Properties of a well-defined macroscopic fundamental diagram for urban traffic

A field experiment in Yokohama (Japan) revealed that a macroscopic fundamental diagram (MFD) linking space-mean flow, density and speed exists on a large urban area. It was observed that when the highly scattered plots of flow vs. density from individual fixed detectors were aggregated the scatter nearly disappeared and points grouped along a well defined curve. Despite these and other recent findings for the existence of well-defined MFDs for urban areas, these MFDs should not be universally expected. In this paper we investigate what are the properties that a network should satisfy, so that an MFD with low scatter exists. We show that the spatial distribution of vehicle density in the network is one of the key components that affect the scatter of an MFD and its shape. We also propose an analytical derivation of the spatial distribution of congestion that considers correlation between adjacent links. We investigate the scatter of an MFD in terms of errors in the probability density function of spatial link occupancy and errors of individual links’ fundamental diagram (FD). Later, using real data from detectors for an urban arterial and a freeway network we validate the proposed derivations and we show that an MFD is not well defined in freeway networks as hysteresis effects are present. The datasets in this paper consist of flow and occupancy measures from 500 fixed sensors in the Yokohama downtown area in Japan and 600 loop detectors in the Twin Cities Metropolitan Area Freeway network in Minnesota, USA.     

A self-learning system for local ramp metering with queue management

This paper presents the design and evaluation process of a self-learning system for local ramp metering control. This system is developed on the basis of reinforcement learning (RL) and can deal with the problem of on-ramp queue management through a continuous learning process. A general framework of the system design including the definition of RL elements and an algorithm that can accomplish the learning process is proposed. Simulation tests are carried out to evaluate the performance of the new system. In terms of the total time spent by road users, the new system can achieve a 30% reduction from the situation of no control, a result which is competitive with the widely accepted algorithm ALINEA. Meanwhile, simulation results show that the new system can keep on-ramp queues strictly under a series of pre-specified constraints, which proves its capability of managing on-ramp queues.     

Traffic noise studies in a tropical environment

This paper reports upon a survey of traffic noise annoyance in three residential districts of Trinidad, West Indies. Householder perceptions were solicited by means of a questionnaire survey and direct measurements of traffic noise levels were taken. The results were compared with surveys elsewhere. It was concluded that household status had little effect on annoyance perception, that at L₁₀ levels greater than 70 dB(A) at a dwelling facade the noise level is unacceptable. L₁₀ levels less than 65 dB(A) at the building facade are not perceived as annoying in the environment considered.     

Evaluate bus emissions generated near far-side and near-side stops and potential reductions by ITS: An empirical study

In this paper, we use second-by-second automatic vehicle location data to estimate bus emissions near far-side and near-side stops. We classify the bus running state near a stop into approach, dwell, and departure. A vehicle specific power approach is used to estimate bus emissions for each state. We show that bus emissions generated near stops can be significantly reduced by using certain intelligent transportation systems techniques.     

The design of a terminal for dangerous goods

This paper aims at examining the possibility of setting up a model terminal for the transportation of dangerous goods. It should be designed in such a manner that its use would be possible for any kind of transportation.

This consideration has been prompted by the interface between transportation planning and technology, as well as by the tendency for harmonizing international recommendations pertaining to the transportation and handling of dangerous goods, especially during the last decades where unified transport has gained ground due to the advantages provided for the safe consignment of dangerous cargoes.

Since the large increase in terminal productivity is due to the heavy investments that were effected in terminal installations and to the modernization of the administration‐management of terminals, a mathematical simulation has been adopted to assist the determination of the capacity of a terminal for dangerous goods.

It is evident that different criteria and various assumptions have been taken into account in order to facilitate a deeper analysis, without ignoring the contribution of dangerous goods to the socio‐economic development.

From the outset of the study, it was already clear that the said process will make it possible to present—as a model—a simple but well defined situation for the purpose of drawing useful conclusions.     

“互联网+”交通信号辅助优化机制探索

为优化城市道路交通信号控制方法,本文结合交通信号控制系统建设发展现状,分析当前各大城市交通信号控制系统普遍存在的问题,立足于互联网环境下的浮动车数据,提出基于互联网平台大数据的交通信号控制辅助优化机制。研究发现可利用互联网路口拥堵报警数据及时有效发现问题路口,利用路段拥堵指数及路口交通流参数变化趋势辅助评估配时方案的优化效果,并通过成都市应用实例证明该机制适用于当前交通控制场景需求,可有效辅助交通信号优化工作,是传统交通模式向真正智能交通模式过渡的阶梯。     

An empirical investigation on consumers’ intentions towards autonomous driving

Major steps towards implementation of autonomous and connected transport are being taken nowadays. The trend of automation technology being used in vehicles by the most important vehicle manufacturing industries is expected to move closer to high or fully Autonomous Vehicles (AVs) through technological advancements in sectors of robotics and artificial intelligence. Vehicles with autonomous driving capabilities are planning to be available on market, in full scale, in the next years. In the longer term substantial benefits are mainly expected for accessibility to transport, safety, traffic flow, emissions, fuel use and comfort. All these potential societal benefits will not be achieved unless AVs are accepted and used by a critical mass of people. Addressing these challenges, this paper: (a) proposes a technology acceptance modelling process by extending the original Technology Acceptance Model (TAM) to explain and predict consumers’ intensions towards AVs, (b) based on the proposed TAM-extended framework, a 30-question survey was conducted in order to investigate the factors influencing consumers’ intensions to use and accept AVs. Results show that the constructs of perceived usefulness, perceived ease to use, perceived trust and social influence, are all useful predictors of behavioral intentions to have or use AVs, with perceived usefulness having the strongest impact. The insights derived from this study could significantly contribute to ongoing research related to technology acceptance of AVs and are expected to allow automobile industries to improve their design and technology.     

Empirics of multi-modal traffic networks – Using the 3D macroscopic fundamental diagram

Traffic is multi-modal in most cities. However, the impacts of different transport modes on traffic performance and on each other are unclear – especially at the network level. The recent extension of the macroscopic fundamental diagram (MFD) into the 3D-MFD offers a novel framework to address this gap at the urban scale. The 3D-MFD relates the network accumulation of cars and public transport vehicles to the network travel production, for either vehicles or passengers. No empirical 3D-MFD has been reported so far.In this paper, we present the first empirical estimate of a 3D-MFD at the urban scale. To this end, we use data from loop detectors and automatic vehicle location devices (AVL) of the public transport vehicles in the city of Zurich, Switzerland. We compare two different areas within the city, that differ in their topology and share of dedicated lanes for public transport. We propose a statistical model of the 3D-MFD, which estimates the effects of the vehicle accumulation on car and public transport speeds under multi-modal traffic conditions. The results quantify the effects of both, vehicles and passengers, and confirm that a greater share of dedicated lanes reduces the marginal effects of public transport vehicles on car speeds. Lastly, we derive a new application of the 3D-MFD by identifying the share of public transport users that maximizes the journey speeds in an urban network accounting for all motorized transport modes.