Search results

The phenomenon of traffic crash under-reporting has been extensively documented in terms of its extent, but not equally analysed in terms of its reasons. As police distrust has been recently identified as a major reason for crash under-reporting, the purpose of this paper is to look at the police service quality for handling the reporting of traffic crashes.

This study introduces a novel approach to evaluate service quality that combines multi-criteria decision analysis (MCDA) with latent class analysis (LCA). Moreover, this study presents the design of a web-based survey on the basis of the SERVQUAL approach to detecting strengths, opportunities and threats with crash reporting to the police at a strategic level. Transportation stakeholders (e.g. researchers, authorities, consultants, NGO representatives, suppliers) with an interest in traffic safety in Denmark participated in the survey that yielded 86 complete responses.

The novel approach was successfully applied and its implementation demonstrated the usefulness of the tool even in countries with a high police service. Results showed that the participating stakeholders perceived human factors as more important than physical factors in order to increase the crash reporting, with responsiveness as the most important and tangibles as the least important dimensions. Nevertheless, most stakeholders viewed a mixture of human and physical factors as crucial to increase crash reporting rates.

This study advances the knowledge about police service quality with a novel expert-based decision support tool based on SERVQUAL, MCDA and LCA, demonstrates its applicability in countries with a high-police service, and opportunities and barriers for increasing the crash reporting rate.

This research applies data mining techniques to discover the relationship between driver inattention and motor vehicle accidents.

The data used in this research is obtained from the Fatality Analysis Reporting System of the National Highway Traffic Safety Administration, focused on the Maryland and Washington, DC area from years 2000 to 2003. The data are first clustered using the Kohonen networks. Then, the patterns and rules of the data are explored by decision tree and neural network models.

Results suggests that when inattention and physical/mental conditions take place at the same time, the driver has a higher tendency of being involved in a crash that collides into static objects. Furthermore, with regards to the manner of collision, the relative importance of colliding into a moving vehicle as the first harmful event is two times higher relative to that of colliding into a fixed object as the first harmful event in a crash.

The data used in this research are limited to fatal crashes that happened in Maryland and Washington, DC from years 2000 to 2003.

This is one of the first research papers utilizing data mining techniques to explore the possible relationships between driver inattention and motor vehicle crashes.

Driving for work has been identified as potentially one of the riskiest activities performed by workers within the course of their working day. Jurisdictions around the world have passed legislation and adopted policy and procedures to improve the safety of workers. However, particularly within the work driving setting, complying with legislation and the minimum safety standards and procedures is not sufficient to improve work driving safety. This chapter outlines the manner in which safety citizenship behavior can offer further improvement to work-related driving safety by acting as a complementary paradigm to improve risk management and current models and applications of safety culture.

Research on concepts associated with risk management and theoretical frameworks associated with safety culture and safety citizenship behavior are reviewed, along with their practical application within the work driving safety setting. A model incorporating safety citizenship behavior as a complementary paradigm to safety culture is proposed. It is suggested that this model provides a theoretical framework to inform future research directions aimed at improving safety within the work driving setting.

Police recruit training has come under scrutiny recently by both practitioners and academics who question the quality of education recruits receive prior to beginning their jobs. Past researchers have questioned whether the training adequately prepares recruits to be effective police officers. This study analyses the content of one police academy to determine if the training is sufficient. This was done by actually attending an academy training program as a recruit to determine what occurs within the academy setting. By comparing the content of this academy to the required elements identified in academic and practitioner’s literature, it was determined that this police academy is providing quality training to potential officers within time and budgetary constraints.

The purpose of this paper is to quantify and evaluate transport sustainability from an integrated perspective. It is argued that transportation systems being interdisciplinary and complex, the integrated approach towards quantification and evaluation would present its sustainability goals’ attainment in a much better way.

The proposed integrated methodology is divided into five major steps that are sub-divided. It adopts a three-tier classification system i.e. pillar, sub-division and indicator. In total, 116 sustainable transportation indicators (STIs) were classified into 10 subdivisions corresponding to three sustainability pillars. The weighting and aggregation of STIs were done using a combination of a statistical tool called principal component analysis/factor analysis, a machine learning tool called fuzzy logic and equal weighting method. The final output that the proposed integrated methodology generates is a new composite index called the integrated sustainable transportation index (IIST).

To check the credibility of the proposed integrated methodology, it was applied to 26 states and the National Capital Territory (NCT) of Delhi, India. Based on the computed IIST, 27 study zones were ranked and mapped. The results showed that while Tamil Nadu (0.643), Telangana (0.574) and Maharashtra (0.564) were the best-performing states, Goa (0.347), Chhattisgarh (0.436) and Meghalaya (0.439) were the worst-performing states, as far as the relative transportation sustainability is concerned.

The proposed integrated methodology could be useful for transportation evaluators, planners and policymakers who can recognize, track and improve the strengths and overcome the weaknesses within a transportation system.

The novelty of this research work is that it uses a multi-stage multi-tool approach to quantify and evaluate transport sustainability that minimizes the demerits of single-stage individual tools while maximizing their merits.

Public opinion regarding the police is generally positive, although there are number of individual and contextual variables that affect these views. Yet research examining public perceptions regarding state law enforcement agencies (particularly state patrols) is rare.

The paper utilizes a representative state‐wide sample of state residents and examine their perceptions of the Colorado State Patrol (CSP).

The paper finds positive views of the CSP overall and place particular emphasis on how individual, contextual, and contact‐related variables affect opinions.

The study focusses on one state patrol and is not generalizable to all state patrols and to other forms of state law enforcement.

The paper fills a void in the research on public opinion regarding state law enforcement and discuss similarities and differences in how they are viewed when compared to municipal agencies.