Updating predictive accident models of modern rural single carriageway A-roads

Abstract

Reliable predictive accident models (PAMs) are essential to design and maintain safe road networks, and yet the models most commonly used in the UK were derived using data collected 20 to 30 years ago. Given that the national personal injury accident total fell by some 30% in the last 25 years, while road traffic increased by over 60%, significant errors in scheme appraisal and evaluation based on the models currently in use seem inevitable. In this paper, the temporal transferability of PAMs for modern rural single carriageway A-roads is investigated, and their predictive performance is evaluated against a recent data set. Despite the age of these models, the PAMs for predicting the total accidents provide a remarkably good fit to recent data and these are more accurate than models where accidents are disaggregated by type. The performance of the models can be improved by calibrating them against recent data.     

Techniques for the inference of mileage rates from MOT data

Abstract

Mathematical and computational techniques are developed for the processing and analysis of annual Ministry of Transport roadworthiness (MOT) test data that the UK Department for Transport has placed in the public domain. First, techniques are given that clean erroneous records and a linking procedure is provided that permits the inference of an individual vehicle's mileage between consecutive tests. Methods are then developed that analyse aggregate mileage totals, as a function of vehicle age, class and geography. The inference of aggregate mileage rates as a function of time is then considered.     

Estimation of a route choice model for urban public transport using smart card data

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in ?ilina, the Slovak Republic, as a case study     

Quantifying the transport-related impacts of parental school choice in England

School travel is becoming increasingly car-based and this is leading to many environmental and health implications for children all over the world. One of several reasons for this is that journey to school distances have increased over time. This is a trend that has been reinforced in some countries by the adoption of so-called ‘school choice’ policies, whereby parents can apply on behalf of their child(ren) to attend any school, and not only the school they live closest to. This paper examines the traffic and environmental impacts of the school choice policy in England. It achieves this by analysing School Census data from 2009 from the Department for Education. Multinomial logit modelling and mixed multinomial logit modelling are used to illustrate the current travel behaviour of English children in their journey to school and examine how there can be a significant reduction in vehicle miles travelled, CO₂ emissions and fuel consumption if the ‘school choice’ policy is removed. The model shows that when school choice was replaced by a policy where each child only travelled to their ‘nearest school’ several changes occurred in English school travel. Vehicle Miles Travelled (VMT) by motorised transport fell by 1 % for car travel and 10 % for bus travel per day. The reduction in vehicle miles travelled could lead to less congestion on the roads during the morning rush hour and less cars driving near school gates. Mode choice changed in the modelled scenario. Car use fell from 32 to 22 %. Bus use fell from 12 to 7 %, whilst NMT saw a rise of 17 %. With more children travelling to school by walking or cycling the current epidemic of childhood obesity could also be reduced through active travel.     

Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature

Abstract

Rapid technological developments in the field of personal communication services probe visions of a next generation in Advanced Traveller Information Services (ATIS). These technological developments provoke a renewed interest in the use and effect of such next‐generation ATIS among academia as well as practitioners. To understand better the potential use and effects of such next‐generation ATIS, a thorough review is warranted of contemporary conceptual ideas and empirical findings on the use of travel information (services) and their effects on travellers’ choices. This paper presents such a review and integrates behavioural determinants such as the role of decision strategies with manifest determinants such as trip contexts and socio‐economic variables into a coherent framework of information acquisition and its effect on travellers’ perceptions.     

Seventy Minutes Plus or Minus 10 — A Review of Travel Time Budget Studies

Abstract

This paper provides a comprehensive review of travel-time budget (TTB) studies in the literature for about the past four decades. Starting with the concept of TTBs, it discusses both the studies that support the existence of TTB and also those that deem the concept to be unfounded. Sociodemographic variables and their relation to TTB are also discussed briefly. However, as past studies use different data sources, survey techniques, and methodology for analysis, cross comparison of studies is not possible. Most importantly, the underlying cause of the regularity that is found at an aggregate level is still not known. The idea of TTB is important because, if it exists, it would mean that the total time spent on travelling per person per day will remain unchanged in spite of all improvements to transport. TTB has immense implications for transport policies and it is usually ignored. The paper also explores the available theoretical explanation of this concept, past research gaps and new analysis potentials. Recent directions in TTB studies are also discussed together with the potential use of multiday multiyear panel data in TTB research to explore the phenomenon better than before.     

Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review

Accurate measurement of travel behaviour is vital for transport planning, modelling, public health epidemiology, and assessing the impact of travel interventions. Self-reported diaries and questionnaires are traditionally used as measurement tools; advances in Global Positioning Systems (GPS) technology allow for comparison. This review aimed to identify and report about studies comparing self-reported and GPS-measured journey durations. We systematically searched, appraised, and analysed published and unpublished articles from electronic databases, reference lists, bibliographies, and websites up to December 2012. Included studies used GPS and self-report to investigate trip duration. The average trip duration from each measure was compared and an aggregated, pooled estimate of the difference, weighted by number of trips, was calculated. We found 12 results from eight eligible studies. All studies showed self-reported journey times were greater than GPS-measured times. The difference between self-report and GPS times ranged from over-reporting of +2.2 to +13.5 minutes per journey. The aggregated, pooled estimate of the difference, weighted by number of trips, was over-report of +4.4 minutes (+28.6%). Studies comparing self-reported and GPS-measured journey duration have shown self-reported to be consistently over-reported across the study sample. Our findings suggest that when using self-reported journey behaviour, the journey durations should be treated as an over-estimation.     

Dynamic sensor zeroing algorithm of 6D IMU mounted on ground vehicles

The main focus of this paper is to compensate the steady state offset error of the 6D IMU which provides the measurements that include the vehicle linear accelerations and angular rates of all three axes. Additionally, the sensor compensation algorithm exploits the wheel speed data and the steering angle information, since they are already available in most of the modern mass production vehicles. These inputs are combined with the inverse vehicle kinematics to estimate the steady state offset error of each sensor inputs as it is done in a disturbance observer, and the raw sensor measurements are compensated by the estimated offset errors. The stability of the error dynamics regarding the integrated signal processing system is verified, and finally, the performance of the system is tested via experiments based on a real production SUV.     

Energy efficiency optimization of electric vehicle driven by in-wheel motors

Electric vehicle is considered to be the solution for energy and environment crisis, but it’s still not competitive enough with conventional vehicles because of the limited energy density and high cost of the power battery. So the energy efficiency is of the most importance for the control of electric vehicles. This paper looks into the energy efficiency optimization problem of electric vehicle driven by four in-wheel motors by developing a comprehensive energy efficiency model of the permanent magnet synchronous motor including the inverter. The calculated efficiency agrees with the measured data quite well. Based on the power loss analysis, the conclusion is drawn that in all driving or braking conditions the total torque requirement should be distributed evenly to all the motors in order to maximize the energy efficiency for electric vehicles driven by permanent magnet synchronous in-wheel motors. Vehicle test results show that the energy efficiency of the evenly distributed torque control is higher than the control strategy proposed by control allocation in literature.