data,” we examine the volume of tweets sent by English-, Arabic-, and mixed-language Twitter users over time and examine the networks of interaction (variously through @replying, retweeting, or both) between these groups as they developed and shifted over the course of these uprisings. Examining @reply and retweet traffic, we identify general patterns of information flow between the English- and Arabic-speaking sides of the Twittersphere and highlight the roles played by users bridging both language spheres.

Speech interference on residential balconies with road traffic noise

Residential balcony design influences speech interference levels caused by road traffic noise and a simplified design methodology is needed for optimising balcony acoustic treatments. This research comprehensively assesses speech interference levels and benefits of nine different balcony designs situated in urban street canyons through the use of a combined direct, specular reflection and diffuse reflection path theoretical model. This thesis outlines the theory, analysis and results that lead up to the presentation of a practical design guide which can be used to predict the acoustic effects of balcony geometry and acoustic treatments in streets with variable geometry and acoustic characteristics.

Characteristics of police-reported road traffic crashes in Ethiopia over a six year period

Ethiopia has one of Africa’s fastest growing non-oil producing economies and an increasing level of motorisation (AfDB, OECD, UNDP, & UNECA, 2012). This rapidly increasing mobility has created some unique road safety concerns; however there is scant published information and related commentary (United Nations Economic Commission for Africa, 2009). The objective of this paper is to quantify police-reported traffic crashes in Ethiopia and characterise the existing state of road safety. Six years (July 2005 - June 2011) of police-reported crash data were analysed, consisting of 12,140 fatal and 29,454 injury crashes on the country’s road network. The 12,140 fatal crashes involved 1,070 drivers, 5,702 passengers, and 7,770 pedestrians, totalling 14,542 fatalities, an average of 1.2 road user fatalities per crash. An important and glaring trend that emerges is that more than half of the fatalities in Ethiopia involve pedestrians. The majority of the crashes occur during daytime hours, involve males, and involve persons in the 18-50 age group—Ethiopia’s active workforce. Crashes frequently occur in mid blocks or roadways. The predominant collision between motor vehicles and pedestrians was a rollover on a road tangent section. Failing to observe the priority of pedestrians and speeding were the major causes of crashes attributed by police. Trucks and minibus taxis were involved in the majority of crashes, while automobiles (small vehicles) were less involved in crashes relative to other vehicle types, partially because small vehicles tend to be driven fewer kilometres per annum. These data illustrate and justify a high priority to identify and implement effective programs, policies, and countermeasures focused on reducing pedestrian crashes.

Traffic density estimation of signalised arterials with stop line detector and probe data

This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

Random breath testing in Queensland and Western Australia : Examination of how the random breath testing rate influences alcohol related traffic crash rates

In this paper we explore the relationship between monthly random breath testing (RBT) rates (per 1000 licensed drivers) and alcohol-related traffic crash (ARTC) rates over time, across two Australian states: Queensland and Western Australia. We analyse the RBT, ARTC and licensed driver rates across 12 years; however, due to administrative restrictions, we model ARTC rates against RBT rates for the period July 2004 to June 2009. The Queensland data reveals that the monthly ARTC rate is almost flat over the five year period. Based on the results of the analysis, an average of 5.5 ARTCs per 100,000 licensed drivers are observed across the study period. For the same period, the monthly rate of RBTs per 1000 licensed drivers is observed to be decreasing across the study with the results of the analysis revealing no significant variations in the data. The comparison between Western Australia and Queensland shows that Queensland's ARTC monthly percent change (MPC) is 0.014 compared to the MPC of 0.47 for Western Australia. While Queensland maintains a relatively flat ARTC rate, the ARTC rate in Western Australia is increasing. Our analysis reveals an inverse relationship between ARTC RBT rates, that for every 10% increase in the percentage of RBTs to licensed driver there is a 0.15 decrease in the rate of ARTCs per 100,000 licenced drivers. Moreover, in Western Australia, if the 2011 ratio of 1:2 (RBTs to annual number of licensed drivers) were to double to a ratio of 1:1, we estimate the number of monthly ARTCs would reduce by approximately 15. Based on these findings we believe that as the number of RBTs conducted increases the number of drivers willing to risk being detected for drinking driving decreases, because the perceived risk of being detected is considered greater. This is turn results in the number of ARTCs diminishing. The results of this study provide an important evidence base for policy decisions for RBT operations.

Alcohol-related driving offences, crashes, and traffic policing strategies in Zhejiang Province, China

Context Alcohol-related traffic offences and associated trauma have attracted attention in China in recent years, culminating in changes to national legislation in May 2011. Harsher penalties were introduced, particularly for offences where blood alcohol concentration (BAC) levels above 80mg/100mL are recorded. Deemed to be drunk under the law, this is now a criminal offence attracting penalties including large monetary fines, licence suspension for 5 years and imprisonment. Objective This paper outlines key statistics about alcohol-related road trauma in Zhejiang Province and strategies used to combat drink- and drunk-driving. Key Outcomes Zhejiang Province, in China’s south east, has a population of approximately 54, 426,000; 22.36% hold a driving licence. Rapid motorisation is occurring there. In 2011, 1,383,318 new licences were issued, representing a 16.78% increase from the previous year. In 2012, there were a total of 65,000 police officers throughout the Province, 12,307 of whom (18.9%) were traffic police. Responsibility for conducting alcohol testing is the responsibility of all traffic police. The number of alcohol breath tests conducted per year was not available. However, traffic police are actively enforcing alcohol-related laws. In 2011, 89,228 drivers were charged with drink-driving (DUI;20-80mg/100 mL) and 10,014 with the more serious drunk-driving offence (DWI;>80mg/100mL) (Zhejiang Traffic Management Department, 2012). These numbers decreased from the previous year (221,262 and 26,390 respectively). For all crashes recorded in 2011 (n=20,176), 2% involved alcohol-impaired road users. Information on the role of alcohol in crashes from previous years was not available. Discussion Various strategies are employed to detect alcohol-impaired drivers including: targeting vehicles from hotels/restaurants; using sense of smell to screen drivers for further testing; passive alcohol sensors to test drivers; and blood tests for crash-involved drivers where a fatality occurred. Although resources to promote road safety are limited, various government initiatives promote awareness of the dangers of alcohol-related driving and more are needed in future.

Promoting a more positive traffic safety culture in Australia : lessons learnt and future directions

Adopting a traffic safety culture approach, this paper identifies and discusses the ongoing challenge of promoting the road safety message in Australia. It is widely acknowledged that mass media and public education initiatives have played a critical role in the significant positive changes witnessed in community attitudes to road safety in the last three to four decades. It could be argued that mass media and education have had a direct influence on behaviours and attitudes, as well as an indirect influence through signposting and awareness raising functions in conjunction with enforcement. Great achievements have been made in reducing fatalities on Australia’s roads; a concept which is well understood among the international road safety fraternity. How well these achievements are appreciated by the general Australian community however, is not clear. This paper explores the lessons that can be learnt from successes in attitudinal and behaviour change in regard to seatbelt use and drink driving in Australia. It also identifies and discusses key challenges associated with achieving further positive changes in community attitudes and behaviours, particularly in relation to behaviours that may not be perceived by the community as dangerous, such as speeding and mobile phone use while driving. Potential strategies for future mass media and public education campaigns to target these challenges are suggested, including ways of harnessing the power of contemporary traffic law enforcement techniques, such as point-to-point speed enforcement and in-vehicle technologies, to help spread the road safety message.

Traffic safety risks trends and patterns analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

Visibility-related characteristics of crashes involving bicyclists and motor vehicles – Responses from an online questionnaire study

Bicyclists are among the most vulnerable of road users, with high fatal crash rates. Although visibility aids have been widely advocated to help prevent bicycle-vehicle conflicts, to date no study has investigated, among crash-involved cyclists, the kind of visibility aids they were using at the time of the crash. This study undertook a detailed investigation of visibility factors involved in bicyclist-motor-vehicle crashes. We surveyed 184 bicyclists (predominantly from Australia via internet cycling forums) who had been involved in motor vehicle collisions regarding the perceived cause of the collision, ambient weather and general visibility, as well as the clothing and bicycle lights used by the bicyclist. Over a third of the crashes occurred in low light levels (dawn, dusk or night-time), which is disproportionate given that only a small proportion of bicyclists typically ride at these times. Importantly, 19% of these bicyclists reported not using bicycle lights at the time of the crash, and only 34% were wearing reflective clothing. Only two participants (of 184) nominated bicyclist visibility as the cause of the crash: 61% attributed the crash to driver inattention. These findings demonstrate that crash-involved bicyclists tend to under-rate and under-utilise visibility aids as a means of improving their safety.

On the periodicity of traffic oscillations and capacity drop : the role of driver characteristics

This paper shows that traffic hysteresis, a manifestation of driver characteristics, has a profound impact on the development of traffic oscillations and the bottleneck discharge rate. Findings suggest that aggressive driver behavior (with small response times and jammed spacing) leads to spontaneous formations of stop-and-go disturbances. Furthermore, the aggressive behavior, coupled with a late response to adopt less aggressive behavior, generates large hysteresis that leads to oscillations’ transformation from localized to substantial disturbances and growth. The larger the magnitude of hysteresis is, the larger the growth is. Our finding also suggests that the bottleneck discharge rate can diminish by 8-23% when driver adopts a less aggressive reaction to a disturbance (characterized by a larger response time). This finding is particularly notable since lane-changes have been believed to be the major cause of a reduction in bottleneck discharge rate.

Public acceptance towards congestion charge : a case study of Brisbane

This paper investigates public acceptance towards congestion charge in Australia by taking Brisbane as a case study. Public acceptance to congestion charge has often been investigated in the literature. However, few were in the context of an Australian city. This paper fills the gap. A face-to-face survey was conducted to solicit public opinions on the congestion charge, should a congestion charge scheme be implemented in the Brisbane City area. The survey data were analysed to pinpoint important factors relevant to people’s attitudes towards congestion charge and to measure their relationships. Main findings from our analysis are: (1) the residents’ attitudes towards congestion charge differ by genders and by user groups of transport modes; (2) for each of the three groups (i.e., the auto users, the transit riders, and the whole participants), a positive and stable correlation was found between a participant’s attitude towards congestion charge and the effectiveness of congestion charge on reducing traffic congestion. A negative and stable correlation was also found for all three groups between a participant’s attitude towards congestion charge and congestion charge’s negative impact on the attractiveness of working in the city; (3) the auto users tended to be more sceptical about the service capacity of existing transit systems in coping with extra passengers induced by the implementation of congestion charge; and (4) for people with high income, introducing the congestion charge may have no impact on their travelling to the city.