Emely Richter
Biographic Data
| ID | 8886977 |
|---|---|
| NAME | Emely Richter |
| GIVEN NAMES | Emely |
| FAMILY NAME | Richter |
| SIGNATURE | RICHTER E |
| AFFILIATIONS | University of Stuttgart |
| ORCID | 0000-0002-1582-6089 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Impacts of highly automated vehicles on travel demand
Automated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific pass…
Vehicle scheduling for on-demand vehicle fleets in macroscopic travel demand models
The planning of on-demand services requires the formation of vehicle schedules consisting of service trips and empty trips. This paper presents an algorithm for building vehicle schedules that uses time-dependent demand matrices (= service trips) as input and determines time-dependent empty trip matrices and the number of required vehicles as a result. The presented approach is intended for long-term, strategic transport planning. For this purpos…
No prominent works on this page.
Impacts of highly automated vehicles on travel demand
Automated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific pass…
Vehicle scheduling for on-demand vehicle fleets in macroscopic travel demand models
The planning of on-demand services requires the formation of vehicle schedules consisting of service trips and empty trips. This paper presents an algorithm for building vehicle schedules that uses time-dependent demand matrices (= service trips) as input and determines time-dependent empty trip matrices and the number of required vehicles as a result. The presented approach is intended for long-term, strategic transport planning. For this purpos…
Computer Science (2 works) · Demand management (2 works) · Economics (2 works) · Engineering (2 works) · Operations research (2 works) · Transport engineering (2 works) · Transportation and Mobility Innovations (2 works) · Transportation Planning and Optimization (2 works) · Algorithm (1 work) · Business (1 work)