Impact assessment of autonomous DRT systems

The market entrance of shared autonomous vehicles (SAV) may have disruptive effects on current transport systems and may lead to their total transformation. For many small and medium-sized cities, a full replacement of public transport services by these systems seems to be possible. For a transport system operator, such a system requires a bigger fleet of vehicles than before, however, vehicles are less expensive and fewer staff is needed for the actual operation. In this paper, we are using a simulation-based approach to evaluate the service quality and operating cost of a demand responsive transit (DRT) system for the city of Cottbus (100 000 inhabitants), Germany. The simulation model used is based on an existing MATSim model of the region that depicts a typical work day. Results suggest, that the current public transport system may be replaced by a system of 300 to 400 DRT vehicles, depending on their operational mode. Compared to previous, schedule based public transport, passengers do not need to transfer, and their overall travel times may be reduced significantly. Results for the cost comparison are preliminary, but results suggest that an autonomous DRT system is not necessarily more expensive than the current public transport system

Motion Hub, the implementation of an integrated end-to-end journey planner

© AET 2018 and contributorsThe term “eMobility” and been brought into use partly to encourage use of electric vehicles but more especially to focus on the transformation from electric vehicles as products to electrified personal transport as a service. Under the wider umbrella of Mobility-as-a-Service (MaaS) this has accompanied the growth of car clubs in general. The Motion Hub project has taken this concept a step further to include not just the car journey but the end-to-end journey. The booking of multifaceted journeys is well established in the leisure and business travel industries, where flights, car hire and hotels are regularly booked with a single transaction on a website. To complete an end-to-end scenario Motion Hub provides integration of public transport with electric vehicle and electric bike use. Building on a previous InnovateUK funded project that reviewed the feasibility of an integrated journey management system, the Motion Hub project has brought together a Car Club, a University, and EV infrastructure company, a bicycle hire company with electric bicycle capabilities and a municipality to implement a scheme and test it on the ground. At the heart of the project has been the development of a website that integrates the public transport booking with the hire of electric vehicles or bicycles. Taking the implementation to a fully working system accessible to members of the public presents a number of significant challenges. This paper identifies those challenges, details the progress and success of the Motion Hub and sets out the lessons learnt about end-to-end travel. The project was fortunate to have as its municipal partner the Council of a sizeable South East England town, Southend-on-Sea. With a population of 174,800 residents with good road, rail and air links there is considerable traffic in and out of the town. The Council has already shown its commitment to sustainable transport. In the previous six years it had installed a number of electric vehicle charging points for use by the public and latterly had trialled car club activity. An early challenge in the project was the location of physical infrastructure in an already crowded municipal space in order to provide the local ‘spokes’ of the system. In addition to its existing charging points, Southend now has four locations where electric cars can be hired, five where electric bikes are available and the local resources to maintain these assets. Combining a number of web-based services and amalgamating their financial transactions is relatively straightforward. However, introducing the potential for public transport ticketing as well raises additional security, scale and financial constraints. The project has engaged with major players and regulators across the public transport industry.Peer reviewe

Data-Driven Multi-step Demand Prediction for Ride-Hailing Services Using Convolutional Neural Network

Ride-hailing services are growing rapidly and becoming one of the most disruptive technologies in the transportation realm. Accurate prediction of ride-hailing trip demand not only enables cities to better understand people's activity patterns, but also helps ride-hailing companies and drivers make informed decisions to reduce deadheading vehicle miles traveled, traffic congestion, and energy consumption. In this study, a convolutional neural network (CNN)-based deep learning model is proposed for multi-step ride-hailing demand prediction using the trip request data in Chengdu, China, offered by DiDi Chuxing. The CNN model is capable of accurately predicting the ride-hailing pick-up demand at each 1-km by 1-km zone in the city of Chengdu for every 10 minutes. Compared with another deep learning model based on long short-term memory, the CNN model is 30% faster for the training and predicting process. The proposed model can also be easily extended to make multi-step predictions, which would benefit the on-demand shared autonomous vehicles applications and fleet operators in terms of supply-demand rebalancing. The prediction error attenuation analysis shows that the accuracy stays acceptable as the model predicts more steps

Transport and Older People: Integrating Transport Planning Tools with User Needs

This study was funded through a pump-priming grant from the Strategic Promotion of Ageing Research Capacity (SPARC) programme. The purpose of the project was to bring together transport and public health research in order to demonstrate how the involvement of older people can help improve tools for transport planning. The study was unique in that it brought together public health and transport planning and engineering with older people to consider how services can be more responsive to older people’s transport needs. The project had five research objectives: 1. To investigate how accessibility problems impact on older people’s independence 2. To determine the extent to which currently available data sources and modelling tools reflect older people’s stated accessibility needs 3. To understand how the gap between expected and perceived accessibility problems varies across different categories of older people 4. To pilot techniques that could be applied to provide a more robust measure of accessibility for older people. 5. To build new research capacity across disciplines to develop a national focus on the interactions between ageing and transport planning. The methods were determined on the basis of ‘appropriate tools with maximum output’. Focus group interviews were selected as a useful tool for reaching a large number of older people within a limited time span, for providing an arena for discussion and debate about a topical subject and for generating ideas for improving transport planning. Following the interviews accompanied walks were undertaken with older people in a range of road environments and traffic situations. The purpose of these walks was to observe and explore the way older people interact with their environment. Data from the focus group interviews and the observations were compared with the outputs from an accessibility planning tool used by local authorities to plan accessible and acceptable transport routes (Accession™). The purpose of this exercise was to investigate whether or not such tools are able to take into account the varying needs of older people. The study was undertaken over eight months. Eighty one older people living in the Leeds district took part in the focus groups. They covered a broad range of mobility levels and used a variety of transport types, as such a reasonably rounded perspective on the issues concerned was offered. In addition six walks were undertaken with older people in their community

Dawn of autonomous vehicles: review and challenges ahead

This paper reviews the state of the art on autonomous vehicles as of 2017, including their impact at socio-economic, energy, safety, congestion and land-use levels. This impact study focuses on the issues that are common denominators and are bound to arise independently of regional factors, such as (but not restricted to) change to vehicle ownership patterns and driver behaviour, opportunities for energy and emissions savings, potential for accident reduction and lower insurance costs, and requalification of urban areas previously assigned to parking. The challenges that lie ahead for carmakers, law and policy makers are also explored, with an emphasis on how these challenges affect the urban infrastructure and issues they create for municipal planners and decision makers. The paper concludes with strengths, weaknesses, opportunities, and threats analysis that integrates and relates all these aspects.info:eu-repo/semantics/publishedVersio

Transportation for an Aging Population: Promoting Mobility and Equity for Low-Income Seniors

This study explores the travel patterns, needs, and mobility problems faced by diverse low-income, inner-city older adults in Los Angeles in order to identify solutions to their mobility challenges. The study draws information from: (1) a systematic literature review of the travel patterns of older adults; (2) a review of municipal policies and services geared toward older adult mobility in six cities; (3) a quantitative analysis of the mobility patterns of older adults in California using the California Household Travel Survey; and (4) empirical work with 81 older adults residing in and around Los Angeles’ inner-city Westlake neighborhood, who participated in focus groups, interviews, and walkabouts around their neighborhood