Real world driving cycle for motorcycles in Edinburgh

Knowledge of the driving cycle is an important requirement in the evaluation of exhaust emissions. Data were collected from trips performed on five routes between the home addresses in the surrounding areas and place of work at Napier University in Edinburgh. A real world Edinburgh motorcycle driving cycle (EMDC) is developed for each of the urban and rural roads, using this data. Forty-four trips were made on the routes in both urban and rural areas. We assess motorcycle speed, percentage time spent in cruise, accelerations, decelerations and idling and their statistical validity over trip lengths. The results show that EMDC has a cycle length of 770 and 656 s for urban and rural trips, which are higher than those of the European Commission’s driving cycle for cars used for emission estimations of motorcycles. Time spent in acceleration and deceleration modes of EMDC are found to be significantly higher than in other driving cycle studies, reflecting diverse driving conditions in Edinburgh.     

Accidents involving pedestrians with their backs to traffic or facing traffic: an evaluation of crash characteristics and injuries

This paper examines pedestrian anatomical injuries and crash characteristics in back‐to‐traffic and facing‐traffic crashes. Pedestrian crashes involving pedestrians walking along streets (i.e. with their backs to traffic or facing traffic) have been overlooked in literature. Although this is not the most frequent type of crash, the crash consequence to pedestrians is a safety concern. Combining Taiwan A1A2 police‐reported accident data and data from the National Health Insurance Database from years 2003–2013, this paper examines anatomical injuries and crash characteristics in back‐to‐traffic and facing‐traffic crashes. There were a total of 830 and 2267 pedestrian casualties in back‐to‐traffic and facing‐traffic crashes respectively. The injuries sustained by pedestrians and crash characteristics of these two crash types were compared with those of other crossing types of crashes (nearside crash, nearside dart‐out crash, offside crash, and offside dart‐out crash). Odds of various injuries to body regions were estimated using logistic regressions. Key findings include that the percentage of fatalities in back‐to‐traffic crashes is the highest; logistic models reveal that pedestrians in back‐to‐traffic crashes sustained more head, neck, and spinal injuries than did pedestrians in other crash types, and unlit darkness and non‐built‐up roadways were associated with an increased risk of pedestrian head injuries. Several crash features (e.g. unlit darkness, overtaking manoeuvres, phone use by pedestrians and drivers, and intoxicated drivers) are more frequently evident in back‐to‐traffic crashes than in other types of crashes. The current research suggests that in terms of crash consequence, facing traffic is safer than back to traffic. Copyright © 2016 John Wiley & Sons, Ltd.     

Understanding transport mode choice for commuting: the role of affect

This study examines the relationship between positive and negative user valence and transport mode choice behaviour. We integrate latent attitudes ‘affect’ and ‘salience’ into transport mode choice models using the framework of integrated choice and latent variable modelling and simultaneous maximum likelihood estimation methods. The results are consistent with findings in similar travel behaviour and behavioural economics literature. The study extends the findings of previous research and has demonstrated that user sentiments about public transport mode and salient public transport experiences have a significant impact on travel mode choice behaviour. It was found that private motorised users are more sensitive to overcrowding and anti-social behaviours on PT than active and PT travellers. Key attitudinal indicators influencing individual transport choice behaviour are established to guide public policy. The key indicators of Affect and Salience must be analysed and addressed through public policy to enhance PT user experience and develop services and facilities to increase the utility of PT in-vehicle travel time.     

基于车载通信实时交通信息的城市道路路径选择方法

为车辆出行规划最优路径是智能交通系统（ITS）的一个重要研究目标.本文根据有效的实时交通信息提出一种车辆路径选择机制,这种机制包括两个阶段.第一阶段,由有线或无线传输设备和车载通信设备组成的交通信息系统（TIS）,收集用于车辆出行导航的实时交通信息数据,并将其存储至交通信息中心.第二阶段,利用有效的实时交通信息,提出两种基于Dijkstra 的路径选择算法,即一步路径选择和逐步路径选择.前者在整个车辆出行过程中,仅在其出行开始阶段单次计算通往目的地的最优路径.逐步路径选择在每个交叉口都实时更新并计算通往目的地的最优路径,并提出使用两种新优化方法以避免算法形成环路.利用NCTUns 6.0 进行路网仿真,结果表明两种算法都借助于实时交通信息,且逐步路径选择优于一步路径选择.