The short-term impacts of cooperative, connected, and automated mobility on passenger transport, Deliverable D6.2 of the H2020 project LEVITATE

Haouari, Rajae; Chaudhry, Amna; Sha, Hua; Richter, Gerald; Singh, Mohit; Papazikou, Evita; Boghani, Hitesh; Roussou, Julia; Hu, Ben; Thomas, Pete; Quddus, Mohammed; Morris, Andrew

Abstract

The aim of the LEVITATE project is to prepare a new impact assessment framework to enable policymakers to manage the introduction of cooperative, connected, and automated transport systems, maximise the benefits and utilise the technologies to achieve societal objectives. As part of this work, the LEVITATE project seeks to forecast societal level impacts of cooperative, connected, and automated mobility (CCAM).
The aim of this report is to provide an analysis of the short-term impacts, described in Deliverable 3.1 (Elvik et al.,2019), of different passenger car transport sub-use cases (policy interventions). The short-term impacts analysed include travel time, vehicle operating cost, and access to travel. Based on several discussions with the stakeholder reference group (SRG) including city officials and industry professionals, a list of key interventions, termed sub-use cases (SUCs), were selected to be tested through different applicable methods. These include road use pricing (rup), provision of dedicated lanes on urban highways, parking price policies, parking space regulations, automated ride sharing, and green light optimal speed advisory (GLOSA). For assessing the travel time impact, mesoscopic and microscopic simulation as well as Delphi method have been used. The Delphi method was also used to estimate impacts on vehicle operating cost and access to travel. Road Use Pricing was modelled through mesoscopic simulation using the full-scale city-level model of Vienna. All other sub-use cases were analysed through microscopic simulation method using Manchester network for Dedicated Lanes, Automated Ride Sharing and GLOSA, Leicester network for Parking Space Regulations, and Santander model for testing Parking Price Policies.
CAVs deployment was tested from 0 to 100% with 20% increments under all applicable sub-use cases. The behaviours of CAVs were defined based on an extensive literature review performed as part of the LEVITATE project. Two types of connected and automated vehicles (CAV) were included in the analysis, 1st Generation CAVs and 2nd Generation CAVs, where 2nd generation CAVs were assumed to have improved driving characteristics and enhanced cognitive capabilities, which will lead to shorter time gaps as compared to the 1st generation CAVs and human-driven vehicles (HDV).
Overall, results from the policy interventions tested under passenger transport provided useful insights with regard to their implications and short-term impacts. Regarding the impact on travel time, the findings from different assessment methods were in line for the majority of studied policy measures. The implementation of a static road use pricing strategy in the city of Vienna indicated more consistent benefits due to static pricing with respect to the average travel time, while the impact due to dynamic road use pricing implementation was found difficult to predict due to the added complexity in traffic operation. The responses from majority of the Delphi study participants also indicated similar trends, suggesting that the introduction of city tool policies would positively impact travel time.
Findings from the microsimulation results of provision of a dedicated lane for CAVs on urban highways indicated maximum travel time savings under innermost lane configuration and at moderate market penetration rate (MPR) of CAVs (60% HDVs, 40% CAVs). The experts’ opinions in this regard also indicated maximum travel time reduction under the innermost lane placement scenario. Parking management was identified as one of the key areas of interest by SRG. In this regard, various on-street parking space regulations were tested, including replacing parking lanes with driving lanes, cycle lanes, public spaces, pick-up drop-off areas, and removing half of the on-street parking. Results indicated positive impacts on traffic operation when parking spaces were replaced with driving lanes, cycle lanes, and public spaces, compared to replacement with pick-up/drop-off areas and removing half of the parking spaces. In addition to parking space replacement interventions, a parking pricing policy was also tested in the inner-city domain to evaluate the impact of various parking strategies on travel time. Under all the tested parking price schemes, on average, the results showed an increase in travel time with respect to no policy intervention (baseline) scenario. It was identified that the right policy decision on parking pricing is critical in avoiding negative impacts on traffic.
Under passenger transport, an automated ridesharing service was also analysed in one of the study networks which showed an increase in travel time due to congestion caused by the empty pick-up trips and circulating behaviour of shared vehicles (using low capacity and secondary roads). It was found that benefits from such services can only be obtained with an increased willingness to share.
With regard to connectivity, the Green Light Optimal Speed Advisory system was tested on a busy corridor in the Manchester network with three signalized intersections, sufficiently apart for GLOSA implementation. All CAVs were assumed to be GLOSA equipped. Results exhibited reduction in number of stops and travel time with GLOSA application as compared with No-GLOSA (baseline) scenario. Maximum travel time savings can be achieved when applied at multiple intersections or at corridor level.
The findings from Delphi study showed that introduction of automated vehicles are expected to increase operating cost in the short term which can expected to be reduced with higher MPR while access to travel was indicated to progressively increase with increasing MPR of automated vehicles. Automated ride sharing services were foreseen to have a significant impact in reducing vehicle operating costs and increasing access to travel.
Overall, the results provide some important messages for city departments of governments to manage potential consequences due to the introduction of CAVs in the transport system. The findings from different policy interventions, tested in this deliverable, exhibit that increasing MPR of CAVs solely may not have positive impacts and the right policy measures are critical for achieving positive impacts (e.g., travel time savings) with the introduction of CAVs. The results also indicate the importance of the transition phase to full fleet penetration of CAVs.

• Report Type: Project Report
• Online Publication Date: Nov 3, 2021
• Publication Date: Nov 3, 2021
• Deposit Date: Jun 13, 2024
• Public URL: https://uwe-repository.worktribe.com/output/12044546